From 013e371fd13bb165c7d681eed3d07aa30148254c Mon Sep 17 00:00:00 2001
From: Shyue Ping Ong <shyuep@gmail.com>
Date: Fri, 28 Jun 2024 13:34:04 -0700
Subject: [PATCH] Fix VASP input output example.

---
 .../2013-01-01-Bandstructure of NiO.ipynb     |  921 ---
 ...tion Energies with the Materials API.ipynb |   43 +-
 ...-14-Inputs and Analysis of VASP runs.ipynb |  193 +-
 notebooks/Al-band/INCAR                       |   25 +
 notebooks/Al-band/KPOINTS                     |  216 +
 notebooks/Al-band/POSCAR                      |    9 +
 notebooks/Al-band/POTCAR                      | 1768 +++++
 notebooks/Al-band/vasprun.xml.gz              |  Bin 0 -> 32866 bytes
 notebooks/Al-dos/INCAR                        |   26 +
 notebooks/Al-dos/KPOINTS                      |    4 +
 notebooks/Al-dos/POSCAR                       |    9 +
 notebooks/Al-dos/POTCAR                       | 1768 +++++
 notebooks/Al-dos/vasprun.xml.gz               |  Bin 0 -> 32866 bytes
 notebooks/Al-relax.cif                        |   27 +
 notebooks/{Si-relax => Al-relax}/INCAR        |    4 +-
 notebooks/Al-relax/KPOINTS                    |    4 +
 notebooks/Al-relax/OUTCAR                     | 6202 +++++++++++++++++
 notebooks/Al-relax/POSCAR                     |    9 +
 notebooks/Al-relax/POTCAR                     | 1768 +++++
 notebooks/Al-relax/vasprun.xml.gz             |  Bin 0 -> 32866 bytes
 notebooks/Al-static/INCAR                     |   23 +
 notebooks/Al-static/KPOINTS                   |    4 +
 notebooks/Al-static/OUTCAR                    | 6202 +++++++++++++++++
 notebooks/Al-static/POSCAR                    |    9 +
 notebooks/Al-static/POTCAR                    | 1768 +++++
 notebooks/Al-static/vasprun.xml.gz            |  Bin 0 -> 32866 bytes
 notebooks/Al.cif                              |   27 +
 notebooks/Si-relax.cif                        |   27 +
 notebooks/Si-relax/KPOINTS                    |    4 -
 notebooks/Si-relax/POSCAR                     |   10 -
 notebooks/Si-relax/POTCAR                     | 1768 -----
 notebooks/Si-static/INCAR                     |   23 +
 notebooks/Si-static/KPOINTS                   |    4 +
 notebooks/Si-static/POSCAR                    |    9 +
 notebooks/Si-static/POTCAR                    | 1768 +++++
 notebooks/Si.cif                              |  218 -
 notebooks/vasprun.Al.xml.gz                   |  Bin 0 -> 32866 bytes
 psp/POT_GGA_PAW_PBE/POTCAR.Al.gz              |  Bin 0 -> 59471 bytes
 38 files changed, 21866 insertions(+), 2994 deletions(-)
 delete mode 100644 notebooks/2013-01-01-Bandstructure of NiO.ipynb
 create mode 100644 notebooks/Al-band/INCAR
 create mode 100644 notebooks/Al-band/KPOINTS
 create mode 100644 notebooks/Al-band/POSCAR
 create mode 100644 notebooks/Al-band/POTCAR
 create mode 100644 notebooks/Al-band/vasprun.xml.gz
 create mode 100644 notebooks/Al-dos/INCAR
 create mode 100644 notebooks/Al-dos/KPOINTS
 create mode 100644 notebooks/Al-dos/POSCAR
 create mode 100644 notebooks/Al-dos/POTCAR
 create mode 100644 notebooks/Al-dos/vasprun.xml.gz
 create mode 100644 notebooks/Al-relax.cif
 rename notebooks/{Si-relax => Al-relax}/INCAR (85%)
 create mode 100644 notebooks/Al-relax/KPOINTS
 create mode 100644 notebooks/Al-relax/OUTCAR
 create mode 100644 notebooks/Al-relax/POSCAR
 create mode 100644 notebooks/Al-relax/POTCAR
 create mode 100644 notebooks/Al-relax/vasprun.xml.gz
 create mode 100644 notebooks/Al-static/INCAR
 create mode 100644 notebooks/Al-static/KPOINTS
 create mode 100644 notebooks/Al-static/OUTCAR
 create mode 100644 notebooks/Al-static/POSCAR
 create mode 100644 notebooks/Al-static/POTCAR
 create mode 100644 notebooks/Al-static/vasprun.xml.gz
 create mode 100644 notebooks/Al.cif
 create mode 100644 notebooks/Si-relax.cif
 delete mode 100644 notebooks/Si-relax/KPOINTS
 delete mode 100644 notebooks/Si-relax/POSCAR
 delete mode 100644 notebooks/Si-relax/POTCAR
 create mode 100644 notebooks/Si-static/INCAR
 create mode 100644 notebooks/Si-static/KPOINTS
 create mode 100644 notebooks/Si-static/POSCAR
 create mode 100644 notebooks/Si-static/POTCAR
 delete mode 100644 notebooks/Si.cif
 create mode 100644 notebooks/vasprun.Al.xml.gz
 create mode 100644 psp/POT_GGA_PAW_PBE/POTCAR.Al.gz

diff --git a/notebooks/2013-01-01-Bandstructure of NiO.ipynb b/notebooks/2013-01-01-Bandstructure of NiO.ipynb
deleted file mode 100644
index 5338ccd..0000000
--- a/notebooks/2013-01-01-Bandstructure of NiO.ipynb	
+++ /dev/null
@@ -1,921 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Band Structure of NiO\n",
-    "\n",
-    "##### Germain Salvato Vallverdu [germain.vallverdu@univ-pau.fr](germain.vallverdu@univ-pau.fr)\n",
-    "\n",
-    "Short examples to show how to extract or plot the band structure from a [VASP](http://vasp.at/) calculation using [pymagen](http://pymatgen.org)."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Uncomment the subsequent lines in this cell to install dependencies for Google Colab.\n",
-    "# !pip install pymatgen==2022.7.19\n",
-    "from __future__ import annotations"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import os\n",
-    "\n",
-    "import matplotlib.pyplot as plt\n",
-    "from pymatgen.electronic_structure.core import Spin\n",
-    "from pymatgen.electronic_structure.plotter import BSDOSPlotter, BSPlotter, DosPlotter\n",
-    "from pymatgen.io.vasp.outputs import BSVasprun, Vasprun\n",
-    "\n",
-    "%matplotlib inline"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "I work in a directory that contains the calculations of the NiO band structure. Look at [this example](http://cms.mpi.univie.ac.at/wiki/index.php/Fcc_Si_bandstructure) to learn how to obtain a band structure from VASP calculations."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "BandStructureNiO.ipynb  KPOINTS                 WAVECAR\r\n",
-      "CHG                     OSZICAR                 XDATCAR\r\n",
-      "CHGCAR                  OUTCAR                  jNiO\r\n",
-      "CONTCAR                 PCDAT                   slurm-348507.out\r\n",
-      "DOSCAR                  POSCAR                  vasprun.xml\r\n",
-      "EIGENVAL                POTCAR\r\n",
-      "INCAR                   PROCAR\r\n"
-     ]
-    }
-   ],
-   "source": [
-    "os.listdir()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### 1) Read vasprun.xml and extract the band structure"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "run = BSVasprun(\"vasprun.xml\", parse_projected_eigen=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "bs = run.get_band_structure(\"KPOINTS\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "You can obtain some information about the band structure :"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "number of bands 14\n"
-     ]
-    }
-   ],
-   "source": [
-    "print(\"number of bands\", bs.nb_bands)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "number of kpoints 200\n"
-     ]
-    }
-   ],
-   "source": [
-    "print(\"number of kpoints\", len(bs.kpoints))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "False"
-      ]
-     },
-     "execution_count": null,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "bs.is_metal()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "True"
-      ]
-     },
-     "execution_count": null,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "bs.is_spin_polarized"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### 2) Extract a given band or eigenvalues\n",
-    "\n",
-    "The `bands` attribute of the `BaandStructure` object is a dictionnary of arrays that contains all the bands. The shape is the following :\n",
-    "\n",
-    "    {Spin.up: np.array((nb_bands, nb_kpoints)), Spin.down: np.array((nb_bands, nb_kpoints))}"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "{<Spin.up: 1>: array([[-12.6235, -12.6259, -12.6329, ..., -14.3847, -14.3914, -14.3936],\n",
-       "        [ -3.5768,  -3.5725,  -3.5597, ...,  -1.3942,  -1.3809,  -1.3765],\n",
-       "        [ -2.9295,  -2.9282,  -2.9243, ...,  -1.3815,  -1.3777,  -1.3765],\n",
-       "        ..., \n",
-       "        [ 20.4623,  20.4656,  20.4757, ...,  23.0714,  23.0629,  23.0559],\n",
-       "        [ 20.4623,  20.4656,  20.4757, ...,  28.6536,  28.9814,  29.1847],\n",
-       "        [ 26.6233,  26.6231,  26.6232, ...,  29.26  ,  29.2519,  29.3045]]),\n",
-       " <Spin.down: -1>: array([[-12.2547, -12.2571, -12.2642, ..., -14.0377, -14.0444, -14.0466],\n",
-       "        [ -3.0758,  -3.0713,  -3.0576, ...,   0.7154,   0.723 ,   0.7256],\n",
-       "        [  0.5472,   0.5477,   0.5494, ...,   0.7227,   0.7249,   0.7256],\n",
-       "        ..., \n",
-       "        [ 20.845 ,  20.8494,  20.8627, ...,  23.4954,  23.5054,  23.5058],\n",
-       "        [ 20.845 ,  20.8494,  20.8627, ...,  29.7286,  29.9021,  29.9973],\n",
-       "        [ 27.0945,  27.0942,  27.094 , ...,  29.9072,  29.9491,  29.9978]])}"
-      ]
-     },
-     "execution_count": null,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "bs.bands"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "(14, 200)"
-      ]
-     },
-     "execution_count": null,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "bs.bands[Spin.up].shape"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "The 9th bands of spin down is extracted by :"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([ 12.1302,  12.131 ,  12.1334,  12.137 ,  12.1416,  12.1469,\n",
-       "        12.1521,  12.1568,  12.1601,  12.1613,  12.1594,  12.1535,\n",
-       "        12.1428,  12.1264,  12.1034,  12.073 ,  12.0347,  11.988 ,\n",
-       "        11.9326,  11.8683,  11.7951,  11.7132,  11.6228,  11.5244,\n",
-       "        11.4186,  11.3058,  11.1867,  11.062 ,  10.9324,  10.7987,\n",
-       "        10.6617,  10.522 ,  10.3805,  10.238 ,  10.0954,   9.9536,\n",
-       "         9.8135,   9.6761,   9.5424,   9.4137,   9.2911,   9.176 ,\n",
-       "         9.0696,   8.9734,   8.8888,   8.8172,   8.76  ,   8.7182,\n",
-       "         8.6928,   8.6842,   8.6842,   8.6957,   8.7301,   8.7877,\n",
-       "         8.8689,   8.9736,   9.1009,   9.2495,   9.4174,   9.602 ,\n",
-       "         9.8008,  10.011 ,  10.2301,  10.4558,  10.6859,  10.9185,\n",
-       "        11.1519,  11.3844,  11.6146,  11.8408,  12.0616,  12.2756,\n",
-       "        12.4812,  12.677 ,  12.8614,  13.0327,  13.1893,  13.3294,\n",
-       "        13.4513,  13.5535,  13.6345,  13.6936,  13.7303,  13.7454,\n",
-       "        13.7402,  13.7171,  13.6793,  13.6301,  13.5731,  13.5118,\n",
-       "        13.4493,  13.3882,  13.3306,  13.278 ,  13.232 ,  13.1933,\n",
-       "        13.1626,  13.1405,  13.1271,  13.1226,  13.1226,  13.1235,\n",
-       "        13.1262,  13.1307,  13.1371,  13.1452,  13.1551,  13.1667,\n",
-       "        13.1802,  13.1953,  13.2121,  13.2307,  13.2509,  13.2727,\n",
-       "        13.2961,  13.3211,  13.3475,  13.3756,  13.405 ,  13.4359,\n",
-       "        13.4681,  13.5016,  13.5365,  13.5725,  13.6098,  13.6482,\n",
-       "        13.6876,  13.7282,  13.7697,  13.8122,  13.8555,  13.8997,\n",
-       "        13.9447,  13.9904,  14.0368,  14.0839,  14.1315,  14.1797,\n",
-       "        14.2283,  14.2774,  14.3268,  14.3766,  14.4267,  14.477 ,\n",
-       "        14.5274,  14.578 ,  14.6285,  14.6791,  14.7295,  14.7798,\n",
-       "        14.7798,  14.9285,  15.0712,  15.2025,  15.313 ,  15.3886,\n",
-       "        15.4144,  15.3871,  15.3166,  15.2167,  15.097 ,  14.9637,\n",
-       "        14.8204,  14.6694,  14.5122,  14.35  ,  14.1833,  14.0129,\n",
-       "        13.839 ,  13.662 ,  13.4821,  13.2995,  13.1142,  12.9266,\n",
-       "        12.7366,  12.5442,  12.3498,  12.1532,  11.9547,  11.7545,\n",
-       "        11.5529,  11.3502,  11.1468,  10.9433,  10.7401,  10.5382,\n",
-       "        10.3384,  10.1418,   9.9497,   9.7636,   9.5851,   9.4164,\n",
-       "         9.2595,   9.1167,   8.9907,   8.8837,   8.7979,   8.7352,\n",
-       "         8.6971,   8.6842])"
-      ]
-     },
-     "execution_count": null,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "bs.bands[Spin.down][9, :]"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "In order to print a band and the corresponding k-points :"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "kx = 0.500  ky = 0.500  kz = 0.500   eps(k) =  12.1302\n",
-      "kx = 0.490  ky = 0.490  kz = 0.490   eps(k) =  12.1310\n",
-      "kx = 0.480  ky = 0.480  kz = 0.480   eps(k) =  12.1334\n",
-      "kx = 0.469  ky = 0.469  kz = 0.469   eps(k) =  12.1370\n",
-      "kx = 0.459  ky = 0.459  kz = 0.459   eps(k) =  12.1416\n",
-      "kx = 0.449  ky = 0.449  kz = 0.449   eps(k) =  12.1469\n",
-      "kx = 0.439  ky = 0.439  kz = 0.439   eps(k) =  12.1521\n",
-      "kx = 0.429  ky = 0.429  kz = 0.429   eps(k) =  12.1568\n",
-      "kx = 0.418  ky = 0.418  kz = 0.418   eps(k) =  12.1601\n",
-      "kx = 0.408  ky = 0.408  kz = 0.408   eps(k) =  12.1613\n",
-      "...\n",
-      "kx = 0.077  ky = 0.153  kz = 0.077   eps(k) =   9.7636\n",
-      "kx = 0.069  ky = 0.138  kz = 0.069   eps(k) =   9.5851\n",
-      "kx = 0.061  ky = 0.122  kz = 0.061   eps(k) =   9.4164\n",
-      "kx = 0.054  ky = 0.107  kz = 0.054   eps(k) =   9.2595\n",
-      "kx = 0.046  ky = 0.092  kz = 0.046   eps(k) =   9.1167\n",
-      "kx = 0.038  ky = 0.077  kz = 0.038   eps(k) =   8.9907\n",
-      "kx = 0.031  ky = 0.061  kz = 0.031   eps(k) =   8.8837\n",
-      "kx = 0.023  ky = 0.046  kz = 0.023   eps(k) =   8.7979\n",
-      "kx = 0.015  ky = 0.031  kz = 0.015   eps(k) =   8.7352\n",
-      "kx = 0.008  ky = 0.015  kz = 0.008   eps(k) =   8.6971\n",
-      "kx = 0.000  ky = 0.000  kz = 0.000   eps(k) =   8.6842\n"
-     ]
-    }
-   ],
-   "source": [
-    "n = 0\n",
-    "for kpoints, e in zip(bs.kpoints, bs.bands[Spin.down][9, :]):\n",
-    "    n += 1\n",
-    "    if n == 11:\n",
-    "        print(\"...\")\n",
-    "    if 10 < n < 190:\n",
-    "        continue\n",
-    "\n",
-    "    print(\n",
-    "        \"kx = %5.3f  ky = %5.3f  kz = %5.3f   eps(k) = %8.4f\"\n",
-    "        % (tuple(kpoints.frac_coords) + (e,))\n",
-    "    )"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### 3) Plot a simple band structure"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "bsplot = BSPlotter(bs)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "5.35857687\n"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.legend.Legend at 0x10eeae470>"
-      ]
-     },
-     "execution_count": null,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x10e64b908>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# get the plot\n",
-    "bsplot.get_plot(ylim=(-20, 10), zero_to_efermi=True)\n",
-    "print(bs.efermi)\n",
-    "\n",
-    "# add some features\n",
-    "ax = plt.gca()\n",
-    "ax.set_title(\"NiO Band Structure\", fontsize=20)\n",
-    "xlim = ax.get_xlim()\n",
-    "ax.hlines(0, xlim[0], xlim[1], linestyles=\"dashed\", color=\"black\")\n",
-    "\n",
-    "# add legend\n",
-    "ax.plot((), (), \"b-\", label=\"spin up\")\n",
-    "ax.plot((), (), \"r--\", label=\"spin down\")\n",
-    "ax.legend(fontsize=16, loc=\"upper left\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "#### 3.1) Extract data from the plot\n",
-    "\n",
-    "You can get data from the plot and in particular the (x, y) coordinates of each band."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "data = bsplot.bs_plot_data()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "dict_keys(['ticks', 'distances', 'energy', 'vbm', 'cbm', 'lattice', 'zero_energy', 'is_metal', 'band_gap'])"
-      ]
-     },
-     "execution_count": null,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "data.keys()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "For example, here, you print the abscissa and the energy of the 9th band. Keep in mind that here the data are the ones used to do the plot. Thus the zero to fermi translation is already done according to the `BSPlotter` class."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "--------------------\n",
-      "  0.0000   6.8926\n",
-      "  0.0273   6.8929\n",
-      "  0.0546   6.8941\n",
-      "  0.0819   6.8956\n",
-      "  0.1092   6.8974\n",
-      "  0.1365   6.8990\n",
-      "  0.1638   6.8999\n",
-      "  0.1911   6.8994\n",
-      "  0.2184   6.8970\n",
-      "  0.2457   6.8919\n",
-      "  0.2730   6.8832\n",
-      "  0.3003   6.8702\n",
-      "  0.3276   6.8520\n",
-      "  0.3549   6.8278\n",
-      "  0.3822   6.7970\n",
-      "  0.4095   6.7589\n",
-      "  0.4368   6.7131\n",
-      "  0.4641   6.6591\n",
-      "  0.4914   6.5967\n",
-      "  0.5187   6.5259\n",
-      "  0.5460   6.4468\n",
-      "  0.5733   6.3595\n",
-      "  0.6006   6.2643\n",
-      "  0.6279   6.1617\n",
-      "  0.6552   6.0522\n",
-      "  0.6825   5.9364\n",
-      "  0.7097   5.8148\n",
-      "  0.7370   5.6881\n",
-      "  0.7643   5.5569\n",
-      "  0.7916   5.4220\n",
-      "  0.8189   5.2841\n",
-      "  0.8462   5.1440\n",
-      "  0.8735   5.0024\n",
-      "  0.9008   4.8600\n",
-      "  0.9281   4.7178\n",
-      "  0.9554   4.5765\n",
-      "  0.9827   4.4371\n",
-      "  1.0100   4.3006\n",
-      "  1.0373   4.1680\n",
-      "  1.0646   4.0403\n",
-      "  1.0919   3.9189\n",
-      "  1.1192   3.8049\n",
-      "  1.1465   3.6996\n",
-      "  1.1738   3.6045\n",
-      "  1.2011   3.5209\n",
-      "  1.2284   3.4503\n",
-      "  1.2557   3.3938\n",
-      "  1.2830   3.3526\n",
-      "  1.3103   3.3275\n",
-      "  1.3376   3.3191\n",
-      "--------------------\n",
-      "  1.3376   3.3191\n",
-      "  1.3691   3.3303\n",
-      "  1.4006   3.3638\n",
-      "  1.4322   3.4189\n",
-      "  1.4637   3.4946\n",
-      "  1.4952   3.5897\n",
-      "  1.5267   3.7025\n",
-      "  1.5583   3.8313\n",
-      "  1.5898   3.9745\n",
-      "  1.6213   4.1303\n",
-      "  1.6528   4.2969\n",
-      "  1.6843   4.4727\n",
-      "  1.7159   4.6560\n",
-      "  1.7474   4.8454\n",
-      "  1.7789   5.0394\n",
-      "  1.8104   5.2363\n",
-      "  1.8419   5.4352\n",
-      "  1.8735   5.6347\n",
-      "  1.9050   5.8335\n",
-      "  1.9365   6.0304\n",
-      "  1.9680   6.2241\n",
-      "  1.9995   6.4135\n",
-      "  2.0311   6.5974\n",
-      "  2.0626   6.7746\n",
-      "  2.0941   6.9436\n",
-      "  2.1256   7.1033\n",
-      "  2.1571   7.2523\n",
-      "  2.1887   7.3891\n",
-      "  2.2202   7.5125\n",
-      "  2.2517   7.6211\n",
-      "  2.2832   7.7139\n",
-      "  2.3148   7.7899\n",
-      "  2.3463   7.8485\n",
-      "  2.3778   7.8898\n",
-      "  2.4093   7.9143\n",
-      "  2.4408   7.9231\n",
-      "  2.4724   7.9179\n",
-      "  2.5039   7.9007\n",
-      "  2.5354   7.8740\n",
-      "  2.5669   7.8405\n",
-      "  2.5984   7.8025\n",
-      "  2.6300   7.7623\n",
-      "  2.6615   7.7225\n",
-      "  2.6930   7.6841\n",
-      "  2.7245   7.6493\n",
-      "  2.7560   7.6192\n",
-      "  2.7876   7.5948\n",
-      "  2.8191   7.5769\n",
-      "  2.8506   7.5659\n",
-      "  2.8821   7.5622\n",
-      "--------------------\n",
-      "  2.8821   7.5622\n",
-      "  2.8933   7.5631\n",
-      "  2.9044   7.5660\n",
-      "  2.9156   7.5708\n",
-      "  2.9267   7.5775\n",
-      "  2.9379   7.5862\n",
-      "  2.9490   7.5966\n",
-      "  2.9601   7.6090\n",
-      "  2.9713   7.6232\n",
-      "  2.9824   7.6392\n",
-      "  2.9936   7.6570\n",
-      "  3.0047   7.6765\n",
-      "  3.0159   7.6978\n",
-      "  3.0270   7.7208\n",
-      "  3.0382   7.7454\n",
-      "  3.0493   7.7716\n",
-      "  3.0604   7.7994\n",
-      "  3.0716   7.8288\n",
-      "  3.0827   7.8596\n",
-      "  3.0939   7.8918\n",
-      "  3.1050   7.9254\n",
-      "  3.1162   7.9604\n",
-      "  3.1273   7.9966\n",
-      "  3.1385   8.0340\n",
-      "  3.1496   8.0727\n",
-      "  3.1607   8.1124\n",
-      "  3.1719   8.1533\n",
-      "  3.1830   8.1951\n",
-      "  3.1942   8.2379\n",
-      "  3.2053   8.2817\n",
-      "  3.2165   8.3263\n",
-      "  3.2276   8.3718\n",
-      "  3.2388   8.4180\n",
-      "  3.2499   8.4649\n",
-      "  3.2610   8.5125\n",
-      "  3.2722   8.5608\n",
-      "  3.2833   8.6096\n",
-      "  3.2945   8.6590\n",
-      "  3.3056   8.7088\n",
-      "  3.3168   8.7591\n",
-      "  3.3279   8.8099\n",
-      "  3.3391   8.8609\n",
-      "  3.3502   8.9124\n",
-      "  3.3613   8.9641\n",
-      "  3.3725   9.0160\n",
-      "  3.3836   9.0682\n",
-      "  3.3948   9.1205\n",
-      "  3.4059   9.1730\n",
-      "  3.4171   9.2255\n",
-      "  3.4282   9.2780\n",
-      "--------------------\n",
-      "  3.4282   9.2780\n",
-      "  3.4616   9.4353\n",
-      "  3.4951   9.5903\n",
-      "  3.5285   9.7395\n",
-      "  3.5619   9.8760\n",
-      "  3.5954   9.9843\n",
-      "  3.6288  10.0379\n",
-      "  3.6622  10.0174\n",
-      "  3.6957   9.9370\n",
-      "  3.7291   9.8218\n",
-      "  3.7625   9.6868\n",
-      "  3.7960   9.5394\n",
-      "  3.8294   9.3836\n",
-      "  3.8628   9.2214\n",
-      "  3.8963   9.0544\n",
-      "  3.9297   8.8833\n",
-      "  3.9631   8.7089\n",
-      "  3.9966   8.5317\n",
-      "  4.0300   8.3521\n",
-      "  4.0634   8.1703\n",
-      "  4.0969   7.9866\n",
-      "  4.1303   7.8011\n",
-      "  4.1637   7.6139\n",
-      "  4.1972   7.4253\n",
-      "  4.2306   7.2352\n",
-      "  4.2640   7.0438\n",
-      "  4.2975   6.8511\n",
-      "  4.3309   6.6573\n",
-      "  4.3643   6.4624\n",
-      "  4.3978   6.2667\n",
-      "  4.4312   6.0704\n",
-      "  4.4646   5.8738\n",
-      "  4.4981   5.6773\n",
-      "  4.5315   5.4813\n",
-      "  4.5649   5.2862\n",
-      "  4.5984   5.0929\n",
-      "  4.6318   4.9021\n",
-      "  4.6652   4.7147\n",
-      "  4.6987   4.5319\n",
-      "  4.7321   4.3549\n",
-      "  4.7655   4.1852\n",
-      "  4.7990   4.0246\n",
-      "  4.8324   3.8750\n",
-      "  4.8658   3.7385\n",
-      "  4.8993   3.6174\n",
-      "  4.9327   3.5139\n",
-      "  4.9661   3.4305\n",
-      "  4.9996   3.3692\n",
-      "  5.0330   3.3317\n",
-      "  5.0664   3.3191\n"
-     ]
-    }
-   ],
-   "source": [
-    "ibands = 9  # band number from 0 --> number of bands\n",
-    "spin = str(Spin.up)\n",
-    "\n",
-    "for xpath, epath in zip(data[\"distances\"], data[\"energy\"]):\n",
-    "    print(20 * \"-\")\n",
-    "    for x, bands in zip(xpath, epath[spin][ibands]):\n",
-    "        print(f\"{x:8.4f} {bands:8.4f}\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Same as above but in a plot."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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0Fdmqz8PC+8HTBm5+KjhjuBPhxp/5ir1XLqz9Lfy/vvDev0Lx4YZH9Vbz+82/56EPHqKDpwNzJsyhTbM2wckcYZIGZ+Nq05qSPJ128YcWuopsq5+CM/tg6rOQEOR9T5p3hlv+4rtx2v0m2PA/8LurYc5k2PhnOLMfLnJow/ma8yzcu5Cpi6fy58//zJSuU5g7cS5ZyVnBzRtBxOEgddJkKtato1a3CGkyCeWpIdnZ2SY/X589UgFStA+eHQr9ZsC0P4R+/OLDsOVV2PoanDvo+1pcCrToykcJcSyS8xSmtWVX8T6q66rp2bwnPxz0Q4a3GR76rBGgav9+DuTkkvXTx2h+112244QVEdlkjMm+4uu00FVEMgZemQFHPoF/yIcUy1e7Z/bDwdW+VTZn9pFXfYoXpZz0NtfQK6MvN3a4kWtaXhOzK1ka6uAtt4IxdF7wlu0oYaWhhW538wqlmmr/B7DvfRj/pP0yB8i4yvej3uT6H6pxUqdM5tSTP6dq3z7iu3a1HSfi6By6ijzGwAf/DmkdYHCAV7Uoqzw33wxOJyV5S2xHiUha6CryFOTBia0w6mdWNtJSweNq0YLkEcMpWbJEtwJoAi10FVnqvPDhf0GLHnD1TNtpVBCkTp5C7YkTnNf7bY2mha4iS0EeFO2GUY9BlB8AEatSxozGkZRE6RKddmksLXQVOYyBNb+FjK7Qe4rtNCpIHImJpIwbR+nyd6mr0g1cG0MLXUWO/R/CyW0w4gd6dR7lPJMnUVdWRvlHq2xHiSha6CpyrP1/kNLGt2eLimrJQ4fizGxByRLdCqAxtNBVZDi+Bb5YA8MeBFe87TQqyMTpJDUnl/JVq/EWN30jtFijha4iwyd/AncyDLzTdhIVIp5JuVBTQ+nyd21HiRha6Cr8lRfC9jd9Z4AmptlOo0IkoXdv4rp0oWSprnZpKC10Ff42/RW81XDtA7aTqBASEVInT+JC/iZqjh2zHSciNLnQRaSHiGz5yo9SEXk4kOGUwlsDnz7vO4WoRTfbaVSIeXJzAShZ+rblJJGhyYVujNltjBlgjBkADALOAwsDlkwp8B0rV34SBt9nO4myIK5dOxIHDqR06RJCuTNspArUlMsYYL8x5lCA3k8pn/y/gqctdB1nO4myJHXyJKr27qNq927bUcJeoAr9NmBegN5LKZ+zB33b5F7zbXDqTs+xKmXCBHC5KF261HaUsOd3oYtIHL6tn9+4xK/fLyL5IpJfqEdLqcbYPAfEoUsVY5wrPZ1mI0ZQ8vYy3YHxCgJx2TMR2GyMOXWxXzTGPAc8B74Ti/wdzBiDt85QVVtHdW0dVbV1VNV6qfHWUVtnqKsDp0NIcDtoFu8iPSkOh0NPiYk43lrf8W7dxkNqW9tplGWeSZMof/RRzufnkzxkiO04YSsQhX47QZ5u+be8Hbz6yWEMhhpv4/6f4HQIrVMT6NqyGQPapzG0SwbZHdNxOXXFZljbtwLKT8E1enWuIGX0jUhSEqVL39ZCvwy/Cl1EkoFxQFAXCA+7KoMEtxMRcDsEl9NBvMtBnMtBvMtJvMuB2+XA7RBEwFsHlTVeyiprKCyv4sjZC+w5VcbTe/byuxV7aZ4cx9QBbblreEc6ZiQHM7pqqs9eguRM6HaT7SQqDDiSkkgZM4bSd98l61/+GUecHmxyMX4VujGmAsgIUJZLGt+nFeP7tPL7fUora1i3t4iln5/gpY+/4MX1B7l1UDseuakHWZ6EACRVAVFR5FuueO13wem2nUaFidRJuZQuWULF2rWkjB5tO05Yiql5B0+Cm4n9WvPMt65h3U9Gc/eIziz87BhjfrOK1/OP6DrXcLFtPtTVwsA7bCdRYSR52DCc6em62uUyYqrQv6qlJ4F/ze3Nih/dQO82Hn785jb+8bUtXKj22o6mtsyDNtdAy162k6gwIm43nokTKPtwJd7yCttxwlLMFvqXOmYk89p3hvJP43uwdNtxZv5pA0XlekqKNad2wKnPof/ttpOoMOTJzcVUVlL+wQrbUcJSzBc6gMMhPHRjV/58ZzZ7T5cx608bOFVaaTtWbNr6Gjhc0PcW20lUGEocMAB3mza6t8slaKF/xdjeWcy5ewgnSyq5/c8fc7ai2nak2FLnhc/f8D3mnxz0e+0qAonDgSc3l4r166k9c8Z2nLCjhf4113bJ4IX/M5ij5y5w75xPdU49lA6uhrIT0F+PmFOX5snJAa+X0uXLbUcJO1roF3Ftlwx+f9sAthwp5sdvbdPVL6Gy7XWI90D3ibaTqDCW0KM78d26UarTLt+ghX4JE/q25tGberBk63FeWPeF7TjRr+YCFCyBXpPBrc8EqMvz5OZy4bPPqD6qB198lRb6ZTw46irG98niyWUFfHb4nO040W3ve1BdBv1utZ1ERQBPzs0AlC5bZjlJeNFCvwwR4akZ/WnlSeCH87dQUVVrO1L0+vwNSG4Jna+3nURFgLh27UgcMEAfMvoaLfQr8CS4+c3M/hw6e57/WlZgO050qiyBPe9B3+ngcNpOoyKEJzeXqj17qNyzx3aUsKGF3gBDu2Rw38jOvPrJYT4+oEulAq5gKXiroN8M20lUBPFMGA8OB6Vv67TLl7TQG+hH43rQoXkSP1vwOZU1upQxoHYsgLQO0HaQ7SQqgrhatCB56FBKly3TlWj1tNAbKDHOyZPT+nGgqII/rtpvO070qDgD+1dCn+kgehCJahxPbi41R45QuW2b7ShhQQu9EUZ2a0HO1a35w0f7OXruvO040aEgD4zXN3+uVCOljBuLxMVR8rauSQct9Eb72c29EIEn9QZpYOxYAM2vglZX206iIpAzJYVmN1xP6bJ3MF6dCtVCb6S2aYl874auLPv8JPlfnLUdJ7KVn4Yv1vo24tLpFtVEnpwcvEVFnN+40XYU67TQm+A713emZUo8P39nl96M8cfOxWDqoM8020lUBGs2ahSOpCSddkELvUmS4lz8cFx3Nh06x7s7TtmOE7l2LIIWPSCrt+0kKoI5EhJIGTeWsvfep646tndI1UJvohmD2nFVZjK/eW833jq9Sm+0slNwaB30mWo7iYoCnpwc6kpLqVi71nYUq/wqdBFJE5E3RWSXiBSIyLBABQt3LqeDh8d2Z+/pcpZuO247TuQpyAMM9NZCV/5LHjYMZ1pazO/A6O8V+tPAcmNMT6A/EFNLP3L6taZHVgpPr9hLrbfOdpzIsnMxtOiu54aqgBC3m5QJ4ylbuZK6itg9b7TJhS4iqcD1wPMAxphqY0xxoIJFAodD+OG4bhwoqmDpthO240SO8tO+6ZbeU3V1iwqY1JwczIULlK38yHYUa/y5Qu8MFAJ/FZHPROQvIpIcoFwR46bereiRlcIzK/dRp3PpDVOwxLe6pfcU20lUFEkcNAhXq1aUxvBqF38K3QVcA/zBGDMQqAAe+/qLROR+EckXkfzCwkI/hgtPDofw4I1Xsfd0Oe/t1BUvDVKQBxldIauP7SQqiojDgWfiRMrXrsVbHFOTBX/jT6EfBY4aYz6p//xNfAX/d4wxzxljso0x2ZmZmX4MF75yr25Dp4wknlm5T9elX0nFGTi4xncykU63qADz5ORATQ1lK1bYjmJFkwvdGHMSOCIiPeq/NAbYGZBUEcbpEL57w1V8fqyEDft1e93L2v22b+8WnW5RQZDQpzdxHTvG7ENG/q5y+T7wiohsAwYAT/ofKTJNHdiWFs3i+dPqA7ajhLediyGtI7TubzuJikIigicnh/OfbKTm9GnbcULOr0I3xmypn0652hgz1RgTswdvJrid3D2iE6v2FFJwotR2nPB0oRgOrILeOt2igseTczPU1VG2/F3bUUJOnxQNoDuu7UhSnJM/r9Gr9Iva/Q7U1UAvnW5RwRN/1VXE9+wZk6tdtNADKDXJzYxB7Vi69QSnyyptxwk/BXmQ0kZPJlJB58m5mQtbt1J95IjtKCGlhR5gd4/oTE1dHS9vOGQ7SnipKod9H0CvSeDQP3YquFJvvhkg5s4b1b9ZAdapRTJjembx8ieH9ezRr9r7nu8g6N6TbSdRMcDdti2JAwfG3LSLFnoQ3DOyE2crqsnbqpt2/U1BHiRnQoeY2b9NWebJyaFq714q9+yxHSVktNCDYFiXDHpkpTBn/Rf6oBFAzQXY8x70zAGH03YaFSM8E8aDwxFT0y5a6EEgInx7eEd2HC9l06GYXcn5v/avhJoK3/y5UiHiatGC5KFDKV22LGYurLTQg2TawLZ4Ely8uP4L21HsK8iDhFTodL3tJCrGeHJyqDlyhMpt22xHCQkt9CBJinMxI7s9y7efjO0ljN4a2L0MetwMrjjbaVSMSRk3FnG7Y2YrAC30IJp9bQdq6wzzN8bWWti/c3A1VJb4NuNSKsScHg/JN1xP6TvvYLzRv+pMCz2IumQ247puLXh14+HYPdGoYAm4k+GqG20nUTEqNTcXb2ER5zdutB0l6LTQg2z2tR05UVLJioLY2yiIOi/sehu63wTuRNtpVIxqNmoUjqSkmJh20UIPsrG9WtLKk8CrGw/bjhJ6hz+GitM63aKsciQkkDJuLGXvvkdddbXtOEGlhR5kLqeDWYPbs3pPIYfPnLcdJ7QK8sAZD93G2U6iYpwnJ4e6sjIq1qyxHSWotNBD4LYh7XEIzPs0hq7S6+p88+ddx0B8iu00KsYlDxuGMz2dkqVLbUcJKi30EGidmsjonlm8kX+E6toYuTl6fDOUHtPpFhUWxO0mZcJ4yld+hLe8wnacoNFCD5HZ13agqLyaFQUxcpB0QR44XNBjgu0kSgG+1S6mspLyD6L3vFEt9BC5vnsmbVITmBcLN0eNgZ150PkGSEy3nUYpABIHDsTdpg0lS6N3tYsWeog4HcKswR1Ys7co+m+Onvwczh3Ug6BVWBGHA09ODhXr11N7JjoPc9dCD6GZg9vFxs3RgjwQh293RaXCiGdSLni9lL6z3HaUoNBCDyHfzdGWvLnpKDXR+uSoMbBjEXQaCcktbKdR6u8kdO9OfPfulEbpahe/Cl1EvhCRz0Vki4jkBypUNLttcAcKy6r4cFeUPjlauAvO7NXpFhW2PJNyubBlS1SeNxqIK/QbjTEDjDHZAXivqDeqRyZZnnhei9abozvzAIGeuve5Ck+pOb6pwGi8StcplxBzOR3MGNSeVXsKOV58wXacwNu5yHfMXEqW7SRKXZS7TRuSsrMpyVsSdQdf+FvoBlghIptE5P6LvUBE7heRfBHJLyws9HO46DBrcHsM8Hp+lP2Tr3APnN4JfabaTqLUZXkmT6L64EEqt++wHSWg/C30kcaYAcBE4CER+caRNMaY54wx2caY7MzMTD+Hiw7tmycxsmsL3sg/ircuiq4Qdi7yfdSnQ1WY84wfj7jdlC5dYjtKQPlV6MaYY/UfTwMLgSGBCBULZg1uz7HiC6zbV2Q7SuDsWATth4Knte0kSl2WMzWVZqNuoOTtZZjaWttxAqbJhS4iySKS8uXPgZuA7YEKFu3G9c4iPcnNa9GyJr1oL5zeodMtKmJ4Jk3CW1RExYaPbUcJGH+u0LOAtSKyFdgIvG2Mic7V+kEQ73Iy/Zp2vL/zFEXlVbbj+G+HTreoyNJs1CgcHg8leXm2owRMkwvdGHPAGNO//kcfY8x/BTJYLJg1uD01XsPCzcdsR/HfjoW+6ZbUtraTKNUgjrg4PBMnUrZiRdTswKjLFi3qnpXCNR3SmPfp4chePlW42zfd0ne67SRKNUrqlMmYCxcoe/9921ECQgvdstuGdOBAYQX5h87ZjtJ02xcAok+HqoiTOHAg7vbtKclbbDtKQGihW5Z7dWuaxbsid1tdY2DHAt/eLSmtbKdRqlFEhNTJkzn/8SfUnDxpO47ftNAtS4pzMXlAG5Z9foKSCzW24zTeqR1QtAf6TLOdRKkmSZ0yGYyhJC/y16RroYeB2wd3oLKmjsVbIvDm6I4Fvq1ydXWLilBxHTqQmD2IkoULI/teFlroYaFvWw+9W3uYt/FIZP2BMgY+fwO63AjN9ClgFbnSpk71bQWwbZvtKH6kvsDjAAALyUlEQVTRQg8DIsLtQ9pTcKKUbUdLbMdpuKOfQvFh6DfDdhKl/JIyYQKSkEDxwoW2o/hFCz1MTBnYlkS3M7KeHP38DXAl6MlEKuI5mzUj5aZxlL69jLqqyH3QTws9THgS3Ezq35rFW45TVhkBN0e9tb7lit0nQILHdhql/JY2bRp1ZWWUrVhhO0qTaaGHkduHdOB8tZe8rcdtR7mygx/B+SKdblFRI+naa3G3bUvJW2/ZjtJkWuhhZED7NHq19vDqJxHw5OjW+ZCQCt3G2U6iVECIw0Hq9GlUrN9A9dEIXHGGFnpYERG+dW0HdhwvZWs43xytKoNdS6HPdHDF206jVMCkTZsGIpRE6M1RLfQwM3VAG5LinLzy8SHbUS6tYAnUnIf+t9tOolRAudu0IXn4cIoXLsB4vbbjNJoWephJSXAzZUBblmw7Tsn5ML05unUepHeG9nqeiYo+abfeQu3xE1Ss32A7SqNpoYeh2df6nhx9c/NR21G+qeQoHFwD/W8DEdtplAq4ZmPG4ExPp/j1+bajNJoWehjq2zaVgR3SeOXjQ9SF25mjW+YBBq6eZTuJUkHhiIsjdfo0yj5cSc2p07bjNIoWepi6a1gnDhRVsDaczhytq4PPXoJO10HzzrbTKBU06TNngtdLyYLIWsKohR6mJvZrRUZyHHM3hNHN0UNrofgQXPNt20mUCqq4jh1JGjaUc2+8EVE3R7XQw1S8y8ntQzrwwa5THDl73nYcn80vQXwq9JpkO4lSQZc+6zZqj5+gfPVq21EaTAs9jM0e2gGHCHM3fGE7ClwohoI8uHoGuBNtp1Eq6FLGjMaVlcW5l1+xHaXB/C50EXGKyGcisjQQgdT/ap2ayMS+rXjt0yNUVNXaDbP1Nait1OkWFTPE7Sb9tllUrFtH1YGDtuM0SCCu0H8AFATgfdRF3DOyM2WVtbxlcwmjMfDpX6DdYGjd314OpUIsbeZMxO3m3Kuv2o7SIH4Vuoi0A3KAvwQmjvq6azqkM6B9Gi+sPYjX1hLGg6vhzF4YfJ+d8ZWyxJWRQcrECZQsXIi3vNx2nCvy9wr9d8CPgboAZFGXcN91nfnizHne33nKToBP/wKJzaH3VDvjK2VR8zvvpK6iguI337Qd5YqaXOgikgucNsZsusLr7heRfBHJLywsbOpwMW1Cn1Z0aJ7En1bvD/0ujCVHYdfbMHA2uBNCO7ZSYSCxXz+SsrM5O2cupiZMt+Oo588V+ghgsoh8AbwGjBaRl7/+ImPMc8aYbGNMdmamnjvZFC6ng/uu68xnh4vJP3QutIN/8kffxyH3h3ZcpcJI83vvofbECUqXL7cd5bKaXOjGmJ8aY9oZYzoBtwEfGmPuCFgy9XdmDGpP8+Q4nlm5L3SDVpbCpjnQewqkdQjduEqFmWY33EDcVVdx5vkXwvqsAl2HHiES45zcO7IzH+0uZNvR4tAM+tlLUFUKw/8hNOMpFabE4SDjnrup2rWLirVrbce5pIAUujHmI2NMbiDeS13at4d1JDXRzX9/GIKrdG8NfPxH6DAc2g4K/nhKhbnUSZNwtWlN0f88E7ZX6XqFHkFSEtzcPaIT7+88xfZjQT7RaOs8KDkMIx8O7jhKRQiJi6PFA9/lwtatVKxdZzvORWmhR5h7RnYmLcnNU+/uDt4g3hpY/RS0uQa63RS8cZSKMGnTptZfpf9PWF6la6FHGE+CmwdHXcWqPYV8fOBMcAbZOg+KD8Oon+ohFkp9xVev0stXfmQ7zjdooUegbw/rRCtPAj9/Z1fgD8CoqYRVX16djwvseysVBdKmTyOuc2dOP/VU2K1L10KPQAluJ4+O78HWI8Us/OxYYN/842d8c+fjntCrc6UuQtxuWv74n6g+eJBz81+3HefvaKFHqOkD2zKgfRq/WL6LssoAXSWUnYQ1v4WeudD5+sC8p1JRqNmoUSQNG0rRf/833uIQLSNuAC30COVwCE9M7kNReRW/DtQN0hVPQG0VjPv3wLyfUlFKRMh67DG85eWc+sUvbcf5Gy30CNa/fRp3DevEnA2H/L9Buuc92PoqDP8+ZFwVmIBKRbGEHj3I+M59lCxaFDanGmmhR7gfT+hBx4wk/unNrZQ2derl/FnI+z607A2jHgtsQKWiWIsHHyS+W1dO/OvjeEtLbcfRQo90SXEufjOjP8eLK3nk9a2NX/VSVwdL/hHOF8HUP4ArPjhBlYpCjrg4Wj/5JLVnz3LskUetHyithR4Fsjs1559v7sX7O0/x9Ad7G/ebP/wPKFgCY5+ANgOCE1CpKJbYrx+t/uVfqFizhtO/+a3VLC6ro6uAuXtEJ3aeKOXpD/aSFOfkgRsaMA/+yZ9g7W9h0P+BYQ8FPaNS0Sp91kyqdu/m7Asv4PR4yHjgfsTCsl8t9CghIvxiej8qa7z8/J1dnCqt4rGJPYlzXeQfYXVeeP9x2PA/0ONmuPnXuuZcKT9l/fQxvGVlFP7ud9SePk3WYz9B4uJCmkELPYq4nA5+N2sALZrF88K6g2w4cIbvj+7KuN5ZuJ0O31Og+z+AlU/Cqe0w5AGY8HNwOG1HVyriidtNm1/+AlfLTM4+/wLl69bS8uGHaXb99TiSk0OTIZQbzGRnZ5v8/PyQjRfLlm8/yc/fKeDQmfMMdO7n6bg/0p4TiKmD5l1g9L9C3+m2YyoVlcpXreL0r39N1d59IIK7Q3ta//t/kHztkCa9n4hsMsZkX+l1eoUepSb0bcW43lms3HWa/XsTObunE8k9byWj6xDoPh6cbtsRlYpazW64geQRI6hYt44LO3ZQtWs3rhYZQR9Xr9CVUirMNfQKXZctKqVUlNBCV0qpKKGFrpRSUUILXSmlokSTC11EEkRko4hsFZEdIvJEIIMppZRqHH+WLVYBo40x5SLiBtaKyDvGmI8DlE0ppVQjNLnQjW+9Y3n9p+76H+F3DLZSSsUIv+bQRcQpIluA08D7xphPLvKa+0UkX0TyCwsL/RlOKaXUZQTkwSIRSQMWAt83xmy/zOsKgUNNHKYFUNTE3xuJ9PuNbvr9Rr9Afs8djTGZV3pRQB79N8YUi8hKYAJwyUJvSKBLEZH8hjwpFS30+41u+v1GPxvfsz+rXDLrr8wRkURgHLArUMGUUko1jj9X6K2BOSLixPc/hteNMUsDE0sppVRj+bPKZRswMIBZruS5EI4VDvT7jW76/Ua/kH/PId1tUSmlVPDoo/9KKRUlIqLQRWSCiOwWkX0i8pjtPMEkIi+IyGkRueRqoWgiIu1FZKWI7KzfQuIHtjMFU6xumVH/zMpnIhL199lE5AsR+VxEtohISA+ACPspl/qbrnvwraI5CnwK3G6M2Wk1WJCIyPX4nsCda4zpaztPsIlIa6C1MWaziKQAm4CpUfzfV4Dkr26ZAfwg2rfMEJEfAdmAxxiTaztPMInIF0C2MSbk6+4j4Qp9CLDPGHPAGFMNvAZMsZwpaIwxq4GztnOEijHmhDFmc/3Py4ACoK3dVMFjfGJqywwRaQfkAH+xnSXaRUKhtwWOfOXzo0TxX/hYJiKd8K2c+sYWEtGkIVtmRJnfAT8G6mwHCREDrBCRTSJyfygHjoRCVzFARJoBbwEPG2NKbecJJmOM1xgzAGgHDBGRqJ1aE5Fc4LQxZpPtLCE0sv6/70Tgofpp1JCIhEI/BrT/yuft6r+mokT9XPJbwCvGmAW284SKMaYY+HLLjGg1AphcP6/8GjBaRF62Gym4jDHH6j+exrfH1ZBQjR0Jhf4p0E1EOotIHHAbkGc5kwqQ+puEzwMFxpjf2s4TbLG2ZYYx5qfGmHbGmE74/u5+aIy5w3KsoBGR5Pqb+4hIMnATl9nfKtDCvtCNMbXAPwDv4rth9roxZofdVMEjIvOADUAPETkqIvfazhRkI4A78V25ban/cbPtUEHUGlgpItvwXay8r1tmRJUsfIf9bAU2Am8bY5aHavCwX7aolFKqYcL+Cl0ppVTDaKErpVSU0EJXSqkooYWulFJRQgtdKaWihBa6UkpFCS10pZSKElroSikVJf4/T+Lm6NaybI4AAAAASUVORK5CYII=",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x10f2eb550>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ibands = 9  # band number from 0 --> number of bands\n",
-    "spin = str(Spin.up)\n",
-    "\n",
-    "for xpath, epath in zip(data[\"distances\"], data[\"energy\"]):\n",
-    "    plt.plot(xpath, epath[spin][ibands])"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "The same again but merging the slices of the band."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x10f259160>]"
-      ]
-     },
-     "execution_count": null,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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RIQFGh3NTW3Li0Bo+9tFdqcZnAC12gyEgkF3CnOWVs3VkJ4SxPNVz5v5PJAnAg+wvrqdv2Mpj691/peHylEjCg/x9NgGUNfQQFRJAYoR7zApZkTo6PVfqAI5T3dpHYU0HD65O9YjGb5ORBOAhtNY8d6qGvKRwVqe7f5tZfz8Tm7JifXZXqrKGbvKSwt3mjcHPpNiSHcdHV1t88vfhDK8WmVEK7lvlWXP/J5IE4CEu1HVRWt/tMW1mAbZkx2HuHKC6zbfaENhsmstuMgNoom25cTR1D3GlqdfoUDye1prXi8xszopjfmSw0eHMmSQAD/H8qeuEBPoZ2vN/trbkjO5K5Wvjztfb+xkYsbLYDWYATfTJLmEyDGS383VdXG/v596Vnnv3D5IAPELXwAj7z9ezZ2Uy4UHuXfydKCM2hJSoYI75WB+aT1pAuNkTwPzIYHISwqQvkAPsL64n0N/E3flJRodiF0kAHmBfsZmBESuPrXOPrp8zpdTouPPxSt9qQ1DW0INJQW6iez0BAGzNiefUtXYGR6xGh+KxrDbNGxfq2b4onggPuiGbjCQAD/DC6dE2s8s8cKrZlpw4egYtPtUWoryxm4y4ULfYo+FG23LjGLbYOHWt3ehQPNapqjZaeoa4d4XnDMdORRKAmysxd3GpoZtH1rr3wq+pbM4ebUfsS+2hyxp63Gb+/43WL4wl0N8kdQA77CuuJzTQj9sWe17rhxtJAnBzewtrCfQ3scdD7zZiQgNZmhzBUR8pBPcOWbje3s8iAzeBuZngQD/WL4yRBDBHQxYrb5c0cNfSJIIC3O8Jb7YkAbixwRErrxeZ2Zmf5PYrf29mS04cRdc76BuyGB2K010eXwHsJi0gJrMtJ56rzb3Udw4YHYrH+fByC92DFo+f/TNOEoAbO1jaSPegxe37/kxna3Y8I1bNaR8Yd77UMN4DyD2fAOD/Twc9KrOBZm3/+XpiQgM/Gdr0dJIA3NjewlrSYoLZmBlrdCh2KciIZp6/iaM+UAcoa+gmIsiflCj3XRyUmxhGUkQQH13x/t+HI/UNWThU1sSuZUkE+HnHW6d3vAovVNvez8cVbXx2TRomN237PFNBAX6szYjheKX3v+GUNXSTNz/CrVdrK6XYmhPHsYpWrD6+a9tsvHepicERG3tWemY9bjJ2JQCl1ItKqeKxj2qlVPEUx92tlLqslKpQSn3bnmv6ipcKa1EKj9tkeiobs2Ipb+yhrXfI6FCcZrwFxBI3Hv8fty03nq6BEc7XyS5hM7X/fD3JkUGsSY82OhSHsSsBaK0f0Vqv1FqvBF4BXr3xGKWUH/ATYCewBPicUmqJPdf1dlab5qWzdWzNiSfZjYcSZmPD2DCWN88/r2nvp3/Y/VpATGZLdhxKjRY1xfQ6+ob56EoL96xM9vgn8okcMgSkRp93Hwb+OMkfrwMqtNZVWuth4AVgjyOu662OVbTS0DXIIx5e/J1oeWokIYF+nKhsMzoUpylrcP8ZQOOiZde2WTlQ0oDFprl3hXfM/hnnqBrAVqBJa311kj9LAWonfF039j0xhb1naokOCeD2JZ6/0GRcgJ+JtRkxnKjy7gTgri0gJnPb4kQu1HXR3D1odChub39xPVnxoR4xvDcb0yYApdQhpVTJJB8T7+I/x+R3/7OmlHpKKVWolCpsafG9x9P2vmHevdTIfatSmOfv+QtNJtqUFUtFcy/NPd75hlPW0E1mfJjHLBAa38T8iAwD3VRD1wCnq9vZszLFrYv7czFtAtBa3661zp/kYx+AUsofeAB4cYpTmIGJYxmpY9+b6nq/0FoXaK0L4uPjZ/5KvMTrRWZGrNpjWz/czMas0TrAySrvrAOUNfR4xPDPuLykcOZHBvF+eZPRobi1N883oDVeN/wDjhkCuh0o11rXTfHnZ4AcpdRCpVQg8Ciw3wHX9Tpaa/YW1rIiNdLtWgk7wtLk0W0iT3jhdNCu/hHMnQMeUQAep5RiR14CR6+2MmSR7qBT2XfezPLUSDLiQo0OxeEckQAe5YbhH6VUslLqAIDW2gJ8FTgIlAF7tdalDriu17lQ10V5Yw8Pe+HdP4xuS7h+YYxXFoLLPKAFxGRuW5xA/7DVJ1Zpz0VFcy8l5m6vmvs/kb+9J9BaPzHJ9+qBXRO+PgAcsPda3u7FwlqCAkzc44WPmuM2ZMZyqKyZhq4Bj95K70bjM4A8rUi4MTOOef4m3i9rZmuO7w25TmdfsRmTgnuWzzc6FKeQlcBuYmDYyhvF9ezKn+/xm0zczHgdwNueAsoauokJDSQhfJ7RocxKcKAfm7Pj+KC8WTaLv4HWmn3F9WzKiiMhIsjocJxCEoCbeLukgZ4hC5/1orn/k1mcFEFUSIAXJoAeFs8P98hZItvzErje3k9lS5/RobiVotpOrrf3s8dLOn9ORhKAm3jxTC0LYkPYkBljdChOZRqvA3jRegCL1cblJvfdBGY649NBP5DZQJ+yr8jsFfv+3owkADdQ3drHqWvtPFyQ5pF3kLO1KSuOuo4Batv7jQ7FIa619jFssXlcAXhcSlQweUnhvF8mq4LHWaw23rzQwO2LEwj34iFZSQBu4KWztZgUPLjaOxq/Tcfb6gCXPKgFxFR25CVQWNNB18CI0aG4hWMVrbT1DXvt7J9xkgAMZrHaePlsHbcuSiAp0jsLTTfKSQgjLizQa4aByhp6CPBTZCeEGR3KnN22OAGrTfOhbBUJjO77GxHkz62LvHtmlCQAg310tYWm7iEeLvCNu38YXYC0PjOWE5VtXjHzpLyxm6z4MAL9Pfef08q0aGJCA3m/TOoAA8NWDpY2smvZfK9rx3Ijz/0b6yX2nqkjNjSQHXmJRofiUhszY2nsHqS6zfPrAKX13R43//9GfqbRVcEflDczYrUZHY6h3itron/Y6vXDPyAJwFCtvUMcKmvigdUpHn33OBfeUgdo6h6kpWeI/JRIo0Ox251LEukZtHDKS3s1zdS+IjNJEUGsX+jdM/JAEoChXjtnxmLTHr/p+1xkxoWSED7P4+sAF+u6AFiW6vkJYGtOPEEBJt671Gh0KIbp6Bvmwyst3OtlG79MRRKAQbTWvFhYy6r0KHI8pH+8Iyml2Jjl+XWAi+YuTMrzWkBMJjjQjy3Z8bx3qcmjfyf2eOvi6MYv3rz4ayJJAAYpqu2kornXq3b9mq1NWbG09g5R2dJrdChzVmLuIis+jNB5drfVcgt3Lk2kvmuQ0vpuo0MxxL5iM9kJYV6R0GdCEoBB9p6pJTjAj91e3PhtOhsz4wA47sF1gIvmLpZ5wfj/uNvyEjApePeS780Gquvo50x1B/etTPaJBZkgCcAQfUMW3jhfz2eWzyfMS+4c5yItJpiUqGCPLQQ3dw/S7CUF4HGxYfMoWBDDu6W+VwfYf74ewCdm/4yTBGCAAxcb6Bu2euWuX7OhlGJDZiwnq9qw2TxvzPmi2XsKwBPdsSSR8sYer2nVMRNaa147Z2Z1ehRpMSFGh+MykgAMsLewlsy4UAoWRBsdiuE2ZsXS0T/C5aYeo0OZtQt1XSgvKQBPdMeS0TUp7/nQMND5ui6uNvfy0BrfuimTBOBilS29nKnu4LM+0vhtOp68HsDbCsDjMuJCyU0M410fmg760thmTLtXeOfGL1ORBOBiewtr8TMpHlzjO+OMN5MSFUx6TIhHrgfwtgLwRHcsSeRMdQed/cNGh+J0gyNW9p+v5+6lSV69GdNkJAG40JDFysuFdezISyAh3Dcav83ExsxYTlW1YfWgOsB4Adh7E0ASVpv2iRbRB0sb6Rn0/s2YJiMJwIUOljbR1jfM5zcsMDoUt7IpO5buQcsn++p6Am8tAI9bnhJJbGigR0/RnamXz9aREhXMxsxYo0NxOUkALvTcyRrSY0LYmh1ndChuZfwf3vHKVoMjmbmLZu8sAI8zmRRrFkRTWOPdfYHMnQMcq2jlwTWpPtH64UaSAFykormHU9faeWx9uk/+RbuZhIggMuNDPaoQ7K0F4InWZsRQ09ZPc8+g0aE4zatn69AaPrvGd9qxTyQJwEWeO3WdAD/ls3/RprMxM5Yz1R1YPKQV8YU67y0Aj1uTMTpN+Wx1h8GROIfWmpfP1bEhM8an5v5PJAnABQaGrbxyto6d+fOJDZtndDhuaWNWLL1Dlk/G1t2ZN64Ankx+ciTz/E2c8dIEcKa6g5q2fj7rY3P/J5IE4AJvXqine9DC4+vTjQ7FbW0YqwN4wnTQTwrAXp4AAv1NrEiL4qyX1gFeKqwlbJ4/O5clGR2KYSQBuMBzp66TnRDGOh/YYGKu4sLmkZsY5hF1gPEC8NJk7ywAT7Q2I5qS+m76hy1Gh+JQXf0jvHGhnntWzCck0HvrONORBOBkJeYuims7eXx9uqz8ncbGzFgKqzsYtrh3HeBinfcXgMcVZMRgtWmKazuNDsWhXj5Xx+CIzeenZEsCcLLnT18nKMDEA6uk+DudjVlxDIxYOV/nvm82WmuKajtZlRZldCgusTo9GqWg0IvqADab5g8na1idHsXSZO8expuOJAAn6h2ysK/IzD3Lk4kM8a0l5nOxITMGpdy7L1BNWz/tfcOsSveNRn6RwQEsSgynsMZ7EsDxyjautfbxhY2+ffcPkgCc6rUiM33DVh738cfMmYoKCWRxUoRbJ4Ci2tE3wtULfOMJAGDNgmjO1XR4VKuOm/n9iWpiQgPZtcy3Gr9NRhKAk2it+d3xapalRLLCS9sFOMPGrFjOXu9gcMRqdCiTOlfTSWigHzkJvrOP89qMGHqHLFxu9LyW3Teq7xzgUFkTj6xNY56/n9HhGE4SgJMcvdpKRXMvT27OkOLvLGzMjGXYYqPounvWAYpqO1iRFoWfD63mXjO2b4U3tIX44+nraOCxdTIlGyQBOM1vPr5GXNg8PrNcHjNnY11mDCblnusBBoatlDX0sCrdd4Z/AFKjg0mKCPL4BWHDFht/PF3LjkUJPrvy90aSAJygqqWXw5db+PyGdHnMnKWIoADyUyI56YZ1gAt1nVhtmtU+UgAep5SiICOas9We/QRwsLSR1t4hPi/F30/YlQCUUi8qpYrHPqqVUsVTHFetlLo4dlyhPdf0BL89Xk2gn4nH18tftLnYmBlLUW2H2y0+KhqbC7/SR6aATlSwIJr6rkHMnQNGhzJnvz9RTVpMMLfkxBsdituwKwForR/RWq/UWq8EXgFevcnh28eOLbDnmu6ua2CEl8/Wcc+KZOLDpe/PXGzOjmPEqjl1zb3uOAur21kYF+qT/ZwKMkZXsRd66FPAuesdnKnu4IlNC6Ub7wQOGQJSo1XOh4E/OuJ8nuylwlr6h608uTnD6FA81rqFMczzN/Hh5RajQ/mEzaY5U93B2gzfGv4Zt3h+BGHz/DntZkl5pn51tIqIIH8eWeu7jd8m46gawFagSWt9dYo/18AhpdRZpdRTDrqm2xmx2vjNx9Wsy4jx+k6RzhQU4MeGzFg+uuo+CeBKcw9dAyOsW+h7u0YB+JkUazOi3e6pbCZq2vp4p6SRxzcsIMwH2nfMxrQJQCl1SClVMsnHngmHfY6b3/1vGRsm2gk8rZTadpPrPaWUKlRKFba0uM8bwEy8daEBc+cAT23LNDoUj7ctN56qlj7qOvqNDgWAM2NvfOsyfLeh34bMWCqae2npGTI6lFl59tg1/EyKJzdlGB2K25k2AWitb9da50/ysQ9AKeUPPAC8eJNzmMf+2wy8Bqy7ybG/0FoXaK0L4uM9p1ijteanRyrJTQxjR16C0eF4vFtyR7fN/OiKe2wTebq6g8SIeaTFBBsdimHGW3afuuZ+M7Sm0twzyItnarl/VQoJEUFGh+N2HDEEdDtQrrWum+wPlVKhSqnw8c+BO4ESB1zXrRy+3Mzlph7+/JYsKTI5QFZ8GMmRQXx4pdnoUNBac+ZaO+sWxvr0or6lyaN1gJNuuEZjKr/8qIoRq42/uDXb6FDckiMSwKPcMPyjlEpWSh0Y+zIROKaUOg+cBt7SWr/jgOu6lZ8dqSIlKph7ViQbHYpXUEpxy6J4jle0MWLYKopVAAAUYUlEQVTwNpF1HQM0dg+yzkcLwOP8/UyszYjmZJVn1AHaeof4w8nr7FmZQkZcqNHhuCW7E4DW+gmt9c9u+F691nrX2OdVWusVYx9Ltdbfs/ea7uZsTTunq9v58taFBPjJ2jpHuXVRAj1DFs4YPPVwvPDpqwXgiTypDvCrY9cYtFh5ervc/U9F3q0c4KdHqogOCZApZg62JTuOQD8TH5QZOwx0vLKVmNBAchLCDI3DHXhKHaClZ4jfflzN7uXJZMvvbUqSAOxU0dzLobImvrQpw6e3lnOG0Hn+bMiK5YNy4xKA1pqPK1rZlBUrtR3+fx3g4wr3TgA//uAqw1Yb37wj1+hQ3JokADv97ng1gf4mviA9/53i9sUJVLX2UdXSa8j1K1t6aeoeYkt2nCHXdzf+fiY2ZMZwvNI9ZmdN5npbP8+fvs4ja9NYKGP/NyUJwA5dAyO8cq6Oe1ck+2R7AFfYvmh0Sq1RTwHHro6+0W2WBPCJLdlx1LT1U9vuHms0bvRvh67gZ1J8/bYco0Nxe5IA7DDe9uEJWWDiNGkxISxKDOdQWZMh1/+4so30mBBpHzzBlpzRZHiswv2eArr6R3jzQgOPrk0nUeb9T0sSgB0OXGxgRWqktH1wstsWJ3CmuoOOvmGXXtditXGysk3u/m+QFR9GYsQ8t0wAB0oaGLbaeGB1itGheARJAHNks2nKG3t8ZnNwI92dn4TVpl3+FHDB3EXPkIXN2TL9cyKlFFuy4zle0YrNzfYJfq3ITFZ8KMvkpmxGJAHMUU17P/3DVpbMjzA6FK+3LCWSlKhgDpY2uvS6R8qbMSnYnCVPADfakhNLR/8Ilxq6jQ7lE3Ud/Zy+1s79q1J8esX2bEgCmKNL9aN/8RdLAnA6pRR3LU3io6ut9A65bpOY98ubWbMgmujQQJdd01OMJ8WjV91nGGhfcT0Ae1bK8M9MSQKYo7KGbvxMipxEWWTiCjuXJTFssXHYRbOBGrsGKa3vZkdeokuu52kSIoLISwrnyGXjezWN219cT8GCaCnYz4IkgDm61NBNVnwoQQGy568rrE6PJi5sHu+UuGYYaHza6W2LpbPrVHbkJVBY00H34IjRoVDV0svlph4+s3y+0aF4FEkAc1TW0C3j/y7kZ1LszE/i/fImlwwDvV/WRFpMsLR/uInteQlYbZqjbtCy+2Dp6ASBO5cmGRyJZ5EEMAcdfcM0dA2yJFkSgCvdtyqZwREbB538FDAwbOVYRSu35SVKMfEmVqVFERkcwGE3GAY6WNr4yWQBMXOSAOagrEEKwEZYnR5NWkwwrxebnXqdo1dbGLLYZGOfafj7mdiWG8+Ryy2GTgdt7BqkuLaTu5ZKvWa2JAHMQenYDCAZAnItpRR7VqTwcUUrzT2DTrvOGxcaiAkNZGOWzP+fzvZF8bT2DlFS32VYDO9eGn0ivDtfhn9mSxLAHFw0d5EcGST9fwxw36pkbBrePN/glPP3D1s4dKmJnflJsrfDDGzLjUcpeN/Alt0HSxvJjA8lOyHcsBg8lfwNn4OS+i6WykpDQ2QnhJOfEsFLZ+vQ2vHDDh+UNzMwYmX3ctnZbSbiwuaxOj2ady8Z06uppWeIE5Vt7MqX2T9zIQlglnqHLFxr7ZOl5gZ6dG06ZQ3dFNd2Ovzcb5yvJyF8HusWxjj83N5qZ34SZQ3d1LT1ufzab5c0YNNw70pJ2HMhCWCWLtV3ozXkp8j4v1HuW5VCaKAfz5267tDzdg+OcPhyC59ZPh8/2fxlxu4am3rpqjUaE+0vrmdRYji5iTL8MxeSAGapxDxa7JIOoMYJm+fPvStTePNCPV0DjluE9No5M8MWGw+sSnXYOX1BWkwI+SkRvO3iBGDuHKCwpkPu/u0gCWCWSsxdJITPIyFceo0b6fH16QyO2HjlbJ1Dzqe15rlTNaxIjWRZqiT32dqZP5/i2k4augZcds03z4/2/tktq3/nTBLALJXUd8ndvxvIT4lkzYJonj12jRGrze7znanu4EpTL4+vl60952J8CqazF+lNtK+4nhWpkSyIlW0f50oSwCz0D1uoaO6VBOAmvnJLFubOAd68UG/3uZ47VUN4kD+7V8jd5FxkxYeRlxTOvvP2/y5mosTcxaWGbh5YLcN19pAEMAtlDT3YNORLCwi3sCMvgUWJ4fz0SKVdK1EbugZ4+2IjD65OJSTQ34ER+pYHVqdQdL2TqpZep1/r5bN1BPqb2CPj/3aRBDAL4wVgGSN2DyaT4iu3ZnGlqZf37Ngt7CeHK9Bovrx1oQOj8z17VqZgUvB6kXNbdQyOWHmtyMxdS5OICpG9GuwhCWAWSsxdxIYGkiSbTbuN3cvnkxkfyr+8Xc6wZfa1AHPnAC+eqeXhgjRSo6WPvD0SI4LYnB3Hq0Vmp/YGeu9SE10DIzxcIMM/9pIEMAsXzaMFYOkQ6T78/Ux8Z/cSqlr7+N3x6ln//I8/qECheHp7tuOD80EPrE6hrmN0eqaz7C2sJSUqWLbqdABJADM0OGLlanOvLABzQ9sXJbB9UTw/ev/qrJrEFV3v4MUz1/ncujSSpY2wQ9y1NInQQD9ePFPrlPNXNPdw9Gorj65NwySL9ewmCWCGLjf2YLVpaQHhpv7X7iUMW218a+95rDMYfhgcsfJXL50nMSKIb921yAUR+oaQQH/uX53CGxfqaesdcvj5f/1xNfP8TTy2Pt3h5/ZFkgBm6OJYAXhpsiQAd5QVH8bf37uUo1db+ff3r057/L8evExlSx///OByIoICXBCh7/jSxgyGLTZecPBTQEffMK+eq+P+VSnSiddBJAHMUIm5i6iQAFKjZajAXT2yNo2H1qTy7x9c5fmb9An68QdXefbYNb64cQG35Ma7MELfkJMYzpbsOP5wsgaLAxbpjXv+9HUGR2w8uVlmazmKJIAZKq7tZHlqlBSA3ZhSin/Yk8+tufH89WsX+f6BMvom7B/cPTjCP7x5iR++e4X7V6Xwt/csNTBa7/alTRk0dA06rE30wLCV3x6vZmtOHIuSpPGbo8iqlxnoHbJwuannk66Hwn0FB/rxyy8W8Df7S/n5R1U8f+o6t+YlYLXZOF7ZRmf/CJ9bl84/3pcvHT+daEdeAgtiQ/jJ4QruXppkd8H29yeqaekZ4pnHVzsmQAHIE8CMXKjrRGtYlR5ldChiBvz9TPzT/ct45SsbuW1xAudqOrja1Mu6jBje/NoWvv/AMnnzdzI/k+Lrt+VQWt/NO6X29QfqGRzhpx9WcktuPGszZJ8GR7LrCUAptRL4GRAEWIC/0FqfnuS4u4EfAX7Ar7TW/2zPdV2t6ProxiMr0yQBeJI1C2JYs0DeMIyyZ2UKzxyp5P+8d4W7libNOek+e+wanf0j/NWdMlvL0ex9AvgB8F2t9Urgb8a+/hSllB/wE2AnsAT4nFJqiZ3Xdami651kxofKsnMhZsHPpPjmHblUNPfy2hzbQ9S29/PzD6vYmZ8kLVicwN4EoIHxlVGRwGStANcBFVrrKq31MPACsMfO67qM1pri2g5WpUUbHYoQHufupUmsSIvi+wfKZr0uQGvNX792EZOC7+z2qHtGj2FvAvgG8K9KqVrgh8D/mOSYFGDihOC6se9NSin1lFKqUClV2NLSYmd49qvrGKC1d1jG/4WYA5NJ8a8PLadn0MLf7Cud1c++fLaOo1db+fbOPFmp7STTJgCl1CGlVMkkH3uArwB/qbVOA/4SeNbegLTWv9BaF2itC+LjjZ+jfe76aE8TSQBCzE1uYjhfvz2Hty42sK94ZkNBpfVd/N3+UtZmRMsmPU40bRFYa337VH+mlPo98PWxL18CfjXJYWYgbcLXqWPf8whF1zsJDvBjkWw6LcSc/dm2TA6XN/NfX7pAdEgg226yAM/cOcCTvzlDZHAAP35stfT8cSJ7h4DqgVvGPt8BTLYG/wyQo5RaqJQKBB4F9tt5XZcpqu1keWok/n4yY1aIufL3M/Hsl9aSlRDGU/9RyJHLzZMed7Gui8d+eZKBESu/eXIdidJ63ansfVf7U+B/K6XOA/8EPAWglEpWSh0A0FpbgK8CB4EyYK/WenaDgQYZHLFyqb6LVelSABbCXpEhAfzHn6wjPSaEJ35zhq+/UMT52k56BkcoMXfxg3fKeeCnHzM0YuO3T66VFb8uYNc6AK31MWDNJN+vB3ZN+PoAcMCeaxmhtL6bEauW8X8hHCQubB77v7qFZ45U8rMjlewr/vTEwc8sm8/37s+XKdcuIq0gbqJovAAsC8CEcJigAD++eUcuj61L53xdJ1UtfcSHz2NbbhwJ4TLk40qSAG6iqLaTlKhgEmQcUgiHS4oMIilS+msZSSqbN1FU08FKGf4RQngpSQBTqOvop75rkLULpAAshPBOkgCmcKa6HYB1C2MNjkQIIZxDEsAUTl9rJyLIX6aiCSG8liSAKZy+1s7ajBjpGy+E8FqSACbR2jtEZUsfaxdKL3khhPeSBDCJM9fGx/8lAQghvJckgEmcutZOUICJ/GTZgEII4b0kAUzi44pW1mbEEOgv/3uEEN5L3uFu0Nw9yNXmXjZnxxkdihBCOJUkgBscr2wDYHOWJAAhhHeTBHCDjytaiQwOYElyxPQHCyGEB5MEMIHWmuOVbWzMjJX5/0IIrycJYIKatn7MnQNszpb2D0II7ycJYILxbeq25hi/Gb0QQjibJIAJjlxpYWFcKBlxoUaHIoQQTicJYMzgiJUTlW3cukju/oUQvkESwJgTVW0MWWzcuijB6FCEEMIlJAGMOVLeTFCAifXS/0cI4SMkATA6/fODy81syoojKMDP6HCEEMIlJAEAlxq6qW0f4K6liUaHIoQQLiMJADhY0ohJwe2LJQEIIXyHJADgndJG1i2MITZsntGhCCGEy/h8Aqhs6eVKUy93L00yOhQhhHApn08A75Q0AnCnJAAhhI/x6QSgtebVc3Wsy4ghOSrY6HCEEMKlfDoBXDR3UdnSx/2rU4wORQghXM6nE8Cr58wE+pvYtWy+0aEIIYTL+WwCGLHaeON8PbcvTiAyOMDocIQQwuV8NgG8U9JIW98wD61JNToUIYQwhM8mgN8dryY9JoRbcqX5mxDCN9mVAJRSK5VSJ5VSxUqpQqXUuimOq1ZKXRw/zp5rOkKJuYvCmg6+uHGBbP0ohPBZ/nb+/A+A72qt31ZK7Rr7+tYpjt2utW6183oO8dvj1QQH+PHZgjSjQxFCCMPYOwSkgYixzyOBejvP53Q1bX28XmTm4YJUKf4KIXyavU8A3wAOKqV+yGgy2TTFcRo4pJSyAj/XWv/CzuvO2Y/ev4qfSfH09myjQhBCCLcwbQJQSh0CJuuT8D+B24C/1Fq/opR6GHgWuH2SY7dorc1KqQTgPaVUudb6oymu9xTwFEB6evoMX8bMVDT38HqRmS9vzSQhIsih5xZCCE+jtNZz/2GluoAorbVWSimgS2sdMc3P/B3Qq7X+4XTnLygo0IWFjqkZ22yaR39xkrLGbo781a3S+VMI4ZWUUme11gUzOdbeGkA9cMvY5zuAq5MEE6qUCh//HLgTKLHzurP2h1M1nK5u5zu7l8ibvxBCYH8N4E+BHyml/IFBxoZulFLJwK+01ruAROC10QcE/IHntdbv2HndWblQ18n3D5SzLTeez8rCLyGEAOxMAFrrY8CaSb5fD+wa+7wKWGHPdexR0dzLE785Q2xYID98aDljiUgIIXyevU8AbmtwxMor5+r4/oFyggJM/MefrJfCrxBCTOB1CWDIYuXhn5+k1NyFxabZlBXLvzy4nLSYEKNDE0IIt+J1CWCevx+ZcaFsyopl3cIYbs2Nl2EfIYSYhNclAID/+8hKo0MQQgi357PdQIUQwtdJAhBCCB8lCUAIIXyUJAAhhPBRkgCEEMJHSQIQQggfJQlACCF8lCQAIYTwUXbtB+BsSqkWoGaOPx4HuMUexC4ir9e7yev1bo58vQu01vEzOdCtE4A9lFKFM90UwRvI6/Vu8nq9m1GvV4aAhBDCR0kCEEIIH+XNCeAXRgfgYvJ6vZu8Xu9myOv12hqAEEKIm/PmJwAhhBA34XUJQCl1t1LqslKqQin1baPjcTal1K+VUs1KqRKjY3EFpVSaUuqwUuqSUqpUKfV1o2NyJqVUkFLqtFLq/Njr/a7RMTmbUspPKVWklHrT6FhcQSlVrZS6qJQqVkoVuvTa3jQEpJTyA64AdwB1wBngc1rrS4YG5kRKqW1AL/B7rXW+0fE4m1JqPjBfa31OKRUOnAXu89bfsRrdzi5Ua92rlAoAjgFf11qfNDg0p1FKfRMoACK01ruNjsfZlFLVQIHW2uXrHrztCWAdUKG1rtJaDwMvAHsMjsmptNYfAe1Gx+EqWusGrfW5sc97gDIgxdionEeP6h37MmDsw3vu2m6glEoFPgP8yuhYfIG3JYAUoHbC13V48ZuDr1NKZQCrgFPGRuJcY0MixUAz8J7W2ptf778B/w2wGR2IC2ngkFLqrFLqKVde2NsSgPARSqkw4BXgG1rrbqPjcSattVVrvRJIBdYppbxyqE8ptRto1lqfNToWF9sy9vvdCTw9NqzrEt6WAMxA2oSvU8e+J7zI2Fj4K8BzWutXjY7HVbTWncBh4G6jY3GSzcC9Y2PiLwA7lFJ/MDYk59Nam8f+2wy8xuhQtkt4WwI4A+QopRYqpQKBR4H9BsckHGisKPosUKa1/j9Gx+NsSql4pVTU2OfBjE5wKDc2KufQWv8PrXWq1jqD0X+7H2itP29wWE6llAodm8yAUioUuBNw2Yw+r0oAWmsL8FXgIKPFwb1a61Jjo3IupdQfgRPAIqVUnVLqT4yOyck2A19g9O6weOxjl9FBOdF84LBS6gKjNzjvaa19Ynqkj0gEjimlzgOngbe01u+46uJeNQ1UCCHEzHnVE4AQQoiZkwQghBA+ShKAEEL4KEkAQgjhoyQBCCGEj5IEIIQQPkoSgBBC+ChJAEII4aP+H9FkFJtzMxkdAAAAAElFTkSuQmCC",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x10f2eb630>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ibands = 1  # band number from 0 --> number of bands\n",
-    "spin = str(Spin.up)\n",
-    "\n",
-    "x = list()\n",
-    "y = list()\n",
-    "for xpath, epath in zip(data[\"distances\"], data[\"energy\"]):\n",
-    "    x += xpath\n",
-    "    y += epath[spin][ibands]\n",
-    "\n",
-    "plt.plot(x, y)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### 4) Plot DOS\n",
-    "\n",
-    "Read the DOS from another calculations."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "5.24546925\n",
-      "5.24546925\n"
-     ]
-    }
-   ],
-   "source": [
-    "dosrun = Vasprun(\"../DOS_SMEAR/vasprun.xml\", parse_dos=True)\n",
-    "dos = dosrun.complete_dos\n",
-    "print(dosrun.efermi)\n",
-    "print(dos.efermi)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x10ec1a588>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "dosplot = DosPlotter(sigma=0.1)\n",
-    "dosplot.add_dos(\"Total DOS\", dos)\n",
-    "dosplot.add_dos_dict(dos.get_element_dos())\n",
-    "plt = dosplot.get_plot()\n",
-    "plt.grid()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### 5) Plot Bands and DOS"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "bs = run.get_band_structure(\"KPOINTS\", efermi=dos.efermi)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x10ed38c88>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "bsdosplot = BSDOSPlotter(\n",
-    "    bs_projection=\"elements\",\n",
-    "    dos_projection=\"elements\",\n",
-    "    vb_energy_range=22,\n",
-    "    egrid_interval=2.5,\n",
-    ")\n",
-    "plt = bsdosplot.get_plot(bs, dos=dos)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x10ec5e2e8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "bsdosplot = BSDOSPlotter(\n",
-    "    bs_projection=\"elements\",\n",
-    "    dos_projection=\"elements\",\n",
-    "    vb_energy_range=11,\n",
-    "    cb_energy_range=10,\n",
-    "    egrid_interval=2,\n",
-    ")\n",
-    "plt = bsdosplot.get_plot(bs, dos=dos)"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.9.12"
-  },
-  "vscode": {
-   "interpreter": {
-    "hash": "8022b3e932e045c760cb4633b91dd1cb8bc60d104ca9808334cbd1645adbe837"
-   }
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/notebooks/2013-01-01-Calculating Reaction Energies with the Materials API.ipynb b/notebooks/2013-01-01-Calculating Reaction Energies with the Materials API.ipynb
index 9fe40cd..9d8627e 100644
--- a/notebooks/2013-01-01-Calculating Reaction Energies with the Materials API.ipynb	
+++ b/notebooks/2013-01-01-Calculating Reaction Energies with the Materials API.ipynb	
@@ -9,30 +9,40 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
     "# Uncomment the subsequent lines in this cell to install dependencies for Google Colab.\n",
-    "# !pip install pymatgen==2022.7.19\n",
-    "from __future__ import annotations"
+    "# !pip install pymatgen==2022.7.19"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "a2df3dedded4417a9585b20941e0c078",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Retrieving ThermoDoc documents:   0%|          | 0/176 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
       "Caculated\n",
       "CaO + CO2 -> CaCO3\n",
-      "Reaction energy = -146.67299148102813 kJ mol^-1\n",
-      "Experimental\n",
-      "CaO + CO2 -> CaCO3\n",
-      "Reaction energy = -178.30000000000064 kJ mol^-1\n"
+      "Reaction energy = -146.61075988908848 kJ mol^-1\n"
      ]
     }
    ],
@@ -69,22 +79,7 @@
     "\n",
     "print(\"Caculated\")\n",
     "print(reaction)\n",
-    "print(\"Reaction energy = {}\".format(energy.to(\"kJ mol^-1\")))\n",
-    "print\n",
-    "\n",
-    "# The following portions demonstrate how to get the experimental values as well.\n",
-    "exp_CaO = mpr.get_exp_entry(\"CaO\")\n",
-    "exp_CaCO3 = mpr.get_exp_entry(\"CaCO3\")\n",
-    "\n",
-    "# Unfortunately, the Materials Project database does not have gas phase experimental entries. This is the value from NIST. We manually create the entry.\n",
-    "# Exp entries should be in kJ/mol.\n",
-    "exp_CO2 = ComputedEntry(\"CO2\", -393.51)\n",
-    "\n",
-    "exp_reaction = ComputedReaction([exp_CaO, exp_CO2], [exp_CaCO3])\n",
-    "\n",
-    "print(\"Experimental\")\n",
-    "print(exp_reaction)\n",
-    "print(f\"Reaction energy = {exp_reaction.calculated_reaction_energy} kJ mol^-1\")"
+    "print(\"Reaction energy = {}\".format(energy.to(\"kJ mol^-1\")))"
    ]
   }
  ],
diff --git a/notebooks/2017-04-14-Inputs and Analysis of VASP runs.ipynb b/notebooks/2017-04-14-Inputs and Analysis of VASP runs.ipynb
index 7203243..daf9b8d 100644
--- a/notebooks/2017-04-14-Inputs and Analysis of VASP runs.ipynb	
+++ b/notebooks/2017-04-14-Inputs and Analysis of VASP runs.ipynb	
@@ -4,7 +4,9 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Generate VASP Inputs for Structure Relaxation"
+    "# Generate VASP Inputs for Structure Relaxation\n",
+    "\n",
+    "Note that all examples files are just valid vasprun.xml files and not necessary the actual outputs from a proper VASP calculation. They are presented just for code demonstration purposes."
    ]
   },
   {
@@ -14,23 +16,30 @@
    "outputs": [],
    "source": [
     "# Uncomment the subsequent lines in this cell to install dependencies for Google Colab.\n",
-    "# !pip install pymatgen==2022.7.19\n",
-    "from __future__ import annotations"
+    "# !pip install pymatgen==2022.7.19\n"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 2,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/shyue/repos/matgenb/.venv/lib/python3.11/site-packages/pymatgen/io/vasp/sets.py:722: BadInputSetWarning: Relaxation of likely metal with ISMEAR < 0 (-5). See VASP recommendations on ISMEAR for metals (https://www.vasp.at/wiki/index.php/ISMEAR).\n",
+      "  warnings.warn(\n"
+     ]
+    }
+   ],
    "source": [
     "from pymatgen.core import Structure\n",
     "from pymatgen.io.vasp.sets import MPRelaxSet\n",
-    "\n",
-    "s = Structure.from_file(\"Si.cif\", primitive=True)\n",
+    "s = Structure.from_file(\"Al.cif\", primitive=True)\n",
     "custom_settings = {\"NELMIN\": 5}  # user custom incar settings\n",
     "relax = MPRelaxSet(s, user_incar_settings=custom_settings)\n",
-    "relax.write_input(\"Si-relax\")"
+    "relax.write_input(\"Al-relax\")"
    ]
   },
   {
@@ -46,26 +55,29 @@
    "metadata": {},
    "outputs": [
     {
-     "ename": "FileNotFoundError",
-     "evalue": "[Errno 2] No such file or directory: 'Si-relax/vasprun.xml'",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
-      "Cell \u001b[0;32mIn[3], line 3\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mpymatgen\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mio\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mvasp\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m Vasprun\n\u001b[0;32m----> 3\u001b[0m v \u001b[38;5;241m=\u001b[39m \u001b[43mVasprun\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mSi-relax/vasprun.xml\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m      4\u001b[0m \u001b[38;5;28mprint\u001b[39m(v\u001b[38;5;241m.\u001b[39mfinal_energy)  \u001b[38;5;66;03m# final total energy\u001b[39;00m\n\u001b[1;32m      5\u001b[0m s \u001b[38;5;241m=\u001b[39m v\u001b[38;5;241m.\u001b[39mfinal_structure\n",
-      "File \u001b[0;32m~/miniconda3/envs/mavrl/lib/python3.11/site-packages/pymatgen/io/vasp/outputs.py:310\u001b[0m, in \u001b[0;36mVasprun.__init__\u001b[0;34m(self, filename, ionic_step_skip, ionic_step_offset, parse_dos, parse_eigen, parse_projected_eigen, parse_potcar_file, occu_tol, separate_spins, exception_on_bad_xml)\u001b[0m\n\u001b[1;32m    307\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mseparate_spins \u001b[38;5;241m=\u001b[39m separate_spins\n\u001b[1;32m    308\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mexception_on_bad_xml \u001b[38;5;241m=\u001b[39m exception_on_bad_xml\n\u001b[0;32m--> 310\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[43mzopen\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfilename\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmode\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mrt\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mas\u001b[39;00m file:\n\u001b[1;32m    311\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m ionic_step_skip \u001b[38;5;129;01mor\u001b[39;00m ionic_step_offset:\n\u001b[1;32m    312\u001b[0m         \u001b[38;5;66;03m# Remove parts of the xml file and parse the string\u001b[39;00m\n\u001b[1;32m    313\u001b[0m         content: \u001b[38;5;28mstr\u001b[39m \u001b[38;5;241m=\u001b[39m file\u001b[38;5;241m.\u001b[39mread()\n",
-      "File \u001b[0;32m~/miniconda3/envs/mavrl/lib/python3.11/site-packages/monty/io.py:54\u001b[0m, in \u001b[0;36mzopen\u001b[0;34m(filename, *args, **kwargs)\u001b[0m\n\u001b[1;32m     52\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m (lzma \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m) \u001b[38;5;129;01mand\u001b[39;00m (ext \u001b[38;5;129;01min\u001b[39;00m (\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m.XZ\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m.LZMA\u001b[39m\u001b[38;5;124m\"\u001b[39m)):\n\u001b[1;32m     53\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m lzma\u001b[38;5;241m.\u001b[39mopen(filename, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[0;32m---> 54\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mopen\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mfilename\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
-      "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: 'Si-relax/vasprun.xml'"
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "-3.74198121 eV\n",
+      "Full Formula (Al1)\n",
+      "Reduced Formula: Al\n",
+      "abc   :   2.857496   2.857496   2.857496\n",
+      "angles:  60.000000  60.000000  60.000000\n",
+      "pbc   :       True       True       True\n",
+      "Sites (1)\n",
+      "  #  SP      a    b    c\n",
+      "---  ----  ---  ---  ---\n",
+      "  0  Al      0    0    0\n"
      ]
     }
    ],
    "source": [
     "from pymatgen.io.vasp import Vasprun\n",
     "\n",
-    "v = Vasprun(\"Si-relax/vasprun.xml\")\n",
+    "v = Vasprun(\"Al-relax/vasprun.xml.gz\")\n",
     "print(v.final_energy)  # final total energy\n",
     "s = v.final_structure\n",
-    "s.to(filename=\"Si-relax.cif\")  # save relaxed structure into cif file\n",
+    "s.to(fmt=\"cif\")  # save relaxed structure into cif file\n",
     "print(s)  # relaxed structure"
    ]
   },
@@ -78,17 +90,26 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/shyue/repos/matgenb/.venv/lib/python3.11/site-packages/pymatgen/io/vasp/sets.py:999: UserWarning: Use of standardize=True with from_prev_run is not recommended as there is no guarantee the copied files will be appropriate for the standardized structure.\n",
+      "  warnings.warn(\n"
+     ]
+    }
+   ],
    "source": [
     "from pymatgen.io.vasp.sets import MPStaticSet\n",
     "\n",
     "custom_settings = {\"NELM\": 60}  # user custom incar settings\n",
     "static = MPStaticSet.from_prev_calc(\n",
-    "    \"Si-relax/\", standardize=True, user_incar_settings=custom_settings\n",
+    "    \"Al-relax/\", standardize=True, user_incar_settings=custom_settings\n",
     ")\n",
-    "static.write_input(\"Si-static\")"
+    "static.write_input(\"Al-static\")"
    ]
   },
   {
@@ -100,13 +121,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "-3.74198121 eV\n"
+     ]
+    }
+   ],
    "source": [
     "from pymatgen.io.vasp import Vasprun\n",
     "\n",
-    "v = Vasprun(\"Si-static/vasprun.xml\")\n",
+    "v = Vasprun(\"Al-static/vasprun.xml.gz\")\n",
     "print(v.final_energy)  # final total energy"
    ]
   },
@@ -119,27 +148,36 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/shyue/repos/matgenb/.venv/lib/python3.11/site-packages/pymatgen/io/vasp/sets.py:1713: UserWarning: Use of standardize=True with from_prev_run is not recommended as there is no guarantee the copied files will be appropriate for the standardized structure. copy_chgcar is enforced to be false.\n",
+      "  warnings.warn(\n"
+     ]
+    }
+   ],
    "source": [
     "from pymatgen.io.vasp.sets import MPNonSCFSet\n",
     "\n",
     "# generate uniform k-points for DOS calc.\n",
     "custom_settings = {\"LAECHG\": \"False\", \"LVHAR\": \"False\"}  # user custom incar settings\n",
     "dos = MPNonSCFSet.from_prev_calc(\n",
-    "    \"Si-static/\",\n",
+    "    \"Al-static/\",\n",
     "    mode=\"uniform\",\n",
     "    reciprocal_density=200,\n",
     "    user_incar_settings=custom_settings,\n",
     ")\n",
-    "dos.write_input(\"Si-dos\")\n",
+    "dos.write_input(\"Al-dos\")\n",
     "\n",
     "# generate k-points along high symmetry line for band structure calc.\n",
     "band = MPNonSCFSet.from_prev_calc(\n",
-    "    \"Si-static/\", mode=\"line\", standardize=True, user_incar_settings=custom_settings\n",
+    "    \"Al-static/\", mode=\"line\", standardize=True, user_incar_settings=custom_settings\n",
     ")\n",
-    "band.write_input(\"Si-band\")"
+    "band.write_input(\"Al-band\")"
    ]
   },
   {
@@ -151,15 +189,26 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "%matplotlib inline\n",
     "from pymatgen.electronic_structure.plotter import DosPlotter\n",
     "from pymatgen.io.vasp import Vasprun\n",
     "\n",
-    "v = Vasprun(\"Si-dos/vasprun.xml\")\n",
+    "v = Vasprun(\"Al-dos/vasprun.xml.gz\")\n",
     "tdos = v.tdos\n",
     "plotter = DosPlotter()\n",
     "plotter.add_dos(\"Total DOS\", tdos)\n",
@@ -175,15 +224,26 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "%matplotlib inline\n",
     "from pymatgen.electronic_structure.plotter import DosPlotter\n",
     "from pymatgen.io.vasp import Vasprun\n",
     "\n",
-    "v = Vasprun(\"Si-dos/vasprun.xml\")\n",
+    "v = Vasprun(\"Al-dos/vasprun.xml.gz\")\n",
     "cdos = v.complete_dos\n",
     "element_dos = cdos.get_element_dos()\n",
     "plotter = DosPlotter()\n",
@@ -200,15 +260,26 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 9,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "%matplotlib inline\n",
     "from pymatgen.electronic_structure.plotter import DosPlotter\n",
     "from pymatgen.io.vasp import Vasprun\n",
     "\n",
-    "v = Vasprun(\"Si-dos/vasprun.xml\")\n",
+    "v = Vasprun(\"Al-dos/vasprun.xml.gz\")\n",
     "cdos = v.complete_dos\n",
     "spd_dos = cdos.get_spd_dos()\n",
     "plotter = DosPlotter()\n",
@@ -225,19 +296,47 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 10,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Axes: xlabel='$\\\\mathrm{Wave\\\\ Vector}$', ylabel='$\\\\mathrm{E\\\\ -\\\\ E_f\\\\ (eV)}$'>"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "%matplotlib inline\n",
     "from pymatgen.electronic_structure.plotter import BSPlotter\n",
     "from pymatgen.io.vasp import BSVasprun, Vasprun\n",
     "\n",
-    "v = BSVasprun(\"Si-band/vasprun.xml\")\n",
-    "bs = v.get_band_structure(kpoints_filename=\"Si-band/KPOINTS\", line_mode=True)\n",
+    "v = BSVasprun(\"Al-band/vasprun.xml.gz\")\n",
+    "bs = v.get_band_structure(kpoints_filename=\"Al-band/KPOINTS\", line_mode=True)\n",
     "plt = BSPlotter(bs)\n",
     "plt.get_plot(vbm_cbm_marker=True)"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
@@ -256,9 +355,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.5"
+   "version": "3.11.8"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 1
+ "nbformat_minor": 4
 }
diff --git a/notebooks/Al-band/INCAR b/notebooks/Al-band/INCAR
new file mode 100644
index 0000000..e4ebdcc
--- /dev/null
+++ b/notebooks/Al-band/INCAR
@@ -0,0 +1,25 @@
+ALGO = All
+EDIFF = 1e-05
+ENAUG = 1360.0
+ENCUT = 680.0
+ICHARG = 11
+ISMEAR = 0
+ISPIN = 1
+ISYM = 0
+KPOINT_BSE = -1 0 0 0
+LAECHG = False
+LASPH = True
+LCHARG = False
+LELF = True
+LMIXTAU = -1
+LORBIT = 11
+LREAL = Auto
+LVHAR = False
+LVTOT = True
+LWAVE = False
+METAGGA = R2scan
+NBANDS = 6
+NELM = 200
+NSW = 0
+PREC = Accurate
+SIGMA = 0.2
diff --git a/notebooks/Al-band/KPOINTS b/notebooks/Al-band/KPOINTS
new file mode 100644
index 0000000..66f7a0b
--- /dev/null
+++ b/notebooks/Al-band/KPOINTS
@@ -0,0 +1,216 @@
+Non SCF run along symmetry lines
+213
+Reciprocal
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diff --git a/notebooks/Al-band/POSCAR b/notebooks/Al-band/POSCAR
new file mode 100644
index 0000000..8e43408
--- /dev/null
+++ b/notebooks/Al-band/POSCAR
@@ -0,0 +1,9 @@
+Al1
+1.0
+  -0.0000000000000001    2.0205550799999998    2.0205550799999998
+   2.0205550799999998    0.0000000000000000    2.0205550799999998
+   2.0205550799999998    2.0205550799999998    0.0000000000000002
+Al
+1
+direct
+   0.0000000000000000    0.0000000000000000    0.0000000000000000 Al
diff --git a/notebooks/Al-band/POTCAR b/notebooks/Al-band/POTCAR
new file mode 100644
index 0000000..c8d9ecb
--- /dev/null
+++ b/notebooks/Al-band/POTCAR
@@ -0,0 +1,1768 @@
+ PAW_PBE Al 04Jan2001
+ 3.00000000000000000
+ parameters from PSCTR are:
+   VRHFIN =Al: s2p1
+   LEXCH  = PE
+   EATOM  =    53.5387 eV,    3.9350 Ry
+
+   TITEL  = PAW_PBE Al 04Jan2001
+   LULTRA =        F    use ultrasoft PP ?
+   IUNSCR =        1    unscreen: 0-lin 1-nonlin 2-no
+   RPACOR =    1.500    partial core radius
+   POMASS =   26.982; ZVAL   =    3.000    mass and valenz
+   RCORE  =    1.900    outmost cutoff radius
+   RWIGS  =    2.650; RWIGS  =    1.402    wigner-seitz radius (au A)
+   ENMAX  =  240.300; ENMIN  =  180.225 eV
+   ICORE  =        2    local potential
+   LCOR   =        T    correct aug charges
+   LPAW   =        T    paw PP
+   EAUG   =  291.052
+   DEXC   =    -.041
+   RMAX   =    2.974    core radius for proj-oper
+   RAUG   =    1.300    factor for augmentation sphere
+   RDEP   =    1.966    radius for radial grids
+   QCUT   =   -4.203; QGAM   =    8.405    optimization parameters
+ 
+   Description
+     l     E      TYP  RCUT    TYP  RCUT
+     0   .000     23  1.900
+     0   .000     23  1.900
+     1   .000     23  1.900
+     1  1.000     23  1.900
+     2   .000      7  1.900
+   Error from kinetic energy argument (eV)
+   NDATA  =      100
+   STEP   =   20.000   1.050
+  2.17      1.95      1.85      1.68      1.61      1.48      1.37      1.32
+  1.24      1.17      1.14      1.08      1.03      .977      .931      .886
+  .843      .801      .758      .695      .653      .611      .549      .509
+  .469      .413      .359      .325      .278      .235      .197      .163
+  .133      .107      .858E-01  .676E-01  .483E-01  .370E-01  .256E-01  .193E-01
+  .132E-01  .922E-02  .676E-02  .535E-02  .461E-02  .426E-02  .410E-02  .397E-02
+  .383E-02  .358E-02  .322E-02  .288E-02  .243E-02  .199E-02  .152E-02  .120E-02
+  .964E-03  .771E-03  .660E-03  .604E-03  .576E-03  .555E-03  .527E-03  .479E-03
+  .425E-03  .355E-03  .288E-03  .231E-03  .185E-03  .161E-03  .147E-03  .140E-03
+  .133E-03  .123E-03  .108E-03  .913E-04  .740E-04  .607E-04  .519E-04  .482E-04
+  .459E-04  .430E-04  .384E-04  .320E-04  .261E-04  .219E-04  .198E-04  .188E-04
+  .176E-04  .155E-04  .128E-04  .107E-04  .933E-05  .881E-05  .825E-05  .723E-05
+  .594E-05  .506E-05  .462E-05  .439E-05
+END of PSCTR-controll parameters
+ local part
+ 98.2657514061040160
+  -.11196040E+01  -.11177563E+01  -.11049391E+01  -.10835857E+01  -.10537102E+01
+  -.10153337E+01  -.96848653E+00  -.91320931E+00  -.84955472E+00  -.77758869E+00
+  -.69739125E+00  -.60905702E+00  -.51269522E+00  -.40842942E+00  -.29639696E+00
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+ gradient corrections used for XC
+ 5
+ core charge-density (partial)
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+   .70899290E-08   .69009630E-08   .66476019E-08   .63330303E-08   .59609865E-08
+   .55357193E-08   .50619397E-08   .45447703E-08   .39896912E-08   .34024845E-08
+   .27891755E-08   .21559726E-08   .15092042E-08   .85525562E-09   .20050533E-09
+  -.44873610E-09  -.10862855E-08  -.17061442E-08  -.23025520E-08  -.28700406E-08
+  -.34034825E-08  -.38981382E-08  -.43496976E-08  -.47543168E-08  -.51086485E-08
+ 19.8421228800786942 T
+ Non local Part
+ 0 2 1.57396957515338021
+ 5.95455379507119975 -0.947622792329037567E-01 -0.947622792329037567E-01 0.296195088768378464E-02
+ Reciprocal Space Part
+   .13409733E+02   .13382075E+02   .13299383E+02   .13162496E+02   .12972802E+02
+   .12732216E+02   .12443151E+02   .12108486E+02   .11731521E+02   .11315936E+02
+   .10865735E+02   .10385193E+02   .98787938E+01   .93511736E+01   .88070567E+01
+   .82511945E+01   .76883045E+01   .71230118E+01   .65597931E+01   .60029244E+01
+   .54564335E+01   .49240574E+01   .44092056E+01   .39149292E+01   .34438970E+01
+   .29983779E+01   .25802301E+01   .21908966E+01   .18314083E+01   .15023919E+01
+   .12040845E+01   .93635322E+00   .69871958E+00   .49038802E+00   .31027782E+00
+   .15705775E+00   .29182647E-01  -.75068728E-01  -.15755540E+00  -.22023607E+00
+  -.26513192E+00  -.29429087E+00  -.30975401E+00  -.31352446E+00  -.30753926E+00
+  -.29364457E+00  -.27357438E+00  -.24893296E+00  -.22118103E+00  -.19162579E+00
+  -.16141461E+00  -.13153226E+00  -.10280149E+00  -.75886681E-01  -.51300211E-01
+  -.29411257E-01  -.10456575E-01   .54470782E-02   .18289318E-01   .28151688E-01
+   .35192780E-01   .39633300E-01   .41741408E-01   .41818646E-01   .40186718E-01
+   .37175352E-01   .33111427E-01   .28309498E-01   .23063815E-01   .17641885E-01
+   .12279569E-01   .71776987E-02   .25001265E-02  -.16268801E-02  -.51140339E-02
+  -.79073552E-02  -.99855950E-02  -.11356924E-01  -.12055066E-01  -.12135042E-01
+  -.11668711E-01  -.10740245E-01  -.94417001E-02  -.78688093E-02  -.61171035E-02
+  -.42784553E-02  -.24381137E-02  -.67227666E-03   .95377115E-03   .23869497E-02
+   .35871154E-02   .45272632E-02   .51932414E-02   .55830355E-02   .57056838E-02
+   .55798975E-02   .52324585E-02   .46964705E-02   .40095377E-02   .32119402E-02
+ Real Space Part
+   .14168332E+02   .14164548E+02   .14153168E+02   .14134110E+02   .14107236E+02
+   .14072351E+02   .14029201E+02   .13977476E+02   .13916802E+02   .13846747E+02
+   .13766822E+02   .13676478E+02   .13575120E+02   .13462104E+02   .13336753E+02
+   .13198366E+02   .13046233E+02   .12879648E+02   .12697933E+02   .12500453E+02
+   .12286641E+02   .12056018E+02   .11808219E+02   .11543011E+02   .11260317E+02
+   .10960234E+02   .10643049E+02   .10309254E+02   .99595526E+01   .95948683E+01
+   .92163417E+01   .88253273E+01   .84233833E+01   .80122567E+01   .75938636E+01
+   .71702647E+01   .67436372E+01   .63162432E+01   .58903953E+01   .54684206E+01
+   .50526239E+01   .46452503E+01   .42484496E+01   .38642423E+01   .34944874E+01
+   .31408551E+01   .28048028E+01   .24875556E+01   .21900922E+01   .19131367E+01
+   .16571542E+01   .14223538E+01   .12086951E+01   .10159005E+01   .84347138E+00
+   .69070857E+00   .55673541E+00   .44052363E+00   .34092076E+00   .25667855E+00
+   .18648144E+00   .12897456E+00   .82790505E-01   .46574318E-01   .19006105E-01
+  -.11789916E-02  -.15173868E-01  -.24085734E-01  -.28925672E-01  -.30601483E-01
+  -.29913685E-01  -.27554490E-01  -.24109477E-01  -.20061646E-01  -.15797484E-01
+  -.11614647E-01  -.77308590E-02  -.42936222E-02  -.13903576E-02   .94138527E-03
+   .27039652E-02   .39302082E-02   .46747130E-02   .50060754E-02   .50001483E-02
+   .47344072E-02   .42834371E-02   .37155182E-02   .30902480E-02   .24571077E-02
+   .18548572E-02   .13116297E-02   .84558522E-03   .46598444E-03   .17454639E-03
+  -.33035122E-04  -.16552831E-03  -.23464831E-03  -.25366604E-03  -.23619783E-03
+ Reciprocal Space Part
+   .22782613E+02   .23315036E+02   .24902461E+02   .27515550E+02   .31106045E+02
+   .35607707E+02   .40937615E+02   .46997770E+02   .53677000E+02   .60853104E+02
+   .68395199E+02   .76166219E+02   .84025512E+02   .91831484E+02   .99444233E+02
+   .10672812E+03   .11355423E+03   .11980265E+03   .12536457E+03   .13014412E+03
+   .13405990E+03   .13704626E+03   .13905420E+03   .14005194E+03   .14002513E+03
+   .13897680E+03   .13692684E+03   .13391124E+03   .12998106E+03   .12520107E+03
+   .11964820E+03   .11340978E+03   .10658163E+03   .99266060E+02   .91569770E+02
+   .83601783E+02   .75471360E+02   .67286004E+02   .59149575E+02   .51160538E+02
+   .43410401E+02   .35982338E+02   .28950054E+02   .22376876E+02   .16315096E+02
+   .10805572E+02   .58775711E+01   .15488595E+01  -.21739765E+01  -.52949998E+01
+  -.78281995E+01  -.97966024E+01  -.11231245E+02  -.12170039E+02  -.12656555E+02
+  -.12738765E+02  -.12467763E+02  -.11896499E+02  -.11078562E+02  -.10067019E+02
+  -.89133461E+01  -.76664768E+01  -.63719601E+01  -.50712644E+01  -.38012212E+01
+  -.25936171E+01  -.14749341E+01  -.46623308E+00   .41682414E+00   .11638261E+01
+   .17693472E+01   .22325832E+01   .25569021E+01   .27493279E+01   .28199759E+01
+   .27814568E+01   .26482677E+01   .24361865E+01   .21616865E+01   .18413835E+01
+   .14915296E+01   .11275626E+01   .76371893E+00   .41271721E+00   .85513783E-01
+  -.20886718E+00  -.46343070E+00  -.67323809E+00  -.83536896E+00  -.94882456E+00
+  -.10143798E+01  -.10343929E+01  -.10125814E+01  -.95377446E+00  -.86365056E+00
+  -.74847025E+00  -.61481243E+00  -.46932237E+00  -.31847831E+00  -.16838293E+00
+ Real Space Part
+   .67870036E+03   .67870018E+03   .67867834E+03   .67857166E+03   .67827732E+03
+   .67765642E+03   .67653890E+03   .67472952E+03   .67201476E+03   .66817044E+03
+   .66296977E+03   .65619161E+03   .64762864E+03   .63709519E+03   .62443445E+03
+   .60952495E+03   .59228597E+03   .57268173E+03   .55072433E+03   .52647529E+03
+   .50004563E+03   .47159452E+03   .44132659E+03   .40948792E+03   .37636085E+03
+   .34225791E+03   .30751483E+03   .27248303E+03   .23752177E+03   .20299012E+03
+   .16923911E+03   .13660416E+03   .10539804E+03   .75904601E+02   .48373350E+02
+   .23015018E+02  -.17530555E-02  -.20552589E+02  -.38558389E+02  -.53985185E+02
+  -.66842894E+02  -.77183055E+02  -.85095653E+02  -.90705160E+02  -.94165948E+02
+  -.95657212E+02  -.95377600E+02  -.93539678E+02  -.90364424E+02  -.86075877E+02
+  -.80896089E+02  -.75040500E+02  -.68713826E+02  -.62106548E+02  -.55392046E+02
+  -.48724413E+02  -.42236960E+02  -.36041382E+02  -.30227573E+02  -.24864026E+02
+  -.19998753E+02  -.15660655E+02  -.11861258E+02  -.85967224E+01  -.58500506E+01
+  -.35933890E+01  -.17903604E+01  -.39834401E+00   .62935963E+00   .13415316E+01
+   .17872494E+01   .20143452E+01   .20681249E+01   .19903586E+01   .18185396E+01
+   .15854000E+01   .13186656E+01   .10410237E+01   .77027522E+00   .51963802E+00
+   .29816771E+00   .11126218E+00  -.38782344E-01  -.15219382E+00  -.23115179E+00
+  -.27924207E+00  -.30095696E+00  -.30125413E+00  -.28518342E+00  -.25758592E+00
+  -.22286623E+00  -.18483508E+00  -.14661700E+00  -.11061535E+00  -.78525597E-01
+  -.51387033E-01  -.29662701E-01  -.13337670E-01  -.20265672E-02   .49177022E-02
+ Non local Part
+ 1 2 1.57396957515338021
+ 2.08596921736620722 -0.219845133596054454 -0.219845133596054454 0.318470468308045818E-01
+ Reciprocal Space Part
+   .00000000E+00   .91444362E+00   .18200628E+01   .27081564E+01   .35702672E+01
+   .43982992E+01   .51846279E+01   .59222029E+01   .66046406E+01   .72263059E+01
+   .77823805E+01   .82689184E+01   .86828863E+01   .90221895E+01   .92856818E+01
+   .94731617E+01   .95853519E+01   .96238662E+01   .95911622E+01   .94904822E+01
+   .93257828E+01   .91016553E+01   .88232384E+01   .84961246E+01   .81262624E+01
+   .77198561E+01   .72832654E+01   .68229055E+01   .63451509E+01   .58562434E+01
+   .53622059E+01   .48687645E+01   .43812779E+01   .39046771E+01   .34434149E+01
+   .30014259E+01   .25820974E+01   .21882514E+01   .18221371E+01   .14854338E+01
+   .11792633E+01   .90421166E+00   .66035883E+00   .44731547E+00   .26426574E+00
+   .11001489E+00  -.16959482E-01  -.11845383E+00  -.19648383E+00  -.25322950E+00
+  -.29098142E+00  -.31208901E+00  -.31891180E+00  -.31377445E+00  -.29892618E+00
+  -.27650527E+00  -.24850873E+00  -.21676767E+00  -.18292833E+00  -.14843870E+00
+  -.11454071E+00  -.82267567E-01  -.52446018E-01  -.25702942E-01  -.24758515E-02
+   .16973315E-01   .32541723E-01   .44267105E-01   .52307807E-01   .56922016E-01
+   .58446762E-01   .57277240E-01   .53846950E-01   .48609073E-01   .42019463E-01
+   .34521535E-01   .26533281E-01   .18436538E-01   .10568602E-01   .32161666E-02
+  -.33884585E-02  -.90689793E-02  -.13704765E-01  -.17228726E-01  -.19623655E-01
+  -.20917313E-01  -.21176526E-01  -.20500578E-01  -.19014180E-01  -.16860294E-01
+  -.14193031E-01  -.11170883E-01  -.79504486E-02  -.46808410E-02  -.14988831E-02
+   .14748080E-02   .41388000E-02   .64128687E-02   .82390791E-02   .95819716E-02
+ Real Space Part
+   .00000000E+00   .85309095E+00   .17068897E+01   .25619792E+01   .34186972E+01
+   .42770239E+01   .51364833E+01   .59960591E+01   .68541311E+01   .77084320E+01
+   .85560280E+01   .93933233E+01   .10216089E+02   .11019515E+02   .11798286E+02
+   .12546676E+02   .13258660E+02   .13928044E+02   .14548598E+02   .15114207E+02
+   .15619011E+02   .16057551E+02   .16424913E+02   .16716851E+02   .16929902E+02
+   .17061488E+02   .17109989E+02   .17074805E+02   .16956381E+02   .16756224E+02
+   .16476883E+02   .16121911E+02   .15695805E+02   .15203923E+02   .14652384E+02
+   .14047957E+02   .13397928E+02   .12709970E+02   .11992000E+02   .11252039E+02
+   .10498070E+02   .97379027E+01   .89790527E+01   .82286216E+01   .74931981E+01
+   .67787712E+01   .60906616E+01   .54334692E+01   .48110393E+01   .42264467E+01
+   .36819955E+01   .31792365E+01   .27189983E+01   .23014311E+01   .19260618E+01
+   .15918583E+01   .12972993E+01   .10404493E+01   .81903589E+00   .63052672E+00
+   .47220493E+00   .34124110E+00   .23476029E+00   .14990293E+00   .83878565E-01
+   .34011999E-01  -.22187125E-02  -.27152431E-01  -.42923156E-01  -.51445940E-01
+  -.54409961E-01  -.53278076E-01  -.49292041E-01  -.43482528E-01  -.36683042E-01
+  -.29546785E-01  -.22565597E-01  -.16090112E-01  -.10350361E-01  -.54761336E-02
+  -.15165109E-02   .15418954E-02   .37583729E-02   .52234553E-02   .60463403E-02
+   .63444334E-02   .62349887E-02   .58287507E-02   .52254374E-02   .45108691E-02
+   .37555125E-02   .30142006E-02   .23267784E-02   .17194394E-02   .12065275E-02
+   .79260455E-03   .47461243E-03   .24398580E-03   .88606522E-04  -.54803893E-05
+ Reciprocal Space Part
+   .00000000E+00  -.83498910E+00  -.16210622E+01  -.23104234E+01  -.28574909E+01
+  -.32199425E+01  -.33596863E+01  -.32437372E+01  -.28449779E+01  -.21427893E+01
+  -.11235349E+01   .21910978E+00   .18839910E+01   .38624748E+01   .61386104E+01
+   .86894527E+01   .11485537E+02   .14491493E+02   .17666786E+02   .20966562E+02
+   .24342585E+02   .27744237E+02   .31119566E+02   .34416348E+02   .37583151E+02
+   .40570366E+02   .43331197E+02   .45822568E+02   .48005954E+02   .49848094E+02
+   .51321591E+02   .52405380E+02   .53085050E+02   .53353033E+02   .53208641E+02
+   .52657958E+02   .51713607E+02   .50394370E+02   .48724708E+02   .46734162E+02
+   .44456679E+02   .41929851E+02   .39194116E+02   .36291913E+02   .33266832E+02
+   .30162758E+02   .27023048E+02   .23889743E+02   .20802833E+02   .17799600E+02
+   .14914036E+02   .12176355E+02   .96126055E+01   .72443863E+01   .50886642E+01
+   .31577012E+01   .14590822E+01  -.41603396E-02  -.12333316E+01  -.22337787E+01
+  -.30145253E+01  -.35878468E+01  -.39688012E+01  -.41747256E+01  -.42247146E+01
+  -.41390918E+01  -.39388882E+01  -.36453379E+01  -.32794042E+01  -.28613431E+01
+  -.24103142E+01  -.19440445E+01  -.14785503E+01  -.10279200E+01  -.60415995E+00
+  -.21710162E+00   .12562985E+00   .41859060E+00   .65844015E+00   .84381665E+00
+   .97517162E+00   .10545714E+01   .10854732E+01   .10724824E+01   .10211013E+01
+   .93747368E+00   .82813501E+00   .69977333E+00   .55900714E+00   .41218506E+00
+   .26521133E+00   .12340009E+00  -.86396001E-02  -.12708702E+00  -.22896138E+00
+  -.31214272E+00  -.37536384E+00  -.41817583E+00  -.44089029E+00  -.44450187E+00
+ Real Space Part
+   .00000000E+00   .26085377E+02   .51924350E+02   .77273381E+02   .10189463E+03
+   .12555874E+03   .14804753E+03   .16915655E+03   .18869754E+03   .20650067E+03
+   .22241657E+03   .23631817E+03   .24810224E+03   .25769060E+03   .26503112E+03
+   .27009826E+03   .27289331E+03   .27344430E+03   .27180542E+03   .26805612E+03
+   .26229988E+03   .25466251E+03   .24529016E+03   .23434703E+03   .22201274E+03
+   .20847949E+03   .19394903E+03   .17862948E+03   .16273206E+03   .14646782E+03
+   .13004436E+03   .11366275E+03   .97514541E+02   .81779007E+02   .66620708E+02
+   .52187346E+02   .38608004E+02   .25991781E+02   .14426842E+02   .39799125E+01
+  -.53038085E+01  -.13400300E+02  -.20305974E+02  -.26036550E+02  -.30625599E+02
+  -.34122792E+02  -.36591902E+02  -.38108637E+02  -.38758330E+02  -.38633570E+02
+  -.37831828E+02  -.36453127E+02  -.34597819E+02  -.32364505E+02  -.29848161E+02
+  -.27138474E+02  -.24318440E+02  -.21463237E+02  -.18639365E+02  -.15904084E+02
+  -.13305110E+02  -.10880592E+02  -.86593085E+01  -.66610979E+01  -.48974623E+01
+  -.33723283E+01  -.20829232E+01  -.10207335E+01  -.17250887E+00   .47872073E+00
+   .95264583E+00   .12707242E+01   .14552970E+01   .15287927E+01   .15130345E+01
+   .14286600E+01   .12946585E+01   .11280262E+01   .94353671E+00   .75361867E+00
+   .56833199E+00   .39542954E+00   .24049102E+00   .10711426E+00  -.28511252E-02
+  -.89042306E-01  -.15230805E+00  -.19443228E+00  -.21786747E+00  -.22548699E+00
+  -.22036365E+00  -.20557950E+00  -.18407003E+00  -.15850398E+00  -.13119836E+00
+  -.10406658E+00  -.78596797E-01  -.55856123E-01  -.36516393E-01  -.20896302E-01
+ PAW radial sets
+ 323 1.04059493489918520
+(5E20.12)                                
+ augmentation charges (non sperical)
+  -.341766652135E-01  -.122010546069E-02  -.116040768608E-01  -.363810619556E-02  -.122010546069E-02
+   .384576074109E-04  -.679372435619E-03   .157116179356E-03  -.116040768608E-01  -.679372435619E-03
+   .138577003978E-02  -.265884052569E-02  -.363810619556E-02   .157116179356E-03  -.265884052569E-02
+   .601327217851E-03
+ uccopancies in atom
+   .200000000196E+01   .000000000000E+00   .000000000000E+00   .000000000000E+00   .000000000000E+00
+   .000000000000E+00   .000000000000E+00   .000000000000E+00   .000000000000E+00   .000000000000E+00
+   .333333333668E+00   .000000000000E+00   .000000000000E+00   .000000000000E+00   .000000000000E+00
+   .000000000000E+00
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+ core charge-density (pseudized)
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+ pseudo wavefunction
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+   .904887507411E+00   .915218814120E+00   .922553366029E+00
+ ae wavefunction
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+ pseudo wavefunction
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+ ae wavefunction
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+ pseudo wavefunction
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literal 0
HcmV?d00001

diff --git a/notebooks/Al-dos/INCAR b/notebooks/Al-dos/INCAR
new file mode 100644
index 0000000..54d6f17
--- /dev/null
+++ b/notebooks/Al-dos/INCAR
@@ -0,0 +1,26 @@
+ALGO = All
+EDIFF = 1e-05
+ENAUG = 1360.0
+ENCUT = 680.0
+ICHARG = 11
+ISMEAR = -5
+ISPIN = 1
+ISYM = 2
+KPOINT_BSE = -1 0 0 0
+LAECHG = False
+LASPH = True
+LCHARG = False
+LELF = True
+LMIXTAU = -1
+LORBIT = 11
+LREAL = Auto
+LVHAR = False
+LVTOT = True
+LWAVE = False
+METAGGA = R2scan
+NBANDS = 6
+NEDOS = 2001
+NELM = 200
+NSW = 0
+PREC = Accurate
+SIGMA = 0.5
diff --git a/notebooks/Al-dos/KPOINTS b/notebooks/Al-dos/KPOINTS
new file mode 100644
index 0000000..c263e77
--- /dev/null
+++ b/notebooks/Al-dos/KPOINTS
@@ -0,0 +1,4 @@
+pymatgen with grid density = 3007 / number of atoms
+0
+Gamma
+14 14 14
diff --git a/notebooks/Al-dos/POSCAR b/notebooks/Al-dos/POSCAR
new file mode 100644
index 0000000..687f0e8
--- /dev/null
+++ b/notebooks/Al-dos/POSCAR
@@ -0,0 +1,9 @@
+Al1
+1.0
+   0.0000000000000000    2.0205550799999998    2.0205550799999998
+   2.0205550799999998    0.0000000000000000    2.0205550799999998
+   2.0205550799999998    2.0205550799999998   -0.0000000000000000
+Al
+1
+direct
+   0.0000000000000000    0.0000000000000000    0.0000000000000000 Al
diff --git a/notebooks/Al-dos/POTCAR b/notebooks/Al-dos/POTCAR
new file mode 100644
index 0000000..c8d9ecb
--- /dev/null
+++ b/notebooks/Al-dos/POTCAR
@@ -0,0 +1,1768 @@
+ PAW_PBE Al 04Jan2001
+ 3.00000000000000000
+ parameters from PSCTR are:
+   VRHFIN =Al: s2p1
+   LEXCH  = PE
+   EATOM  =    53.5387 eV,    3.9350 Ry
+
+   TITEL  = PAW_PBE Al 04Jan2001
+   LULTRA =        F    use ultrasoft PP ?
+   IUNSCR =        1    unscreen: 0-lin 1-nonlin 2-no
+   RPACOR =    1.500    partial core radius
+   POMASS =   26.982; ZVAL   =    3.000    mass and valenz
+   RCORE  =    1.900    outmost cutoff radius
+   RWIGS  =    2.650; RWIGS  =    1.402    wigner-seitz radius (au A)
+   ENMAX  =  240.300; ENMIN  =  180.225 eV
+   ICORE  =        2    local potential
+   LCOR   =        T    correct aug charges
+   LPAW   =        T    paw PP
+   EAUG   =  291.052
+   DEXC   =    -.041
+   RMAX   =    2.974    core radius for proj-oper
+   RAUG   =    1.300    factor for augmentation sphere
+   RDEP   =    1.966    radius for radial grids
+   QCUT   =   -4.203; QGAM   =    8.405    optimization parameters
+ 
+   Description
+     l     E      TYP  RCUT    TYP  RCUT
+     0   .000     23  1.900
+     0   .000     23  1.900
+     1   .000     23  1.900
+     1  1.000     23  1.900
+     2   .000      7  1.900
+   Error from kinetic energy argument (eV)
+   NDATA  =      100
+   STEP   =   20.000   1.050
+  2.17      1.95      1.85      1.68      1.61      1.48      1.37      1.32
+  1.24      1.17      1.14      1.08      1.03      .977      .931      .886
+  .843      .801      .758      .695      .653      .611      .549      .509
+  .469      .413      .359      .325      .278      .235      .197      .163
+  .133      .107      .858E-01  .676E-01  .483E-01  .370E-01  .256E-01  .193E-01
+  .132E-01  .922E-02  .676E-02  .535E-02  .461E-02  .426E-02  .410E-02  .397E-02
+  .383E-02  .358E-02  .322E-02  .288E-02  .243E-02  .199E-02  .152E-02  .120E-02
+  .964E-03  .771E-03  .660E-03  .604E-03  .576E-03  .555E-03  .527E-03  .479E-03
+  .425E-03  .355E-03  .288E-03  .231E-03  .185E-03  .161E-03  .147E-03  .140E-03
+  .133E-03  .123E-03  .108E-03  .913E-04  .740E-04  .607E-04  .519E-04  .482E-04
+  .459E-04  .430E-04  .384E-04  .320E-04  .261E-04  .219E-04  .198E-04  .188E-04
+  .176E-04  .155E-04  .128E-04  .107E-04  .933E-05  .881E-05  .825E-05  .723E-05
+  .594E-05  .506E-05  .462E-05  .439E-05
+END of PSCTR-controll parameters
+ local part
+ 98.2657514061040160
+  -.11196040E+01  -.11177563E+01  -.11049391E+01  -.10835857E+01  -.10537102E+01
+  -.10153337E+01  -.96848653E+00  -.91320931E+00  -.84955472E+00  -.77758869E+00
+  -.69739125E+00  -.60905702E+00  -.51269522E+00  -.40842942E+00  -.29639696E+00
+  -.17674840E+00  -.49646910E-01   .84732128E-01   .22620132E+00   .37456122E+00
+   .52960001E+00   .69109312E+00   .85880261E+00   .10324767E+01   .12118494E+01
+   .13966402E+01   .15865537E+01   .17812803E+01   .19804960E+01   .21838631E+01
+   .23910305E+01   .26016344E+01   .28152987E+01   .30316358E+01   .32502469E+01
+   .34707226E+01   .36926434E+01   .39155809E+01   .41390977E+01   .43627492E+01
+   .45860841E+01   .48086459E+01   .50299739E+01   .52496049E+01   .54670742E+01
+   .56819175E+01   .58936719E+01   .61018779E+01   .63060802E+01   .65058297E+01
+   .67006847E+01   .68902126E+01   .70739913E+01   .72516109E+01   .74226751E+01
+   .75868032E+01   .77436311E+01   .78928134E+01   .80340244E+01   .81669598E+01
+   .82913377E+01   .84069000E+01   .85134133E+01   .86106704E+01   .86984902E+01
+   .87767197E+01   .88452338E+01   .89039366E+01   .89527612E+01   .89916710E+01
+   .90206591E+01   .90397490E+01   .90489941E+01   .90484779E+01   .90383136E+01
+   .90186433E+01   .89896376E+01   .89514949E+01   .89044406E+01   .88487257E+01
+   .87846262E+01   .87124416E+01   .86324938E+01   .85451255E+01   .84506988E+01
+   .83495936E+01   .82422058E+01   .81289454E+01   .80102351E+01   .78865077E+01
+   .77582050E+01   .76257751E+01   .74896708E+01   .73503477E+01   .72082620E+01
+   .70638688E+01   .69176200E+01   .67699625E+01   .66213364E+01   .64721729E+01
+   .63228932E+01   .61739059E+01   .60256063E+01   .58783742E+01   .57325732E+01
+   .55885488E+01   .54466274E+01   .53071157E+01   .51702992E+01   .50364417E+01
+   .49057846E+01   .47785463E+01   .46549220E+01   .45350830E+01   .44191768E+01
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+   .29218677E+01   .28874903E+01   .28552118E+01   .28248347E+01   .27961629E+01
+   .27690023E+01   .27431629E+01   .27184590E+01   .26947108E+01   .26717452E+01
+   .26493969E+01   .26275089E+01   .26059335E+01   .25845330E+01   .25631799E+01
+   .25417576E+01   .25201610E+01   .24982963E+01   .24760814E+01   .24534460E+01
+   .24303316E+01   .24066915E+01   .23824903E+01   .23577042E+01   .23323202E+01
+   .23063359E+01   .22797592E+01   .22526073E+01   .22249067E+01   .21966922E+01
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+   .72997532E+00   .72819269E+00   .72649130E+00   .72484025E+00   .72320923E+00
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+   .69916008E+00   .69590344E+00   .69241507E+00   .68869088E+00   .68472926E+00
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+   .45969364E+00   .45862012E+00   .45750279E+00   .45633075E+00   .45509406E+00
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+ gradient corrections used for XC
+ 5
+ core charge-density (partial)
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+   .35871154E-02   .45272632E-02   .51932414E-02   .55830355E-02   .57056838E-02
+   .55798975E-02   .52324585E-02   .46964705E-02   .40095377E-02   .32119402E-02
+ Real Space Part
+   .14168332E+02   .14164548E+02   .14153168E+02   .14134110E+02   .14107236E+02
+   .14072351E+02   .14029201E+02   .13977476E+02   .13916802E+02   .13846747E+02
+   .13766822E+02   .13676478E+02   .13575120E+02   .13462104E+02   .13336753E+02
+   .13198366E+02   .13046233E+02   .12879648E+02   .12697933E+02   .12500453E+02
+   .12286641E+02   .12056018E+02   .11808219E+02   .11543011E+02   .11260317E+02
+   .10960234E+02   .10643049E+02   .10309254E+02   .99595526E+01   .95948683E+01
+   .92163417E+01   .88253273E+01   .84233833E+01   .80122567E+01   .75938636E+01
+   .71702647E+01   .67436372E+01   .63162432E+01   .58903953E+01   .54684206E+01
+   .50526239E+01   .46452503E+01   .42484496E+01   .38642423E+01   .34944874E+01
+   .31408551E+01   .28048028E+01   .24875556E+01   .21900922E+01   .19131367E+01
+   .16571542E+01   .14223538E+01   .12086951E+01   .10159005E+01   .84347138E+00
+   .69070857E+00   .55673541E+00   .44052363E+00   .34092076E+00   .25667855E+00
+   .18648144E+00   .12897456E+00   .82790505E-01   .46574318E-01   .19006105E-01
+  -.11789916E-02  -.15173868E-01  -.24085734E-01  -.28925672E-01  -.30601483E-01
+  -.29913685E-01  -.27554490E-01  -.24109477E-01  -.20061646E-01  -.15797484E-01
+  -.11614647E-01  -.77308590E-02  -.42936222E-02  -.13903576E-02   .94138527E-03
+   .27039652E-02   .39302082E-02   .46747130E-02   .50060754E-02   .50001483E-02
+   .47344072E-02   .42834371E-02   .37155182E-02   .30902480E-02   .24571077E-02
+   .18548572E-02   .13116297E-02   .84558522E-03   .46598444E-03   .17454639E-03
+  -.33035122E-04  -.16552831E-03  -.23464831E-03  -.25366604E-03  -.23619783E-03
+ Reciprocal Space Part
+   .22782613E+02   .23315036E+02   .24902461E+02   .27515550E+02   .31106045E+02
+   .35607707E+02   .40937615E+02   .46997770E+02   .53677000E+02   .60853104E+02
+   .68395199E+02   .76166219E+02   .84025512E+02   .91831484E+02   .99444233E+02
+   .10672812E+03   .11355423E+03   .11980265E+03   .12536457E+03   .13014412E+03
+   .13405990E+03   .13704626E+03   .13905420E+03   .14005194E+03   .14002513E+03
+   .13897680E+03   .13692684E+03   .13391124E+03   .12998106E+03   .12520107E+03
+   .11964820E+03   .11340978E+03   .10658163E+03   .99266060E+02   .91569770E+02
+   .83601783E+02   .75471360E+02   .67286004E+02   .59149575E+02   .51160538E+02
+   .43410401E+02   .35982338E+02   .28950054E+02   .22376876E+02   .16315096E+02
+   .10805572E+02   .58775711E+01   .15488595E+01  -.21739765E+01  -.52949998E+01
+  -.78281995E+01  -.97966024E+01  -.11231245E+02  -.12170039E+02  -.12656555E+02
+  -.12738765E+02  -.12467763E+02  -.11896499E+02  -.11078562E+02  -.10067019E+02
+  -.89133461E+01  -.76664768E+01  -.63719601E+01  -.50712644E+01  -.38012212E+01
+  -.25936171E+01  -.14749341E+01  -.46623308E+00   .41682414E+00   .11638261E+01
+   .17693472E+01   .22325832E+01   .25569021E+01   .27493279E+01   .28199759E+01
+   .27814568E+01   .26482677E+01   .24361865E+01   .21616865E+01   .18413835E+01
+   .14915296E+01   .11275626E+01   .76371893E+00   .41271721E+00   .85513783E-01
+  -.20886718E+00  -.46343070E+00  -.67323809E+00  -.83536896E+00  -.94882456E+00
+  -.10143798E+01  -.10343929E+01  -.10125814E+01  -.95377446E+00  -.86365056E+00
+  -.74847025E+00  -.61481243E+00  -.46932237E+00  -.31847831E+00  -.16838293E+00
+ Real Space Part
+   .67870036E+03   .67870018E+03   .67867834E+03   .67857166E+03   .67827732E+03
+   .67765642E+03   .67653890E+03   .67472952E+03   .67201476E+03   .66817044E+03
+   .66296977E+03   .65619161E+03   .64762864E+03   .63709519E+03   .62443445E+03
+   .60952495E+03   .59228597E+03   .57268173E+03   .55072433E+03   .52647529E+03
+   .50004563E+03   .47159452E+03   .44132659E+03   .40948792E+03   .37636085E+03
+   .34225791E+03   .30751483E+03   .27248303E+03   .23752177E+03   .20299012E+03
+   .16923911E+03   .13660416E+03   .10539804E+03   .75904601E+02   .48373350E+02
+   .23015018E+02  -.17530555E-02  -.20552589E+02  -.38558389E+02  -.53985185E+02
+  -.66842894E+02  -.77183055E+02  -.85095653E+02  -.90705160E+02  -.94165948E+02
+  -.95657212E+02  -.95377600E+02  -.93539678E+02  -.90364424E+02  -.86075877E+02
+  -.80896089E+02  -.75040500E+02  -.68713826E+02  -.62106548E+02  -.55392046E+02
+  -.48724413E+02  -.42236960E+02  -.36041382E+02  -.30227573E+02  -.24864026E+02
+  -.19998753E+02  -.15660655E+02  -.11861258E+02  -.85967224E+01  -.58500506E+01
+  -.35933890E+01  -.17903604E+01  -.39834401E+00   .62935963E+00   .13415316E+01
+   .17872494E+01   .20143452E+01   .20681249E+01   .19903586E+01   .18185396E+01
+   .15854000E+01   .13186656E+01   .10410237E+01   .77027522E+00   .51963802E+00
+   .29816771E+00   .11126218E+00  -.38782344E-01  -.15219382E+00  -.23115179E+00
+  -.27924207E+00  -.30095696E+00  -.30125413E+00  -.28518342E+00  -.25758592E+00
+  -.22286623E+00  -.18483508E+00  -.14661700E+00  -.11061535E+00  -.78525597E-01
+  -.51387033E-01  -.29662701E-01  -.13337670E-01  -.20265672E-02   .49177022E-02
+ Non local Part
+ 1 2 1.57396957515338021
+ 2.08596921736620722 -0.219845133596054454 -0.219845133596054454 0.318470468308045818E-01
+ Reciprocal Space Part
+   .00000000E+00   .91444362E+00   .18200628E+01   .27081564E+01   .35702672E+01
+   .43982992E+01   .51846279E+01   .59222029E+01   .66046406E+01   .72263059E+01
+   .77823805E+01   .82689184E+01   .86828863E+01   .90221895E+01   .92856818E+01
+   .94731617E+01   .95853519E+01   .96238662E+01   .95911622E+01   .94904822E+01
+   .93257828E+01   .91016553E+01   .88232384E+01   .84961246E+01   .81262624E+01
+   .77198561E+01   .72832654E+01   .68229055E+01   .63451509E+01   .58562434E+01
+   .53622059E+01   .48687645E+01   .43812779E+01   .39046771E+01   .34434149E+01
+   .30014259E+01   .25820974E+01   .21882514E+01   .18221371E+01   .14854338E+01
+   .11792633E+01   .90421166E+00   .66035883E+00   .44731547E+00   .26426574E+00
+   .11001489E+00  -.16959482E-01  -.11845383E+00  -.19648383E+00  -.25322950E+00
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+  -.27650527E+00  -.24850873E+00  -.21676767E+00  -.18292833E+00  -.14843870E+00
+  -.11454071E+00  -.82267567E-01  -.52446018E-01  -.25702942E-01  -.24758515E-02
+   .16973315E-01   .32541723E-01   .44267105E-01   .52307807E-01   .56922016E-01
+   .58446762E-01   .57277240E-01   .53846950E-01   .48609073E-01   .42019463E-01
+   .34521535E-01   .26533281E-01   .18436538E-01   .10568602E-01   .32161666E-02
+  -.33884585E-02  -.90689793E-02  -.13704765E-01  -.17228726E-01  -.19623655E-01
+  -.20917313E-01  -.21176526E-01  -.20500578E-01  -.19014180E-01  -.16860294E-01
+  -.14193031E-01  -.11170883E-01  -.79504486E-02  -.46808410E-02  -.14988831E-02
+   .14748080E-02   .41388000E-02   .64128687E-02   .82390791E-02   .95819716E-02
+ Real Space Part
+   .00000000E+00   .85309095E+00   .17068897E+01   .25619792E+01   .34186972E+01
+   .42770239E+01   .51364833E+01   .59960591E+01   .68541311E+01   .77084320E+01
+   .85560280E+01   .93933233E+01   .10216089E+02   .11019515E+02   .11798286E+02
+   .12546676E+02   .13258660E+02   .13928044E+02   .14548598E+02   .15114207E+02
+   .15619011E+02   .16057551E+02   .16424913E+02   .16716851E+02   .16929902E+02
+   .17061488E+02   .17109989E+02   .17074805E+02   .16956381E+02   .16756224E+02
+   .16476883E+02   .16121911E+02   .15695805E+02   .15203923E+02   .14652384E+02
+   .14047957E+02   .13397928E+02   .12709970E+02   .11992000E+02   .11252039E+02
+   .10498070E+02   .97379027E+01   .89790527E+01   .82286216E+01   .74931981E+01
+   .67787712E+01   .60906616E+01   .54334692E+01   .48110393E+01   .42264467E+01
+   .36819955E+01   .31792365E+01   .27189983E+01   .23014311E+01   .19260618E+01
+   .15918583E+01   .12972993E+01   .10404493E+01   .81903589E+00   .63052672E+00
+   .47220493E+00   .34124110E+00   .23476029E+00   .14990293E+00   .83878565E-01
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+  -.15165109E-02   .15418954E-02   .37583729E-02   .52234553E-02   .60463403E-02
+   .63444334E-02   .62349887E-02   .58287507E-02   .52254374E-02   .45108691E-02
+   .37555125E-02   .30142006E-02   .23267784E-02   .17194394E-02   .12065275E-02
+   .79260455E-03   .47461243E-03   .24398580E-03   .88606522E-04  -.54803893E-05
+ Reciprocal Space Part
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+  -.32199425E+01  -.33596863E+01  -.32437372E+01  -.28449779E+01  -.21427893E+01
+  -.11235349E+01   .21910978E+00   .18839910E+01   .38624748E+01   .61386104E+01
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+   .24342585E+02   .27744237E+02   .31119566E+02   .34416348E+02   .37583151E+02
+   .40570366E+02   .43331197E+02   .45822568E+02   .48005954E+02   .49848094E+02
+   .51321591E+02   .52405380E+02   .53085050E+02   .53353033E+02   .53208641E+02
+   .52657958E+02   .51713607E+02   .50394370E+02   .48724708E+02   .46734162E+02
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+   .30162758E+02   .27023048E+02   .23889743E+02   .20802833E+02   .17799600E+02
+   .14914036E+02   .12176355E+02   .96126055E+01   .72443863E+01   .50886642E+01
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+   .93747368E+00   .82813501E+00   .69977333E+00   .55900714E+00   .41218506E+00
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+  -.31214272E+00  -.37536384E+00  -.41817583E+00  -.44089029E+00  -.44450187E+00
+ Real Space Part
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+   .12555874E+03   .14804753E+03   .16915655E+03   .18869754E+03   .20650067E+03
+   .22241657E+03   .23631817E+03   .24810224E+03   .25769060E+03   .26503112E+03
+   .27009826E+03   .27289331E+03   .27344430E+03   .27180542E+03   .26805612E+03
+   .26229988E+03   .25466251E+03   .24529016E+03   .23434703E+03   .22201274E+03
+   .20847949E+03   .19394903E+03   .17862948E+03   .16273206E+03   .14646782E+03
+   .13004436E+03   .11366275E+03   .97514541E+02   .81779007E+02   .66620708E+02
+   .52187346E+02   .38608004E+02   .25991781E+02   .14426842E+02   .39799125E+01
+  -.53038085E+01  -.13400300E+02  -.20305974E+02  -.26036550E+02  -.30625599E+02
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+   .14286600E+01   .12946585E+01   .11280262E+01   .94353671E+00   .75361867E+00
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+  -.10406658E+00  -.78596797E-01  -.55856123E-01  -.36516393E-01  -.20896302E-01
+ PAW radial sets
+ 323 1.04059493489918520
+(5E20.12)                                
+ augmentation charges (non sperical)
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+   .601327217851E-03
+ uccopancies in atom
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+   .333333333668E+00   .000000000000E+00   .000000000000E+00   .000000000000E+00   .000000000000E+00
+   .000000000000E+00
+ grid
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+  -.220380384758E+02  -.217680844180E+02  -.215405378949E+02
+ core charge-density (pseudized)
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+   .567996024910E-01   .439743758259E-01   .337360022701E-01
+ pseudo wavefunction
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+   .904887507411E+00   .915218814120E+00   .922553366029E+00
+ ae wavefunction
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+ pseudo wavefunction
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+ ae wavefunction
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+ End of Dataset
diff --git a/notebooks/Al-dos/vasprun.xml.gz b/notebooks/Al-dos/vasprun.xml.gz
new file mode 100644
index 0000000000000000000000000000000000000000..a2ce3be4af79baab9672d79eb56afe5ffea61c6e
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diff --git a/notebooks/Al-relax.cif b/notebooks/Al-relax.cif
new file mode 100644
index 0000000..163e0d5
--- /dev/null
+++ b/notebooks/Al-relax.cif
@@ -0,0 +1,27 @@
+# generated using pymatgen
+data_Al
+_symmetry_space_group_name_H-M   'P 1'
+_cell_length_a   2.85749640
+_cell_length_b   2.85749640
+_cell_length_c   2.85749640
+_cell_angle_alpha   60.00000000
+_cell_angle_beta   60.00000000
+_cell_angle_gamma   60.00000000
+_symmetry_Int_Tables_number   1
+_chemical_formula_structural   Al
+_chemical_formula_sum   Al1
+_cell_volume   16.49840943
+_cell_formula_units_Z   1
+loop_
+ _symmetry_equiv_pos_site_id
+ _symmetry_equiv_pos_as_xyz
+  1  'x, y, z'
+loop_
+ _atom_site_type_symbol
+ _atom_site_label
+ _atom_site_symmetry_multiplicity
+ _atom_site_fract_x
+ _atom_site_fract_y
+ _atom_site_fract_z
+ _atom_site_occupancy
+  Al  Al0  1  0.00000000  0.00000000  0.00000000  1
diff --git a/notebooks/Si-relax/INCAR b/notebooks/Al-relax/INCAR
similarity index 85%
rename from notebooks/Si-relax/INCAR
rename to notebooks/Al-relax/INCAR
index 94c87d3..31b6ed2 100644
--- a/notebooks/Si-relax/INCAR
+++ b/notebooks/Al-relax/INCAR
@@ -1,5 +1,5 @@
 ALGO = Fast
-EDIFF = 0.0001
+EDIFF = 5e-05
 ENCUT = 520
 IBRION = 2
 ISIF = 3
@@ -9,7 +9,7 @@ LASPH = True
 LORBIT = 11
 LREAL = Auto
 LWAVE = False
-MAGMOM = 2*0.6
+MAGMOM = 1*0.6
 NELM = 100
 NELMIN = 5
 NSW = 99
diff --git a/notebooks/Al-relax/KPOINTS b/notebooks/Al-relax/KPOINTS
new file mode 100644
index 0000000..ac32634
--- /dev/null
+++ b/notebooks/Al-relax/KPOINTS
@@ -0,0 +1,4 @@
+pymatgen with grid density = 962 / number of atoms
+0
+Gamma
+9 9 9
diff --git a/notebooks/Al-relax/OUTCAR b/notebooks/Al-relax/OUTCAR
new file mode 100644
index 0000000..831bddd
--- /dev/null
+++ b/notebooks/Al-relax/OUTCAR
@@ -0,0 +1,6202 @@
+ vasp.5.2.2 15Apr09 complex 
+ executed on              unknown date 2014.10.30  16:25:45
+ running on   32 nodes
+ distr:  one band on   16 nodes,    2 groups
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+ INCAR:
+ POTCAR:   PAW_PBE Al 04Jan2001                   
+ POTCAR:   PAW_PBE Al 04Jan2001                   
+   VRHFIN =Al: s2p1                                                             
+   LEXCH  = PE                                                                  
+   EATOM  =    53.5387 eV,    3.9350 Ry                                         
+                                                                                
+   TITEL  = PAW_PBE Al 04Jan2001                                                
+   LULTRA =        F    use ultrasoft PP ?                                      
+   IUNSCR =        1    unscreen: 0-lin 1-nonlin 2-no                           
+   RPACOR =    1.500    partial core radius                                     
+   POMASS =   26.982; ZVAL   =    3.000    mass and valenz                      
+   RCORE  =    1.900    outmost cutoff radius                                   
+   RWIGS  =    2.650; RWIGS  =    1.402    wigner-seitz radius (au A)           
+   ENMAX  =  240.300; ENMIN  =  180.225 eV                                      
+   ICORE  =        2    local potential                                         
+   LCOR   =        T    correct aug charges                                     
+   LPAW   =        T    paw PP                                                  
+   EAUG   =  291.052                                                            
+   DEXC   =    -.041                                                            
+   RMAX   =    2.974    core radius for proj-oper                               
+   RAUG   =    1.300    factor for augmentation sphere                          
+   RDEP   =    1.966    radius for radial grids                                 
+   QCUT   =   -4.203; QGAM   =    8.405    optimization parameters              
+                                                                                
+   Description                                                                  
+     l     E      TYP  RCUT    TYP  RCUT                                        
+     0   .000     23  1.900                                                     
+     0   .000     23  1.900                                                     
+     1   .000     23  1.900                                                     
+     1  1.000     23  1.900                                                     
+     2   .000      7  1.900                                                     
+  local pseudopotential read in
+  partial core-charges read in
+  atomic valenz-charges read in
+  non local Contribution for L=            0  read in
+    real space projection operators read in
+  non local Contribution for L=            0  read in
+    real space projection operators read in
+  non local Contribution for L=            1  read in
+    real space projection operators read in
+  non local Contribution for L=            1  read in
+    real space projection operators read in
+    PAW grid and wavefunctions read in
+ 
+   number of l-projection  operators is LMAX  =            4
+   number of lm-projection operators is LMMAX =            8
+ 
+ PAW_PBE Al 04Jan2001                   :
+ energy of atom  1       EATOM=  -53.5387
+ kinetic energy error for atom=    0.0002 (will be added to EATOM!!)
+ 
+ 
+ POSCAR: Al1                                     
+  positions in direct lattice
+  No initial velocities read in
+ exchange correlation table for  LEXCH =        8
+   RHO(1)=    0.500       N(1)  =     2000
+   RHO(2)=  100.500       N(2)  =     4000
+
+ VTST: version 2.03d, (02/18/09)
+
+ CHAIN: initializing optimizer
+ 
+ OPT: Using VASP Dynamics algorithm
+ CHAIN: Read ICHAIN             0
+ 
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+ ion  position               nearest neighbor table
+   1  0.000  0.000  0.000-
+ 
+  LATTYP: Found a face centered cubic cell.
+ ALAT       =     4.0326380000
+  
+  Lattice vectors:
+  
+ A1 = (   0.0000000000,   2.0163190000,   2.0163190000)
+ A2 = (   2.0163190000,   0.0000000000,   2.0163190000)
+ A3 = (   2.0163190000,   2.0163190000,   0.0000000000)
+ Subroutine PRICEL returns:
+ Original cell was already a primitive cell.
+ 
+
+Analysis of symmetry for initial positions (statically):
+
+ Routine SETGRP: Setting up the symmetry group for a 
+ face centered cubic supercell.
+
+
+ Subroutine GETGRP returns: Found 48 space group operations
+ (whereof 48 operations were pure point group operations)
+ out of a pool of 48 trial point group operations.
+
+
+The static configuration has the point symmetry O_h .
+
+Analysis of symmetry for dynamics (positions and initial velocities):
+
+ Subroutine DYNSYM returns: Found 48 space group operations
+ (whereof 48 operations were pure point group operations)
+ out of a pool of 48 trial space group operations
+ (whereof 48 operations were pure point group operations)
+ and found also     1 'primitive' translations
+
+
+The dynamic configuration has the point symmetry O_h .
+
+Analysis of magnetic symmetry:
+
+ Subroutine MAGSYM returns: Found 48 space group operations
+ (whereof 48 operations were pure point group operations)
+ out of a pool of 48 trial space group operations
+ (whereof 48 operations were pure point group operations)
+ and found also     1 'primitive' translations
+
+
+The magnetic configuration has the point symmetry O_h .
+ 
+ 
+ KPOINTS: Automatic kpoint scheme                 
+
+Automatic generation of k-mesh.
+ 
+ Subroutine IBZKPT returns following result:
+ ===========================================
+ 
+ Found    220 irreducible k-points:
+ 
+ Following reciprocal coordinates:
+            Coordinates               Weight
+  0.000000  0.000000  0.000000      1.000000
+  0.052632  0.000000  0.000000      8.000000
+  0.105263  0.000000  0.000000      8.000000
+  0.157895  0.000000  0.000000      8.000000
+  0.210526  0.000000  0.000000      8.000000
+  0.263158  0.000000  0.000000      8.000000
+  0.315789  0.000000  0.000000      8.000000
+  0.368421  0.000000  0.000000      8.000000
+  0.421053  0.000000  0.000000      8.000000
+  0.473684  0.000000  0.000000      8.000000
+  0.052632  0.052632  0.000000      6.000000
+  0.105263  0.052632  0.000000     24.000000
+  0.157895  0.052632  0.000000     24.000000
+  0.210526  0.052632  0.000000     24.000000
+  0.263158  0.052632  0.000000     24.000000
+  0.315789  0.052632  0.000000     24.000000
+  0.368421  0.052632  0.000000     24.000000
+  0.421053  0.052632  0.000000     24.000000
+  0.473684  0.052632  0.000000     24.000000
+ -0.473684  0.052632  0.000000     24.000000
+ -0.421053  0.052632  0.000000     24.000000
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+ -0.157895  0.052632  0.000000     24.000000
+ -0.105263  0.052632  0.000000     24.000000
+ -0.052632  0.052632  0.000000     12.000000
+  0.105263  0.105263  0.000000      6.000000
+  0.157895  0.105263  0.000000     24.000000
+  0.210526  0.105263  0.000000     24.000000
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+ -0.105263  0.105263  0.000000     12.000000
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+  0.263158  0.157895  0.000000     24.000000
+  0.315789  0.157895  0.000000     24.000000
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+ -0.315789  0.157895  0.000000     24.000000
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+  0.263158  0.157895  0.052632     48.000000
+  0.315789  0.157895  0.052632     48.000000
+  0.368421  0.157895  0.052632     48.000000
+  0.421053  0.157895  0.052632     48.000000
+  0.473684  0.157895  0.052632     48.000000
+ -0.473684  0.157895  0.052632     48.000000
+ -0.421053  0.157895  0.052632     48.000000
+ -0.368421  0.157895  0.052632     48.000000
+ -0.315789  0.157895  0.052632     48.000000
+ -0.263158  0.157895  0.052632     48.000000
+ -0.210526  0.157895  0.052632     48.000000
+ -0.157895  0.157895  0.052632     48.000000
+ -0.105263  0.157895  0.052632     24.000000
+  0.263158  0.210526  0.052632     24.000000
+  0.315789  0.210526  0.052632     48.000000
+  0.368421  0.210526  0.052632     48.000000
+  0.421053  0.210526  0.052632     48.000000
+  0.473684  0.210526  0.052632     48.000000
+ -0.473684  0.210526  0.052632     48.000000
+ -0.421053  0.210526  0.052632     48.000000
+ -0.368421  0.210526  0.052632     48.000000
+ -0.315789  0.210526  0.052632     48.000000
+ -0.263158  0.210526  0.052632     48.000000
+ -0.210526  0.210526  0.052632     48.000000
+ -0.157895  0.210526  0.052632     24.000000
+  0.315789  0.263158  0.052632     24.000000
+  0.368421  0.263158  0.052632     48.000000
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+ -0.473684  0.263158  0.052632     48.000000
+ -0.421053  0.263158  0.052632     48.000000
+ -0.368421  0.263158  0.052632     48.000000
+ -0.315789  0.263158  0.052632     48.000000
+ -0.263158  0.263158  0.052632     48.000000
+ -0.210526  0.263158  0.052632     24.000000
+  0.368421  0.315789  0.052632     24.000000
+  0.421053  0.315789  0.052632     48.000000
+  0.473684  0.315789  0.052632     48.000000
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+ -0.421053  0.315789  0.052632     48.000000
+ -0.368421  0.315789  0.052632     48.000000
+ -0.315789  0.315789  0.052632     48.000000
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+ -0.421053  0.368421  0.052632     48.000000
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+ -0.421053  0.473684  0.052632     24.000000
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+  0.421053  0.210526  0.105263     48.000000
+  0.473684  0.210526  0.105263     48.000000
+ -0.473684  0.210526  0.105263     48.000000
+ -0.421053  0.210526  0.105263     48.000000
+  0.368421  0.263158  0.105263     24.000000
+  0.421053  0.263158  0.105263     48.000000
+  0.473684  0.263158  0.105263     48.000000
+ -0.473684  0.263158  0.105263     48.000000
+ -0.421053  0.263158  0.105263     48.000000
+ -0.368421  0.263158  0.105263     48.000000
+ -0.315789  0.263158  0.105263     48.000000
+ -0.263158  0.263158  0.105263     48.000000
+ -0.210526  0.263158  0.105263     48.000000
+ -0.157895  0.263158  0.105263     24.000000
+  0.421053  0.315789  0.105263     24.000000
+  0.473684  0.315789  0.105263     48.000000
+ -0.473684  0.315789  0.105263     48.000000
+ -0.421053  0.315789  0.105263     48.000000
+ -0.368421  0.315789  0.105263     48.000000
+ -0.315789  0.315789  0.105263     48.000000
+ -0.263158  0.315789  0.105263     48.000000
+ -0.210526  0.315789  0.105263     24.000000
+  0.473684  0.368421  0.105263     24.000000
+ -0.473684  0.368421  0.105263     48.000000
+ -0.421053  0.368421  0.105263     48.000000
+ -0.368421  0.368421  0.105263     48.000000
+ -0.315789  0.368421  0.105263     48.000000
+ -0.263158  0.368421  0.105263     24.000000
+ -0.473684  0.421053  0.105263     24.000000
+ -0.421053  0.421053  0.105263     48.000000
+ -0.368421  0.421053  0.105263     48.000000
+ -0.315789  0.421053  0.105263     24.000000
+ -0.421053  0.473684  0.105263     24.000000
+ -0.368421  0.473684  0.105263     24.000000
+  0.473684  0.315789  0.157895     24.000000
+ -0.473684  0.315789  0.157895     48.000000
+ -0.421053  0.315789  0.157895     48.000000
+ -0.368421  0.315789  0.157895     48.000000
+ -0.473684  0.368421  0.157895     24.000000
+ -0.421053  0.368421  0.157895     48.000000
+ -0.368421  0.368421  0.157895     48.000000
+ -0.315789  0.368421  0.157895     48.000000
+ -0.263158  0.368421  0.157895     48.000000
+ -0.210526  0.368421  0.157895     24.000000
+ -0.421053  0.421053  0.157895     24.000000
+ -0.368421  0.421053  0.157895     48.000000
+ -0.315789  0.421053  0.157895     48.000000
+ -0.263158  0.421053  0.157895     24.000000
+ -0.368421  0.473684  0.157895     24.000000
+ -0.315789  0.473684  0.157895     24.000000
+ -0.368421  0.421053  0.210526     24.000000
+ -0.315789  0.421053  0.210526     48.000000
+ -0.315789  0.473684  0.210526     24.000000
+ -0.263158  0.473684  0.210526     24.000000
+ 
+ Following cartesian coordinates:
+            Coordinates               Weight
+  0.000000  0.000000  0.000000      1.000000
+ -0.013051  0.013051  0.013051      8.000000
+ -0.026103  0.026103  0.026103      8.000000
+ -0.039154  0.039154  0.039154      8.000000
+ -0.052206  0.052206  0.052206      8.000000
+ -0.065257  0.065257  0.065257      8.000000
+ -0.078308  0.078308  0.078308      8.000000
+ -0.091360  0.091360  0.091360      8.000000
+ -0.104411  0.104411  0.104411      8.000000
+ -0.117463  0.117463  0.117463      8.000000
+  0.000000  0.000000  0.026103      6.000000
+ -0.013051  0.013051  0.039154     24.000000
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+ -0.039154  0.039154  0.065257     24.000000
+ -0.052206  0.052206  0.078308     24.000000
+ -0.065257  0.065257  0.091360     24.000000
+ -0.078308  0.078308  0.104411     24.000000
+ -0.091360  0.091360  0.117463     24.000000
+ -0.104411  0.104411  0.130514     24.000000
+  0.130514 -0.130514 -0.104411     24.000000
+  0.117463 -0.117463 -0.091360     24.000000
+  0.104411 -0.104411 -0.078308     24.000000
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+  0.026103 -0.026103  0.000000     12.000000
+  0.000000  0.000000  0.052206      6.000000
+ -0.013051  0.013051  0.065257     24.000000
+ -0.026103  0.026103  0.078308     24.000000
+ -0.039154  0.039154  0.091360     24.000000
+ -0.052206  0.052206  0.104411     24.000000
+ -0.065257  0.065257  0.117463     24.000000
+ -0.078308  0.078308  0.130514     24.000000
+ -0.091360  0.091360  0.143565     24.000000
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+  0.130514 -0.130514 -0.078308     24.000000
+  0.117463 -0.117463 -0.065257     24.000000
+  0.104411 -0.104411 -0.052206     24.000000
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+  0.000000  0.000000  0.078308      6.000000
+ -0.013051  0.013051  0.091360     24.000000
+ -0.026103  0.026103  0.104411     24.000000
+ -0.039154  0.039154  0.117463     24.000000
+ -0.052206  0.052206  0.130514     24.000000
+ -0.065257  0.065257  0.143565     24.000000
+ -0.078308  0.078308  0.156617     24.000000
+  0.156617 -0.156617 -0.078308     24.000000
+  0.143565 -0.143565 -0.065257     24.000000
+  0.130514 -0.130514 -0.052206     24.000000
+  0.117463 -0.117463 -0.039154     24.000000
+  0.104411 -0.104411 -0.026103     24.000000
+  0.091360 -0.091360 -0.013051     24.000000
+  0.078308 -0.078308  0.000000     12.000000
+  0.000000  0.000000  0.104411      6.000000
+ -0.013051  0.013051  0.117463     24.000000
+ -0.026103  0.026103  0.130514     24.000000
+ -0.039154  0.039154  0.143565     24.000000
+ -0.052206  0.052206  0.156617     24.000000
+ -0.065257  0.065257  0.169668     24.000000
+  0.169668 -0.169668 -0.065257     24.000000
+  0.156617 -0.156617 -0.052206     24.000000
+  0.143565 -0.143565 -0.039154     24.000000
+  0.130514 -0.130514 -0.026103     24.000000
+  0.117463 -0.117463 -0.013051     24.000000
+  0.104411 -0.104411  0.000000     12.000000
+  0.000000  0.000000  0.130514      6.000000
+ -0.013051  0.013051  0.143565     24.000000
+ -0.026103  0.026103  0.156617     24.000000
+ -0.039154  0.039154  0.169668     24.000000
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+ -0.013051  0.013051  0.169668     24.000000
+ -0.026103  0.026103  0.182720     24.000000
+ -0.039154  0.039154  0.195771     24.000000
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+  0.000000  0.000000  0.182720      6.000000
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+  0.195771 -0.195771 -0.013051     24.000000
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+  0.000000  0.000000  0.208822      6.000000
+ -0.013051  0.013051  0.221874     24.000000
+  0.221874 -0.221874 -0.013051     24.000000
+  0.208822 -0.208822  0.000000     12.000000
+  0.000000  0.000000  0.234925      6.000000
+  0.234925 -0.234925  0.000000     12.000000
+  0.000000  0.026103  0.052206     24.000000
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+ -0.039154  0.065257  0.091360     48.000000
+ -0.052206  0.078308  0.104411     48.000000
+ -0.065257  0.091360  0.117463     48.000000
+ -0.078308  0.104411  0.130514     48.000000
+  0.156617 -0.130514 -0.104411     48.000000
+  0.000000  0.026103  0.078308     24.000000
+ -0.013051  0.039154  0.091360     48.000000
+ -0.026103  0.052206  0.104411     48.000000
+ -0.039154  0.065257  0.117463     48.000000
+ -0.052206  0.078308  0.130514     48.000000
+ -0.065257  0.091360  0.143565     48.000000
+  0.169668 -0.143565 -0.091360     48.000000
+  0.156617 -0.130514 -0.078308     48.000000
+  0.143565 -0.117463 -0.065257     48.000000
+  0.130514 -0.104411 -0.052206     48.000000
+  0.117463 -0.091360 -0.039154     48.000000
+  0.104411 -0.078308 -0.026103     48.000000
+  0.091360 -0.065257 -0.013051     48.000000
+  0.078308 -0.052206  0.000000     24.000000
+  0.000000  0.026103  0.104411     24.000000
+ -0.013051  0.039154  0.117463     48.000000
+ -0.026103  0.052206  0.130514     48.000000
+ -0.039154  0.065257  0.143565     48.000000
+ -0.052206  0.078308  0.156617     48.000000
+  0.182720 -0.156617 -0.078308     48.000000
+  0.169668 -0.143565 -0.065257     48.000000
+  0.156617 -0.130514 -0.052206     48.000000
+  0.143565 -0.117463 -0.039154     48.000000
+  0.130514 -0.104411 -0.026103     48.000000
+  0.117463 -0.091360 -0.013051     48.000000
+  0.104411 -0.078308  0.000000     24.000000
+  0.000000  0.026103  0.130514     24.000000
+ -0.013051  0.039154  0.143565     48.000000
+ -0.026103  0.052206  0.156617     48.000000
+ -0.039154  0.065257  0.169668     48.000000
+  0.195771 -0.169668 -0.065257     48.000000
+  0.182720 -0.156617 -0.052206     48.000000
+  0.169668 -0.143565 -0.039154     48.000000
+  0.156617 -0.130514 -0.026103     48.000000
+  0.143565 -0.117463 -0.013051     48.000000
+  0.130514 -0.104411  0.000000     24.000000
+  0.000000  0.026103  0.156617     24.000000
+ -0.013051  0.039154  0.169668     48.000000
+ -0.026103  0.052206  0.182720     48.000000
+  0.208822 -0.182720 -0.052206     48.000000
+  0.195771 -0.169668 -0.039154     48.000000
+  0.182720 -0.156617 -0.026103     48.000000
+  0.169668 -0.143565 -0.013051     48.000000
+  0.156617 -0.130514  0.000000     24.000000
+  0.000000  0.026103  0.182720     24.000000
+ -0.013051  0.039154  0.195771     48.000000
+  0.221874 -0.195771 -0.039154     48.000000
+  0.208822 -0.182720 -0.026103     48.000000
+  0.195771 -0.169668 -0.013051     48.000000
+  0.182720 -0.156617  0.000000     24.000000
+  0.000000  0.026103  0.208822     24.000000
+  0.234925 -0.208822 -0.026103     48.000000
+  0.221874 -0.195771 -0.013051     48.000000
+  0.208822 -0.182720  0.000000     24.000000
+  0.247977 -0.221874 -0.013051     24.000000
+  0.234925 -0.208822  0.000000     24.000000
+  0.000000  0.052206  0.104411     24.000000
+ -0.013051  0.065257  0.117463     48.000000
+ -0.026103  0.078308  0.130514     48.000000
+ -0.039154  0.091360  0.143565     48.000000
+  0.195771 -0.143565 -0.091360     48.000000
+  0.182720 -0.130514 -0.078308     48.000000
+  0.000000  0.052206  0.130514     24.000000
+ -0.013051  0.065257  0.143565     48.000000
+ -0.026103  0.078308  0.156617     48.000000
+  0.208822 -0.156617 -0.078308     48.000000
+  0.195771 -0.143565 -0.065257     48.000000
+  0.182720 -0.130514 -0.052206     48.000000
+  0.169668 -0.117463 -0.039154     48.000000
+  0.156617 -0.104411 -0.026103     48.000000
+  0.143565 -0.091360 -0.013051     48.000000
+  0.130514 -0.078308  0.000000     24.000000
+  0.000000  0.052206  0.156617     24.000000
+ -0.013051  0.065257  0.169668     48.000000
+  0.221874 -0.169668 -0.065257     48.000000
+  0.208822 -0.156617 -0.052206     48.000000
+  0.195771 -0.143565 -0.039154     48.000000
+  0.182720 -0.130514 -0.026103     48.000000
+  0.169668 -0.117463 -0.013051     48.000000
+  0.156617 -0.104411  0.000000     24.000000
+  0.000000  0.052206  0.182720     24.000000
+  0.234925 -0.182720 -0.052206     48.000000
+  0.221874 -0.169668 -0.039154     48.000000
+  0.208822 -0.156617 -0.026103     48.000000
+  0.195771 -0.143565 -0.013051     48.000000
+  0.182720 -0.130514  0.000000     24.000000
+  0.247977 -0.195771 -0.039154     24.000000
+  0.234925 -0.182720 -0.026103     48.000000
+  0.221874 -0.169668 -0.013051     48.000000
+  0.208822 -0.156617  0.000000     24.000000
+  0.247977 -0.195771 -0.013051     24.000000
+  0.234925 -0.182720  0.000000     24.000000
+  0.000000  0.078308  0.156617     24.000000
+  0.234925 -0.156617 -0.078308     48.000000
+  0.221874 -0.143565 -0.065257     48.000000
+  0.208822 -0.130514 -0.052206     48.000000
+  0.247977 -0.169668 -0.065257     24.000000
+  0.234925 -0.156617 -0.052206     48.000000
+  0.221874 -0.143565 -0.039154     48.000000
+  0.208822 -0.130514 -0.026103     48.000000
+  0.195771 -0.117463 -0.013051     48.000000
+  0.182720 -0.104411  0.000000     24.000000
+  0.247977 -0.169668 -0.039154     24.000000
+  0.234925 -0.156617 -0.026103     48.000000
+  0.221874 -0.143565 -0.013051     48.000000
+  0.208822 -0.130514  0.000000     24.000000
+  0.247977 -0.169668 -0.013051     24.000000
+  0.234925 -0.156617  0.000000     24.000000
+  0.247977 -0.143565 -0.039154     24.000000
+  0.234925 -0.130514 -0.026103     48.000000
+  0.247977 -0.143565 -0.013051     24.000000
+  0.234925 -0.130514  0.000000     24.000000
+ 
+ TETIRR: Found    955 inequivalent tetrahedra from    41154
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+
+
+ Dimension of arrays:
+   k-points           NKPTS =    220   k-points in BZ     NKDIM =    220   number of bands    NBANDS=      6
+   number of dos      NEDOS =    301   number of ions     NIONS =      1
+   non local maximal  LDIM  =      4   non local SUM 2l+1 LMDIM =      8
+   total plane-waves  NPLWV =  13824
+   max r-space proj   IRMAX =      1   max aug-charges    IRDMAX=  33012
+   dimension x,y,z NGX =    24 NGY =   24 NGZ =   24
+   dimension x,y,z NGXF=    48 NGYF=   48 NGZF=   48
+   support grid    NGXF=    48 NGYF=   48 NGZF=   48
+   ions per type =               1
+ NGX,Y,Z   is equivalent  to a cutoff of  13.99, 13.99, 13.99 a.u.
+ NGXF,Y,Z  is equivalent  to a cutoff of  27.98, 27.98, 27.98 a.u.
+
+
+ I would recommend the setting:
+   dimension x,y,z NGX =    21 NGY =   21 NGZ =   21
+ SYSTEM =  unknown system                          
+ POSCAR =  Al1                                     
+
+ Startparameter for this run:
+   NWRITE =      2    write-flag & timer
+   PREC   = accura    medium, high low
+   ISTART =      0    job   : 0-new  1-cont  2-samecut
+   ICHARG =      2    charge: 1-file 2-atom 10-const
+   ISPIN  =      2    spin polarized calculation?
+   LNONCOLLINEAR =      F non collinear calculations
+   LSORBIT =      F    spin-orbit coupling
+   INIWAV =      1    electr: 0-lowe 1-rand  2-diag
+   LASPH  =      F    aspherical Exc in radial PAW
+   METAGGA=      F    non-selfconsistent MetaGGA calc.
+
+ Electronic Relaxation 1
+   ENCUT  =  520.0 eV  38.22 Ry    6.18 a.u.   5.30  5.30  5.30*2*pi/ulx,y,z
+   ENINI  =  520.0     initial cutoff
+   ENAUG  =  291.1 eV  augmentation charge cutoff
+   NELM   =    100;   NELMIN=  2; NELMDL=  0     # of ELM steps 
+   EDIFF  = 0.1E-05   stopping-criterion for ELM
+   LREAL  =      F    real-space projection
+   LCOMPAT=      F    compatible to vasp.4.4
+   LREAL_COMPAT= F    compatible to vasp.4.5.1-3
+   GGA_COMPAT  = T    GGA compatible to vasp.4.4-vasp.4.6
+   LMAXPAW     = -100 max onsite density
+   LMAXMIX     =    2 max onsite mixed and CHGCAR
+   VOSKOWN=      0    Vosko Wilk Nusair interpolation
+   ROPT   =    0.00000
+ Ionic relaxation
+   EDIFFG = 0.1E-04   stopping-criterion for IOM
+   NSW    =      0    number of steps for IOM
+   NBLOCK =      1;   KBLOCK =      1    inner block; outer block 
+   IBRION =     -1    ionic relax: 0-MD 1-quasi-New 2-CG
+   NFREE  =      0    steps in history (QN), initial steepest desc. (CG)
+   ISIF   =      3    stress and relaxation
+   IWAVPR =     10    prediction:  0-non 1-charg 2-wave 3-comb
+   ISYM   =      2    0-nonsym 1-usesym 2-fastsym
+   LCORR  =      T    Harris-Foulkes like correction to forces
+
+   POTIM  = 0.5000    time-step for ionic-motion
+   TEIN   =    0.0    initial temperature
+   TEBEG  =    0.0;   TEEND  =   0.0 temperature during run
+   SMASS  =  -3.00    Nose mass-parameter (am)
+   estimated Nose-frequenzy (Omega)   =  0.10E-29 period in steps =****** mass=  -0.186E-27a.u.
+   NPACO  =    256;   APACO  = 16.0  distance and # of slots for P.C.
+   PSTRESS=    0.0 pullay stress
+
+  Mass of Ions in am
+   POMASS =  26.98
+  Ionic Valenz
+   ZVAL   =   3.00
+  Atomic Wigner-Seitz radii
+   RWIGS  =  -1.00
+   NELECT =       3.0000    total number of electrons
+   NUPDOWN=      -1.0000    fix difference up-down
+
+ DOS related values:
+   EMIN   =  10.00;   EMAX   =-10.00  energy-range for DOS
+   EFERMI =   0.00
+   ISMEAR =    -5;   SIGMA  =   0.20  broadening in eV -4-tet -1-fermi 0-gaus
+
+ Electronic relaxation 2 (details)
+   IALGO  =     38    algorithm
+   LDIAG  =      T    sub-space diagonalisation
+   IMIX   =      4    mixing-type and parameters
+     AMIX     =   0.40;   BMIX     =  1.00
+     AMIX_MAG =   1.60;   BMIX_MAG =  1.00
+     AMIN     =   0.10
+     WC   =   100.;   INIMIX=   1;  MIXPRE=   1
+
+ Intra band minimization:
+   WEIMIN = 0.0000     energy-eigenvalue tresh-hold
+   EBREAK =  0.50E-07  absolut break condition
+   DEPER  =   0.30     relativ break condition  
+
+   TIME   =   0.40     timestep for ELM
+
+  volume/ion in A,a.u.               =      16.39       110.64
+  Fermi-wavevector in a.u.,A,eV,Ry     =   0.929421  1.756352 11.753041  0.863824
+  Thomas-Fermi vector in A             =   2.055702
+ 
+ Write flags
+   LWAVE  =      F    write WAVECAR
+   LCHARG =      T    write CHGCAR
+   LVTOT  =      F    write LOCPOT, local potential
+   LELF   =      F    write electronic localiz. function (ELF)
+   LORBIT =     11    0 simple, 1 ext, 2 COOP (PROOUT)
+
+
+ Dipole corrections
+   LMONO  =      F    monopole corrections only (constant potential shift)
+   LDIPOL =      F    correct potential (dipole corrections)
+   IDIPOL =      0    1-x, 2-y, 3-z, 4-all directions 
+   EPSILON=  1.0000000 bulk dielectric constant
+
+ Exchange correlation treatment:
+   GGA     =    --    GGA type
+   LEXCH   =     8    internal setting for exchange type
+   VOSKOWN=      0    Vosko Wilk Nusair interpolation
+   LHFCALC =     F    Hartree Fock is set to
+   LHFONE  =     F    Hartree Fock one center treatment
+   AEXX    =    0.0000 exact exchange contribution
+
+ Linear response parameters
+   LEPSILON=     F    determine dielectric tensor
+   LRPA    =     F    only Hartree local field effects (RPA)
+   LNABLA  =     F    use nabla operator in PAW spheres
+   LVEL    =     F    velocity operator in full k-point grid
+   LINTERFAST=   F  fast interpolation
+   KINTER  =     0    interpolate to denser k-point grid
+   CSHIFT  =0.1000    complex shift for real part using Kramers Kronig
+   OMEGAMAX=  -1.0    maximum frequency
+
+ Orbital magnetization related:
+   ORBITALMAG=     F  switch on orbital magnetization
+   LCHIMAG   =     F  perturbation theory with respect to B field
+
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+ Static calculation
+ charge density and potential will be updated during run
+ spin polarized calculation
+ Variant of blocked Davidson
+ Davidson routine will perform the subspace rotation
+ perform sub-space diagonalisation
+    after iterative eigenvector-optimisation
+ modified Broyden-mixing scheme, WC =      100.0
+ initial mixing is a Kerker type mixing with AMIX =  0.4000 and BMIX =      1.0000
+ Hartree-type preconditioning will be used
+ using additional bands             4
+ reciprocal scheme for non local part
+ use partial core corrections
+ calculate Harris-corrections to forces 
+   (improved forces if not selfconsistent)
+ use gradient corrections 
+ use of overlap-Matrix (Vanderbilt PP)
+ Fermi weights with tetrahedron method with Bloechl corrections
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+  energy-cutoff  :      520.00
+  volume of cell :       16.39
+      direct lattice vectors                 reciprocal lattice vectors
+     0.000000000  2.016319000  2.016319000    -0.247976635  0.247976635  0.247976635
+     2.016319000  0.000000000  2.016319000     0.247976635 -0.247976635  0.247976635
+     2.016319000  2.016319000  0.000000000     0.247976635  0.247976635 -0.247976635
+
+  length of vectors
+     2.851505676  2.851505676  2.851505676     0.429508130  0.429508130  0.429508130
+
+
+ 
+ k-points in units of 2pi/SCALE and weight: Automatic kpoint scheme                 
+   0.00000000  0.00000000  0.00000000       0.000
+  -0.01305140  0.01305140  0.01305140       0.001
+  -0.02610280  0.02610280  0.02610280       0.001
+  -0.03915421  0.03915421  0.03915421       0.001
+  -0.05220561  0.05220561  0.05220561       0.001
+  -0.06525701  0.06525701  0.06525701       0.001
+  -0.07830841  0.07830841  0.07830841       0.001
+  -0.09135981  0.09135981  0.09135981       0.001
+  -0.10441121  0.10441121  0.10441121       0.001
+  -0.11746262  0.11746262  0.11746262       0.001
+   0.00000000  0.00000000  0.02610280       0.001
+  -0.01305140  0.01305140  0.03915421       0.003
+  -0.02610280  0.02610280  0.05220561       0.003
+  -0.03915421  0.03915421  0.06525701       0.003
+  -0.05220561  0.05220561  0.07830841       0.003
+  -0.06525701  0.06525701  0.09135981       0.003
+  -0.07830841  0.07830841  0.10441121       0.003
+  -0.09135981  0.09135981  0.11746262       0.003
+  -0.10441121  0.10441121  0.13051402       0.003
+   0.13051402 -0.13051402 -0.10441121       0.003
+   0.11746262 -0.11746262 -0.09135981       0.003
+   0.10441121 -0.10441121 -0.07830841       0.003
+   0.09135981 -0.09135981 -0.06525701       0.003
+   0.07830841 -0.07830841 -0.05220561       0.003
+   0.06525701 -0.06525701 -0.03915421       0.003
+   0.05220561 -0.05220561 -0.02610280       0.003
+   0.03915421 -0.03915421 -0.01305140       0.003
+   0.02610280 -0.02610280  0.00000000       0.002
+   0.00000000  0.00000000  0.05220561       0.001
+  -0.01305140  0.01305140  0.06525701       0.003
+  -0.02610280  0.02610280  0.07830841       0.003
+  -0.03915421  0.03915421  0.09135981       0.003
+  -0.05220561  0.05220561  0.10441121       0.003
+  -0.06525701  0.06525701  0.11746262       0.003
+  -0.07830841  0.07830841  0.13051402       0.003
+  -0.09135981  0.09135981  0.14356542       0.003
+   0.14356542 -0.14356542 -0.09135981       0.003
+   0.13051402 -0.13051402 -0.07830841       0.003
+   0.11746262 -0.11746262 -0.06525701       0.003
+   0.10441121 -0.10441121 -0.05220561       0.003
+   0.09135981 -0.09135981 -0.03915421       0.003
+   0.07830841 -0.07830841 -0.02610280       0.003
+   0.06525701 -0.06525701 -0.01305140       0.003
+   0.05220561 -0.05220561  0.00000000       0.002
+   0.00000000  0.00000000  0.07830841       0.001
+  -0.01305140  0.01305140  0.09135981       0.003
+  -0.02610280  0.02610280  0.10441121       0.003
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+  -0.05220561  0.05220561  0.13051402       0.003
+  -0.06525701  0.06525701  0.14356542       0.003
+  -0.07830841  0.07830841  0.15661682       0.003
+   0.15661682 -0.15661682 -0.07830841       0.003
+   0.14356542 -0.14356542 -0.06525701       0.003
+   0.13051402 -0.13051402 -0.05220561       0.003
+   0.11746262 -0.11746262 -0.03915421       0.003
+   0.10441121 -0.10441121 -0.02610280       0.003
+   0.09135981 -0.09135981 -0.01305140       0.003
+   0.07830841 -0.07830841  0.00000000       0.002
+   0.00000000  0.00000000  0.10441121       0.001
+  -0.01305140  0.01305140  0.11746262       0.003
+  -0.02610280  0.02610280  0.13051402       0.003
+  -0.03915421  0.03915421  0.14356542       0.003
+  -0.05220561  0.05220561  0.15661682       0.003
+  -0.06525701  0.06525701  0.16966822       0.003
+   0.16966822 -0.16966822 -0.06525701       0.003
+   0.15661682 -0.15661682 -0.05220561       0.003
+   0.14356542 -0.14356542 -0.03915421       0.003
+   0.13051402 -0.13051402 -0.02610280       0.003
+   0.11746262 -0.11746262 -0.01305140       0.003
+   0.10441121 -0.10441121  0.00000000       0.002
+   0.00000000  0.00000000  0.13051402       0.001
+  -0.01305140  0.01305140  0.14356542       0.003
+  -0.02610280  0.02610280  0.15661682       0.003
+  -0.03915421  0.03915421  0.16966822       0.003
+  -0.05220561  0.05220561  0.18271963       0.003
+   0.18271963 -0.18271963 -0.05220561       0.003
+   0.16966822 -0.16966822 -0.03915421       0.003
+   0.15661682 -0.15661682 -0.02610280       0.003
+   0.14356542 -0.14356542 -0.01305140       0.003
+   0.13051402 -0.13051402  0.00000000       0.002
+   0.00000000  0.00000000  0.15661682       0.001
+  -0.01305140  0.01305140  0.16966822       0.003
+  -0.02610280  0.02610280  0.18271963       0.003
+  -0.03915421  0.03915421  0.19577103       0.003
+   0.19577103 -0.19577103 -0.03915421       0.003
+   0.18271963 -0.18271963 -0.02610280       0.003
+   0.16966822 -0.16966822 -0.01305140       0.003
+   0.15661682 -0.15661682  0.00000000       0.002
+   0.00000000  0.00000000  0.18271963       0.001
+  -0.01305140  0.01305140  0.19577103       0.003
+  -0.02610280  0.02610280  0.20882243       0.003
+   0.20882243 -0.20882243 -0.02610280       0.003
+   0.19577103 -0.19577103 -0.01305140       0.003
+   0.18271963 -0.18271963  0.00000000       0.002
+   0.00000000  0.00000000  0.20882243       0.001
+  -0.01305140  0.01305140  0.22187383       0.003
+   0.22187383 -0.22187383 -0.01305140       0.003
+   0.20882243 -0.20882243  0.00000000       0.002
+   0.00000000  0.00000000  0.23492523       0.001
+   0.23492523 -0.23492523  0.00000000       0.002
+   0.00000000  0.02610280  0.05220561       0.003
+  -0.01305140  0.03915421  0.06525701       0.007
+  -0.02610280  0.05220561  0.07830841       0.007
+  -0.03915421  0.06525701  0.09135981       0.007
+  -0.05220561  0.07830841  0.10441121       0.007
+  -0.06525701  0.09135981  0.11746262       0.007
+  -0.07830841  0.10441121  0.13051402       0.007
+   0.15661682 -0.13051402 -0.10441121       0.007
+   0.00000000  0.02610280  0.07830841       0.003
+  -0.01305140  0.03915421  0.09135981       0.007
+  -0.02610280  0.05220561  0.10441121       0.007
+  -0.03915421  0.06525701  0.11746262       0.007
+  -0.05220561  0.07830841  0.13051402       0.007
+  -0.06525701  0.09135981  0.14356542       0.007
+   0.16966822 -0.14356542 -0.09135981       0.007
+   0.15661682 -0.13051402 -0.07830841       0.007
+   0.14356542 -0.11746262 -0.06525701       0.007
+   0.13051402 -0.10441121 -0.05220561       0.007
+   0.11746262 -0.09135981 -0.03915421       0.007
+   0.10441121 -0.07830841 -0.02610280       0.007
+   0.09135981 -0.06525701 -0.01305140       0.007
+   0.07830841 -0.05220561  0.00000000       0.003
+   0.00000000  0.02610280  0.10441121       0.003
+  -0.01305140  0.03915421  0.11746262       0.007
+  -0.02610280  0.05220561  0.13051402       0.007
+  -0.03915421  0.06525701  0.14356542       0.007
+  -0.05220561  0.07830841  0.15661682       0.007
+   0.18271963 -0.15661682 -0.07830841       0.007
+   0.16966822 -0.14356542 -0.06525701       0.007
+   0.15661682 -0.13051402 -0.05220561       0.007
+   0.14356542 -0.11746262 -0.03915421       0.007
+   0.13051402 -0.10441121 -0.02610280       0.007
+   0.11746262 -0.09135981 -0.01305140       0.007
+   0.10441121 -0.07830841  0.00000000       0.003
+   0.00000000  0.02610280  0.13051402       0.003
+  -0.01305140  0.03915421  0.14356542       0.007
+  -0.02610280  0.05220561  0.15661682       0.007
+  -0.03915421  0.06525701  0.16966822       0.007
+   0.19577103 -0.16966822 -0.06525701       0.007
+   0.18271963 -0.15661682 -0.05220561       0.007
+   0.16966822 -0.14356542 -0.03915421       0.007
+   0.15661682 -0.13051402 -0.02610280       0.007
+   0.14356542 -0.11746262 -0.01305140       0.007
+   0.13051402 -0.10441121  0.00000000       0.003
+   0.00000000  0.02610280  0.15661682       0.003
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+  -0.02610280  0.05220561  0.18271963       0.007
+   0.20882243 -0.18271963 -0.05220561       0.007
+   0.19577103 -0.16966822 -0.03915421       0.007
+   0.18271963 -0.15661682 -0.02610280       0.007
+   0.16966822 -0.14356542 -0.01305140       0.007
+   0.15661682 -0.13051402  0.00000000       0.003
+   0.00000000  0.02610280  0.18271963       0.003
+  -0.01305140  0.03915421  0.19577103       0.007
+   0.22187383 -0.19577103 -0.03915421       0.007
+   0.20882243 -0.18271963 -0.02610280       0.007
+   0.19577103 -0.16966822 -0.01305140       0.007
+   0.18271963 -0.15661682  0.00000000       0.003
+   0.00000000  0.02610280  0.20882243       0.003
+   0.23492523 -0.20882243 -0.02610280       0.007
+   0.22187383 -0.19577103 -0.01305140       0.007
+   0.20882243 -0.18271963  0.00000000       0.003
+   0.24797663 -0.22187383 -0.01305140       0.003
+   0.23492523 -0.20882243  0.00000000       0.003
+   0.00000000  0.05220561  0.10441121       0.003
+  -0.01305140  0.06525701  0.11746262       0.007
+  -0.02610280  0.07830841  0.13051402       0.007
+  -0.03915421  0.09135981  0.14356542       0.007
+   0.19577103 -0.14356542 -0.09135981       0.007
+   0.18271963 -0.13051402 -0.07830841       0.007
+   0.00000000  0.05220561  0.13051402       0.003
+  -0.01305140  0.06525701  0.14356542       0.007
+  -0.02610280  0.07830841  0.15661682       0.007
+   0.20882243 -0.15661682 -0.07830841       0.007
+   0.19577103 -0.14356542 -0.06525701       0.007
+   0.18271963 -0.13051402 -0.05220561       0.007
+   0.16966822 -0.11746262 -0.03915421       0.007
+   0.15661682 -0.10441121 -0.02610280       0.007
+   0.14356542 -0.09135981 -0.01305140       0.007
+   0.13051402 -0.07830841  0.00000000       0.003
+   0.00000000  0.05220561  0.15661682       0.003
+  -0.01305140  0.06525701  0.16966822       0.007
+   0.22187383 -0.16966822 -0.06525701       0.007
+   0.20882243 -0.15661682 -0.05220561       0.007
+   0.19577103 -0.14356542 -0.03915421       0.007
+   0.18271963 -0.13051402 -0.02610280       0.007
+   0.16966822 -0.11746262 -0.01305140       0.007
+   0.15661682 -0.10441121  0.00000000       0.003
+   0.00000000  0.05220561  0.18271963       0.003
+   0.23492523 -0.18271963 -0.05220561       0.007
+   0.22187383 -0.16966822 -0.03915421       0.007
+   0.20882243 -0.15661682 -0.02610280       0.007
+   0.19577103 -0.14356542 -0.01305140       0.007
+   0.18271963 -0.13051402  0.00000000       0.003
+   0.24797663 -0.19577103 -0.03915421       0.003
+   0.23492523 -0.18271963 -0.02610280       0.007
+   0.22187383 -0.16966822 -0.01305140       0.007
+   0.20882243 -0.15661682  0.00000000       0.003
+   0.24797663 -0.19577103 -0.01305140       0.003
+   0.23492523 -0.18271963  0.00000000       0.003
+   0.00000000  0.07830841  0.15661682       0.003
+   0.23492523 -0.15661682 -0.07830841       0.007
+   0.22187383 -0.14356542 -0.06525701       0.007
+   0.20882243 -0.13051402 -0.05220561       0.007
+   0.24797663 -0.16966822 -0.06525701       0.003
+   0.23492523 -0.15661682 -0.05220561       0.007
+   0.22187383 -0.14356542 -0.03915421       0.007
+   0.20882243 -0.13051402 -0.02610280       0.007
+   0.19577103 -0.11746262 -0.01305140       0.007
+   0.18271963 -0.10441121  0.00000000       0.003
+   0.24797663 -0.16966822 -0.03915421       0.003
+   0.23492523 -0.15661682 -0.02610280       0.007
+   0.22187383 -0.14356542 -0.01305140       0.007
+   0.20882243 -0.13051402  0.00000000       0.003
+   0.24797663 -0.16966822 -0.01305140       0.003
+   0.23492523 -0.15661682  0.00000000       0.003
+   0.24797663 -0.14356542 -0.03915421       0.003
+   0.23492523 -0.13051402 -0.02610280       0.007
+   0.24797663 -0.14356542 -0.01305140       0.003
+   0.23492523 -0.13051402  0.00000000       0.003
+ 
+ k-points in reciprocal lattice and weights: Automatic kpoint scheme                 
+   0.00000000  0.00000000  0.00000000       0.000
+   0.05263158  0.00000000  0.00000000       0.001
+   0.10526316  0.00000000  0.00000000       0.001
+   0.15789474  0.00000000  0.00000000       0.001
+   0.21052632  0.00000000  0.00000000       0.001
+   0.26315789  0.00000000  0.00000000       0.001
+   0.31578947  0.00000000  0.00000000       0.001
+   0.36842105  0.00000000  0.00000000       0.001
+   0.42105263  0.00000000  0.00000000       0.001
+   0.47368421  0.00000000  0.00000000       0.001
+   0.05263158  0.05263158  0.00000000       0.001
+   0.10526316  0.05263158  0.00000000       0.003
+   0.15789474  0.05263158  0.00000000       0.003
+   0.21052632  0.05263158  0.00000000       0.003
+   0.26315789  0.05263158  0.00000000       0.003
+   0.31578947  0.05263158  0.00000000       0.003
+   0.36842105  0.05263158  0.00000000       0.003
+   0.42105263  0.05263158  0.00000000       0.003
+   0.47368421  0.05263158  0.00000000       0.003
+  -0.47368421  0.05263158  0.00000000       0.003
+  -0.42105263  0.05263158  0.00000000       0.003
+  -0.36842105  0.05263158  0.00000000       0.003
+  -0.31578947  0.05263158  0.00000000       0.003
+  -0.26315789  0.05263158  0.00000000       0.003
+  -0.21052632  0.05263158  0.00000000       0.003
+  -0.15789474  0.05263158  0.00000000       0.003
+  -0.10526316  0.05263158  0.00000000       0.003
+  -0.05263158  0.05263158  0.00000000       0.002
+   0.10526316  0.10526316  0.00000000       0.001
+   0.15789474  0.10526316  0.00000000       0.003
+   0.21052632  0.10526316  0.00000000       0.003
+   0.26315789  0.10526316  0.00000000       0.003
+   0.31578947  0.10526316  0.00000000       0.003
+   0.36842105  0.10526316  0.00000000       0.003
+   0.42105263  0.10526316  0.00000000       0.003
+   0.47368421  0.10526316  0.00000000       0.003
+  -0.47368421  0.10526316  0.00000000       0.003
+  -0.42105263  0.10526316  0.00000000       0.003
+  -0.36842105  0.10526316  0.00000000       0.003
+  -0.31578947  0.10526316  0.00000000       0.003
+  -0.26315789  0.10526316  0.00000000       0.003
+  -0.21052632  0.10526316  0.00000000       0.003
+  -0.15789474  0.10526316  0.00000000       0.003
+  -0.10526316  0.10526316  0.00000000       0.002
+   0.15789474  0.15789474  0.00000000       0.001
+   0.21052632  0.15789474  0.00000000       0.003
+   0.26315789  0.15789474  0.00000000       0.003
+   0.31578947  0.15789474  0.00000000       0.003
+   0.36842105  0.15789474  0.00000000       0.003
+   0.42105263  0.15789474  0.00000000       0.003
+   0.47368421  0.15789474  0.00000000       0.003
+  -0.47368421  0.15789474  0.00000000       0.003
+  -0.42105263  0.15789474  0.00000000       0.003
+  -0.36842105  0.15789474  0.00000000       0.003
+  -0.31578947  0.15789474  0.00000000       0.003
+  -0.26315789  0.15789474  0.00000000       0.003
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+ k-point ** :  -.47370.42110.0526  plane waves:     447
+ k-point ** :  -.42110.42110.0526  plane waves:     443
+ k-point ** :  -.36840.42110.0526  plane waves:     437
+ k-point ** :  -.47370.47370.0526  plane waves:     448
+ k-point ** :  -.42110.47370.0526  plane waves:     450
+ k-point ** :  0.31580.21050.1053  plane waves:     441
+ k-point ** :  0.36840.21050.1053  plane waves:     444
+ k-point ** :  0.42110.21050.1053  plane waves:     440
+ k-point ** :  0.47370.21050.1053  plane waves:     438
+ k-point ** :  -.47370.21050.1053  plane waves:     438
+ k-point ** :  -.42110.21050.1053  plane waves:     440
+ k-point ** :  0.36840.26320.1053  plane waves:     445
+ k-point ** :  0.42110.26320.1053  plane waves:     444
+ k-point ** :  0.47370.26320.1053  plane waves:     440
+ k-point ** :  -.47370.26320.1053  plane waves:     442
+ k-point ** :  -.42110.26320.1053  plane waves:     441
+ k-point ** :  -.36840.26320.1053  plane waves:     436
+ k-point ** :  -.31580.26320.1053  plane waves:     435
+ k-point ** :  -.26320.26320.1053  plane waves:     437
+ k-point ** :  -.21050.26320.1053  plane waves:     437
+ k-point ** :  -.15790.26320.1053  plane waves:     444
+ k-point ** :  0.42110.31580.1053  plane waves:     443
+ k-point ** :  0.47370.31580.1053  plane waves:     441
+ k-point ** :  -.47370.31580.1053  plane waves:     441
+ k-point ** :  -.42110.31580.1053  plane waves:     438
+ k-point ** :  -.36840.31580.1053  plane waves:     438
+ k-point ** :  -.31580.31580.1053  plane waves:     436
+ k-point ** :  -.26320.31580.1053  plane waves:     433
+ k-point ** :  -.21050.31580.1053  plane waves:     437
+ k-point ** :  0.47370.36840.1053  plane waves:     446
+ k-point ** :  -.47370.36840.1053  plane waves:     438
+ k-point ** :  -.42110.36840.1053  plane waves:     439
+ k-point ** :  -.36840.36840.1053  plane waves:     441
+ k-point ** :  -.31580.36840.1053  plane waves:     441
+ k-point ** :  -.26320.36840.1053  plane waves:     438
+ k-point ** :  -.47370.42110.1053  plane waves:     444
+ k-point ** :  -.42110.42110.1053  plane waves:     441
+ k-point ** :  -.36840.42110.1053  plane waves:     442
+ k-point ** :  -.31580.42110.1053  plane waves:     439
+ k-point ** :  -.42110.47370.1053  plane waves:     446
+ k-point ** :  -.36840.47370.1053  plane waves:     445
+ k-point ** :  0.47370.31580.1579  plane waves:     435
+ k-point ** :  -.47370.31580.1579  plane waves:     442
+ k-point ** :  -.42110.31580.1579  plane waves:     439
+ k-point ** :  -.36840.31580.1579  plane waves:     436
+ k-point ** :  -.47370.36840.1579  plane waves:     438
+ k-point ** :  -.42110.36840.1579  plane waves:     441
+ k-point ** :  -.36840.36840.1579  plane waves:     438
+ k-point ** :  -.31580.36840.1579  plane waves:     440
+ k-point ** :  -.26320.36840.1579  plane waves:     439
+ k-point ** :  -.21050.36840.1579  plane waves:     440
+ k-point ** :  -.42110.42110.1579  plane waves:     440
+ k-point ** :  -.36840.42110.1579  plane waves:     439
+ k-point ** :  -.31580.42110.1579  plane waves:     439
+ k-point ** :  -.26320.42110.1579  plane waves:     442
+ k-point ** :  -.36840.47370.1579  plane waves:     440
+ k-point ** :  -.31580.47370.1579  plane waves:     439
+ k-point ** :  -.36840.42110.2105  plane waves:     442
+ k-point ** :  -.31580.42110.2105  plane waves:     442
+ k-point ** :  -.31580.47370.2105  plane waves:     441
+ k-point ** :  -.26320.47370.2105  plane waves:     444
+
+ maximum and minimum number of plane-waves per node :      35     21
+
+ maximum number of plane-waves:     459
+ maximal index in each direction: 
+   IXMAX=  5   IYMAX=  5   IZMAX=  5
+   IXMIN= -5   IYMIN= -5   IZMIN= -5
+
+ NGX is ok and might be reduce to  22
+ NGY is ok and might be reduce to  22
+ NGZ is ok and might be reduce to  22
+
+ parallel 3D FFT for wavefunctions:
+    minimum data exchange during FFTs selected (reduces bandwidth)
+ parallel 3D FFT for charge:
+    minimum data exchange during FFTs selected (reduces bandwidth)
+
+
+ total amount of memory used by VASP on root node  33617. kBytes
+========================================================================
+
+   base      :    30000. kBytes
+   nonl-proj :      451. kBytes
+   fftplans  :      185. kBytes
+   grid      :     2131. kBytes
+   one-center:        6. kBytes
+   wavefun   :      844. kBytes
+ 
+ Broyden mixing: mesh for mixing (old mesh)
+   NGX = 11   NGY = 11   NGZ = 11
+  (NGX  = 48   NGY  = 48   NGZ  = 48)
+  gives a total of   1331 points
+
+ initial charge density was supplied:
+ charge density of overlapping atoms calculated
+ number of electron    3.0000000 magnetization    0.6000000
+ keeping initial charge density in first step
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+ Maximum index for augmentation-charges          1603 (set IRDMAX)
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+ First call to EWALD:  gamma=   0.698
+ Maximum number of real-space cells 3x 3x 3
+ Maximum number of reciprocal cells 3x 3x 3
+
+    FEWALD:  cpu time    0.00: real time    0.00
+   RESPFUN:  cpu time    0.00: real time    0.00
+
+
+----------------------------------------- Iteration    1(   1)  ---------------------------------------
+
+
+    POTLOK:  cpu time    0.19: real time    0.22
+    SETDIJ:  cpu time    0.01: real time    0.02
+     EDDAV:  cpu time    3.31: real time    3.39
+ BZINTS: Fermi energy:  9.578122;  3.000000 electrons
+         Band energy:  12.818451;  BLOECHL correction: -0.111649
+       DOS:  cpu time    0.03: real time    0.03
+    --------------------------------------------
+      LOOP:  cpu time    3.54: real time    3.66
+
+ eigenvalue-minimisations  :  5364
+ total energy-change (2. order) :-0.1839857E+01  (-0.8490176E+02)
+ number of electron    3.0000000 magnetization    0.6000000
+ augmentation part     3.0000000 magnetization    0.6000000
+
+ Free energy of the ion-electron system (eV)
+  ---------------------------------------------------
+  alpha Z        PSCENC =        -0.20486981
+  Ewald energy   TEWEN  =       -73.67253674
+  -1/2 Hartree   DENC   =        -0.09905503
+  -exchange  EXHF       =         0.00000000
+  -V(xc)+E(xc)   XCENC  =       -26.17475841
+  PAW double counting   =        35.53514605       -3.58069100
+  entropy T*S    EENTRO =         0.00000000
+  eigenvalues    EBANDS =        12.81845108
+  atomic energy  EATOM  =        53.53845706
+  ---------------------------------------------------
+  free energy    TOTEN  =        -1.83985680 eV
+
+  energy without entropy =       -1.83985680  energy(sigma->0) =       -1.83985680
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+
+
+----------------------------------------- Iteration    1(   2)  ---------------------------------------
+
+
+     EDDAV:  cpu time    3.90: real time    3.90
+ BZINTS: Fermi energy:  8.133411;  3.000000 electrons
+         Band energy:  10.991366;  BLOECHL correction: -0.045115
+       DOS:  cpu time    0.02: real time    0.02
+    --------------------------------------------
+      LOOP:  cpu time    3.92: real time    3.92
+
+ eigenvalue-minimisations  :  6840
+ total energy-change (2. order) :-0.1827085E+01  (-0.1781267E+01)
+ number of electron    3.0000000 magnetization    0.6000000
+ augmentation part     3.0000000 magnetization    0.6000000
+
+ Free energy of the ion-electron system (eV)
+  ---------------------------------------------------
+  alpha Z        PSCENC =        -0.20486981
+  Ewald energy   TEWEN  =       -73.67253674
+  -1/2 Hartree   DENC   =        -0.09905503
+  -exchange  EXHF       =         0.00000000
+  -V(xc)+E(xc)   XCENC  =       -26.17475841
+  PAW double counting   =        35.53514605       -3.58069100
+  entropy T*S    EENTRO =         0.00000000
+  eigenvalues    EBANDS =        10.99136572
+  atomic energy  EATOM  =        53.53845706
+  ---------------------------------------------------
+  free energy    TOTEN  =        -3.66694216 eV
+
+  energy without entropy =       -3.66694216  energy(sigma->0) =       -3.66694216
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+
+
+----------------------------------------- Iteration    1(   3)  ---------------------------------------
+
+
+     EDDAV:  cpu time    4.01: real time    4.01
+ BZINTS: Fermi energy:  8.120605;  3.000000 electrons
+         Band energy:  10.976373;  BLOECHL correction: -0.044931
+       DOS:  cpu time    0.02: real time    0.02
+    --------------------------------------------
+      LOOP:  cpu time    4.03: real time    4.04
+
+ eigenvalue-minimisations  :  7050
+ total energy-change (2. order) :-0.1499319E-01  (-0.1501025E-01)
+ number of electron    3.0000000 magnetization    0.6000000
+ augmentation part     3.0000000 magnetization    0.6000000
+
+ Free energy of the ion-electron system (eV)
+  ---------------------------------------------------
+  alpha Z        PSCENC =        -0.20486981
+  Ewald energy   TEWEN  =       -73.67253674
+  -1/2 Hartree   DENC   =        -0.09905503
+  -exchange  EXHF       =         0.00000000
+  -V(xc)+E(xc)   XCENC  =       -26.17475841
+  PAW double counting   =        35.53514605       -3.58069100
+  entropy T*S    EENTRO =         0.00000000
+  eigenvalues    EBANDS =        10.97637253
+  atomic energy  EATOM  =        53.53845706
+  ---------------------------------------------------
+  free energy    TOTEN  =        -3.68193534 eV
+
+  energy without entropy =       -3.68193534  energy(sigma->0) =       -3.68193534
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+
+
+----------------------------------------- Iteration    1(   4)  ---------------------------------------
+
+
+     EDDAV:  cpu time    4.04: real time    4.04
+ BZINTS: Fermi energy:  8.120565;  3.000000 electrons
+         Band energy:  10.976334;  BLOECHL correction: -0.044930
+       DOS:  cpu time    0.02: real time    0.02
+    --------------------------------------------
+      LOOP:  cpu time    4.06: real time    4.07
+
+ eigenvalue-minimisations  :  7044
+ total energy-change (2. order) :-0.3812864E-04  (-0.3835956E-04)
+ number of electron    3.0000000 magnetization    0.6000000
+ augmentation part     3.0000000 magnetization    0.6000000
+
+ Free energy of the ion-electron system (eV)
+  ---------------------------------------------------
+  alpha Z        PSCENC =        -0.20486981
+  Ewald energy   TEWEN  =       -73.67253674
+  -1/2 Hartree   DENC   =        -0.09905503
+  -exchange  EXHF       =         0.00000000
+  -V(xc)+E(xc)   XCENC  =       -26.17475841
+  PAW double counting   =        35.53514605       -3.58069100
+  entropy T*S    EENTRO =         0.00000000
+  eigenvalues    EBANDS =        10.97633440
+  atomic energy  EATOM  =        53.53845706
+  ---------------------------------------------------
+  free energy    TOTEN  =        -3.68197347 eV
+
+  energy without entropy =       -3.68197347  energy(sigma->0) =       -3.68197347
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+
+
+----------------------------------------- Iteration    1(   5)  ---------------------------------------
+
+
+     EDDAV:  cpu time    4.08: real time    4.08
+ BZINTS: Fermi energy:  8.120565;  3.000000 electrons
+         Band energy:  10.976334;  BLOECHL correction: -0.044930
+       DOS:  cpu time    0.02: real time    0.02
+    CHARGE:  cpu time    0.11: real time    0.11
+    MIXING:  cpu time    0.00: real time    0.01
+    --------------------------------------------
+      LOOP:  cpu time    4.21: real time    4.22
+
+ eigenvalue-minimisations  :  7146
+ total energy-change (2. order) :-0.1967941E-06  (-0.1963461E-06)
+ number of electron    3.0000000 magnetization   -0.0426071
+ augmentation part    -0.0369119 magnetization   -0.1858986
+
+ Broyden mixing:
+  rms(total) = 0.14891E+00    rms(broyden)= 0.14891E+00
+  rms(prec ) = 0.37033E+00
+  weight for this iteration     100.00
+
+ Free energy of the ion-electron system (eV)
+  ---------------------------------------------------
+  alpha Z        PSCENC =        -0.20486981
+  Ewald energy   TEWEN  =       -73.67253674
+  -1/2 Hartree   DENC   =        -0.09905503
+  -exchange  EXHF       =         0.00000000
+  -V(xc)+E(xc)   XCENC  =       -26.17475841
+  PAW double counting   =        35.53514605       -3.58069100
+  entropy T*S    EENTRO =         0.00000000
+  eigenvalues    EBANDS =        10.97633421
+  atomic energy  EATOM  =        53.53845706
+  ---------------------------------------------------
+  free energy    TOTEN  =        -3.68197367 eV
+
+  energy without entropy =       -3.68197367  energy(sigma->0) =       -3.68197367
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+
+
+----------------------------------------- Iteration    1(   6)  ---------------------------------------
+
+
+    POTLOK:  cpu time    0.02: real time    0.02
+    SETDIJ:  cpu time    0.01: real time    0.01
+     EDDAV:  cpu time    3.51: real time    3.51
+ BZINTS: Fermi energy:  8.109014;  3.000000 electrons
+         Band energy:  10.911058;  BLOECHL correction: -0.041621
+       DOS:  cpu time    0.02: real time    0.02
+    CHARGE:  cpu time    0.10: real time    0.10
+    MIXING:  cpu time    0.00: real time    0.00
+    --------------------------------------------
+      LOOP:  cpu time    3.67: real time    3.67
+
+ eigenvalue-minimisations  :  5952
+ total energy-change (2. order) :-0.7030407E-01  (-0.5750471E-03)
+ number of electron    3.0000000 magnetization    0.0494010
+ augmentation part    -0.0370819 magnetization    0.0567525
+
+ Broyden mixing:
+  rms(total) = 0.61067E-01    rms(broyden)= 0.61067E-01
+  rms(prec ) = 0.22482E+00
+  weight for this iteration     100.00
+
+ eigenvalues of (default mixing * dielectric matrix)
+  average eigenvalue GAMMA=   0.9444
+  0.9444
+
+ Free energy of the ion-electron system (eV)
+  ---------------------------------------------------
+  alpha Z        PSCENC =        -0.20486981
+  Ewald energy   TEWEN  =       -73.67253674
+  -1/2 Hartree   DENC   =        -0.08405912
+  -exchange  EXHF       =         0.00000000
+  -V(xc)+E(xc)   XCENC  =       -26.19176888
+  PAW double counting   =        35.59867548       -3.64723334
+  entropy T*S    EENTRO =         0.00000000
+  eigenvalues    EBANDS =        10.91105761
+  atomic energy  EATOM  =        53.53845706
+  ---------------------------------------------------
+  free energy    TOTEN  =        -3.75227774 eV
+
+  energy without entropy =       -3.75227774  energy(sigma->0) =       -3.75227774
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+
+
+----------------------------------------- Iteration    1(   7)  ---------------------------------------
+
+
+    POTLOK:  cpu time    0.02: real time    0.02
+    SETDIJ:  cpu time    0.01: real time    0.01
+     EDDAV:  cpu time    3.61: real time    3.61
+ BZINTS: Fermi energy:  8.097372;  3.000000 electrons
+         Band energy:  10.882812;  BLOECHL correction: -0.041776
+       DOS:  cpu time    0.02: real time    0.02
+    CHARGE:  cpu time    0.10: real time    0.10
+    MIXING:  cpu time    0.00: real time    0.00
+    --------------------------------------------
+      LOOP:  cpu time    3.76: real time    3.76
+
+ eigenvalue-minimisations  :  5964
+ total energy-change (2. order) : 0.8846572E-02  (-0.7642311E-03)
+ number of electron    3.0000000 magnetization   -0.0048252
+ augmentation part    -0.0378173 magnetization   -0.0127380
+
+ Broyden mixing:
+  rms(total) = 0.26746E-01    rms(broyden)= 0.26746E-01
+  rms(prec ) = 0.71804E-01
+  weight for this iteration     100.00
+
+ eigenvalues of (default mixing * dielectric matrix)
+  average eigenvalue GAMMA=   1.3346
+  0.8791  1.7900
+
+ Free energy of the ion-electron system (eV)
+  ---------------------------------------------------
+  alpha Z        PSCENC =        -0.20486981
+  Ewald energy   TEWEN  =       -73.67253674
+  -1/2 Hartree   DENC   =        -0.09204508
+  -exchange  EXHF       =         0.00000000
+  -V(xc)+E(xc)   XCENC  =       -26.14171949
+  PAW double counting   =        35.63226269       -3.68579144
+  entropy T*S    EENTRO =         0.00000000
+  eigenvalues    EBANDS =        10.88281164
+  atomic energy  EATOM  =        53.53845706
+  ---------------------------------------------------
+  free energy    TOTEN  =        -3.74343117 eV
+
+  energy without entropy =       -3.74343117  energy(sigma->0) =       -3.74343117
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+
+
+----------------------------------------- Iteration    1(   8)  ---------------------------------------
+
+
+    POTLOK:  cpu time    0.02: real time    0.02
+    SETDIJ:  cpu time    0.01: real time    0.01
+     EDDAV:  cpu time    3.41: real time    3.41
+ BZINTS: Fermi energy:  8.093775;  3.000000 electrons
+         Band energy:  10.874623;  BLOECHL correction: -0.041847
+       DOS:  cpu time    0.02: real time    0.02
+    CHARGE:  cpu time    0.10: real time    0.10
+    MIXING:  cpu time    0.00: real time    0.00
+    --------------------------------------------
+      LOOP:  cpu time    3.56: real time    3.56
+
+ eigenvalue-minimisations  :  5700
+ total energy-change (2. order) :-0.3575765E-04  (-0.2563445E-03)
+ number of electron    3.0000000 magnetization   -0.0002771
+ augmentation part    -0.0381739 magnetization   -0.0009017
+
+ Broyden mixing:
+  rms(total) = 0.88922E-02    rms(broyden)= 0.88922E-02
+  rms(prec ) = 0.95960E-02
+  weight for this iteration     100.00
+
+ eigenvalues of (default mixing * dielectric matrix)
+  average eigenvalue GAMMA=   1.4006
+  2.5744  0.9389  0.6885
+
+ Free energy of the ion-electron system (eV)
+  ---------------------------------------------------
+  alpha Z        PSCENC =        -0.20486981
+  Ewald energy   TEWEN  =       -73.67253674
+  -1/2 Hartree   DENC   =        -0.10476980
+  -exchange  EXHF       =         0.00000000
+  -V(xc)+E(xc)   XCENC  =       -26.11802900
+  PAW double counting   =        35.65312182       -3.70946333
+  entropy T*S    EENTRO =         0.00000000
+  eigenvalues    EBANDS =        10.87462287
+  atomic energy  EATOM  =        53.53845706
+  ---------------------------------------------------
+  free energy    TOTEN  =        -3.74346693 eV
+
+  energy without entropy =       -3.74346693  energy(sigma->0) =       -3.74346693
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+
+
+----------------------------------------- Iteration    1(   9)  ---------------------------------------
+
+
+    POTLOK:  cpu time    0.02: real time    0.02
+    SETDIJ:  cpu time    0.01: real time    0.01
+     EDDAV:  cpu time    3.81: real time    3.80
+ BZINTS: Fermi energy:  8.093928;  3.000000 electrons
+         Band energy:  10.875150;  BLOECHL correction: -0.041849
+       DOS:  cpu time    0.02: real time    0.02
+    CHARGE:  cpu time    0.10: real time    0.10
+    MIXING:  cpu time    0.00: real time    0.00
+    --------------------------------------------
+      LOOP:  cpu time    3.96: real time    3.96
+
+ eigenvalue-minimisations  :  6606
+ total energy-change (2. order) : 0.1090099E-03  (-0.6682625E-05)
+ number of electron    3.0000000 magnetization    0.0001953
+ augmentation part    -0.0381911 magnetization    0.0004059
+
+ Broyden mixing:
+  rms(total) = 0.16276E-02    rms(broyden)= 0.16276E-02
+  rms(prec ) = 0.30007E-02
+  weight for this iteration     100.00
+
+ eigenvalues of (default mixing * dielectric matrix)
+  average eigenvalue GAMMA=   1.2690
+  2.6225  0.9707  0.8497  0.6331
+
+ Free energy of the ion-electron system (eV)
+  ---------------------------------------------------
+  alpha Z        PSCENC =        -0.20486981
+  Ewald energy   TEWEN  =       -73.67253674
+  -1/2 Hartree   DENC   =        -0.10535854
+  -exchange  EXHF       =         0.00000000
+  -V(xc)+E(xc)   XCENC  =       -26.11741776
+  PAW double counting   =        35.65916718       -3.71594965
+  entropy T*S    EENTRO =         0.00000000
+  eigenvalues    EBANDS =        10.87515034
+  atomic energy  EATOM  =        53.53845706
+  ---------------------------------------------------
+  free energy    TOTEN  =        -3.74335792 eV
+
+  energy without entropy =       -3.74335792  energy(sigma->0) =       -3.74335792
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+
+
+----------------------------------------- Iteration    1(  10)  ---------------------------------------
+
+
+    POTLOK:  cpu time    0.02: real time    0.02
+    SETDIJ:  cpu time    0.01: real time    0.01
+     EDDAV:  cpu time    4.05: real time    4.05
+ BZINTS: Fermi energy:  8.094086;  3.000000 electrons
+         Band energy:  10.875646;  BLOECHL correction: -0.041850
+       DOS:  cpu time    0.02: real time    0.02
+    CHARGE:  cpu time    0.10: real time    0.10
+    MIXING:  cpu time    0.00: real time    0.00
+    --------------------------------------------
+      LOOP:  cpu time    4.21: real time    4.20
+
+ eigenvalue-minimisations  :  7116
+ total energy-change (2. order) : 0.1876910E-05  (-0.8060209E-06)
+ number of electron    3.0000000 magnetization   -0.0000056
+ augmentation part    -0.0381999 magnetization   -0.0000720
+
+ Broyden mixing:
+  rms(total) = 0.73926E-03    rms(broyden)= 0.73926E-03
+  rms(prec ) = 0.15734E-02
+  weight for this iteration     100.00
+
+ eigenvalues of (default mixing * dielectric matrix)
+  average eigenvalue GAMMA=   1.3757
+  2.6231  1.8389  0.9607  0.8275  0.6284
+
+ Free energy of the ion-electron system (eV)
+  ---------------------------------------------------
+  alpha Z        PSCENC =        -0.20486981
+  Ewald energy   TEWEN  =       -73.67253674
+  -1/2 Hartree   DENC   =        -0.10582417
+  -exchange  EXHF       =         0.00000000
+  -V(xc)+E(xc)   XCENC  =       -26.11693323
+  PAW double counting   =        35.66596946       -3.72326493
+  entropy T*S    EENTRO =         0.00000000
+  eigenvalues    EBANDS =        10.87564632
+  atomic energy  EATOM  =        53.53845706
+  ---------------------------------------------------
+  free energy    TOTEN  =        -3.74335604 eV
+
+  energy without entropy =       -3.74335604  energy(sigma->0) =       -3.74335604
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+
+
+----------------------------------------- Iteration    1(  11)  ---------------------------------------
+
+
+    POTLOK:  cpu time    0.02: real time    0.02
+    SETDIJ:  cpu time    0.01: real time    0.01
+     EDDAV:  cpu time    3.41: real time    3.41
+ BZINTS: Fermi energy:  8.094246;  3.000000 electrons
+         Band energy:  10.876169;  BLOECHL correction: -0.041851
+       DOS:  cpu time    0.02: real time    0.02
+    CHARGE:  cpu time    0.11: real time    0.11
+    MIXING:  cpu time    0.00: real time    0.00
+    --------------------------------------------
+      LOOP:  cpu time    3.57: real time    3.57
+
+ eigenvalue-minimisations  :  5718
+ total energy-change (2. order) :-0.2318165E-05  (-0.2318034E-06)
+ number of electron    3.0000000 magnetization    0.0000082
+ augmentation part    -0.0382086 magnetization   -0.0000018
+
+ Broyden mixing:
+  rms(total) = 0.12175E-03    rms(broyden)= 0.12175E-03
+  rms(prec ) = 0.14755E-03
+  weight for this iteration     100.00
+
+ eigenvalues of (default mixing * dielectric matrix)
+  average eigenvalue GAMMA=   1.4001
+  2.6387  2.5571  0.9682  0.8619  0.7479  0.6265
+
+ Free energy of the ion-electron system (eV)
+  ---------------------------------------------------
+  alpha Z        PSCENC =        -0.20486981
+  Ewald energy   TEWEN  =       -73.67253674
+  -1/2 Hartree   DENC   =        -0.10642957
+  -exchange  EXHF       =         0.00000000
+  -V(xc)+E(xc)   XCENC  =       -26.11626805
+  PAW double counting   =        35.67330599       -3.73118626
+  entropy T*S    EENTRO =         0.00000000
+  eigenvalues    EBANDS =        10.87616902
+  atomic energy  EATOM  =        53.53845706
+  ---------------------------------------------------
+  free energy    TOTEN  =        -3.74335836 eV
+
+  energy without entropy =       -3.74335836  energy(sigma->0) =       -3.74335836
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+
+
+----------------------------------------- Iteration    1(  12)  ---------------------------------------
+
+
+    POTLOK:  cpu time    0.02: real time    0.02
+    SETDIJ:  cpu time    0.01: real time    0.01
+     EDDAV:  cpu time    2.29: real time    2.29
+ BZINTS: Fermi energy:  8.094245;  3.000000 electrons
+         Band energy:  10.876169;  BLOECHL correction: -0.041851
+       DOS:  cpu time    0.02: real time    0.02
+    --------------------------------------------
+      LOOP:  cpu time    2.34: real time    2.34
+
+ eigenvalue-minimisations  :  3078
+ total energy-change (2. order) :-0.3140946E-06  (-0.3960422E-07)
+ number of electron    3.0000000 magnetization    0.0000082
+ augmentation part    -0.0382086 magnetization   -0.0000018
+
+ Free energy of the ion-electron system (eV)
+  ---------------------------------------------------
+  alpha Z        PSCENC =        -0.20486981
+  Ewald energy   TEWEN  =       -73.67253674
+  -1/2 Hartree   DENC   =        -0.10646068
+  -exchange  EXHF       =         0.00000000
+  -V(xc)+E(xc)   XCENC  =       -26.11623001
+  PAW double counting   =        35.67323357       -3.73112122
+  entropy T*S    EENTRO =         0.00000000
+  eigenvalues    EBANDS =        10.87616915
+  atomic energy  EATOM  =        53.53845706
+  ---------------------------------------------------
+  free energy    TOTEN  =        -3.74335867 eV
+
+  energy without entropy =       -3.74335867  energy(sigma->0) =       -3.74335867
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+
+
+ average (electrostatic) potential at core
+  the test charge radii are     1.0406
+  (the norm of the test charge is              1.0000)
+       1 -72.5590
+ 
+ 
+ 
+ E-fermi :   8.0942     XC(G=0): -10.2200     alpha+bet :-14.9718
+   add alpha+bet to get absolut eigen values
+
+ spin component 1
+
+ k-point   1 :       0.0000    0.0000    0.0000
+  band No.  band energies     occupation 
+      1      -3.1118      1.00000
+      2      20.7214      0.00000
+      3      20.7214      0.00000
+      4      20.7214      0.00000
+      5      22.2613      0.00000
+      6      22.2613      0.00000
+
+ k-point   2 :       0.0526    0.0000    0.0000
+  band No.  band energies     occupation 
+      1      -3.0362      1.00000
+      2      19.3192      0.00000
+      3      20.4408      0.00000
+      4      20.4408      0.00000
+      5      22.6602      0.00000
+      6      22.6602      0.00000
+
+ k-point   3 :       0.1053    0.0000    0.0000
+  band No.  band energies     occupation 
+      1      -2.8095      1.00000
+      2      17.2163      0.00000
+      3      19.9594      0.00000
+      4      19.9594      0.00000
+      5      22.8939      0.00000
+      6      23.4741      0.00000
+
+ k-point   4 :       0.1579    0.0000    0.0000
+  band No.  band energies     occupation 
+      1      -2.4326      1.00000
+      2      15.0838      0.00000
+      3      19.5256      0.00000
+      4      19.5256      0.00000
+      5      22.7469      0.00000
+      6      24.1771      0.00000
+
+ k-point   5 :       0.2105    0.0000    0.0000
+  band No.  band energies     occupation 
+      1      -1.9065      1.00000
+      2      13.0128      0.00000
+      3      19.1937      0.00000
+      4      19.1937      0.00000
+      5      22.5768      0.00000
+      6      23.6003      0.00000
+
+ k-point   6 :       0.2632    0.0000    0.0000
+  band No.  band energies     occupation 
+      1      -1.2331      1.00000
+      2      11.0340      0.00000
+      3      18.9786      0.00000
+      4      18.9786      0.00000
+      5      22.4609      0.00000
+      6      22.6497      0.00000
+
+ k-point   7 :       0.3158    0.0000    0.0000
+  band No.  band energies     occupation 
+      1      -0.4142      1.00000
+      2       9.1627     -0.06441
+      3      18.8857      0.00000
+      4      18.8857      0.00000
+      5      21.7585      0.00000
+      6      21.7585      0.00000
+
+ k-point   8 :       0.3684    0.0000    0.0000
+  band No.  band energies     occupation 
+      1       0.5475      1.00000
+      2       7.4080      0.96988
+      3      18.9177      0.00000
+      4      18.9177      0.00000
+      5      20.9749      0.00000
+      6      20.9749      0.00000
+
+ k-point   9 :       0.4211    0.0000    0.0000
+  band No.  band energies     occupation 
+      1       1.6490      1.00000
+      2       5.7764      1.00000
+      3      19.0758      0.00000
+      4      19.0758      0.00000
+      5      20.3114      0.00000
+      6      20.3114      0.00000
+
+ k-point  10 :       0.4737    0.0000    0.0000
+  band No.  band energies     occupation 
+      1       2.8831      1.00000
+      2       4.2769      1.00000
+      3      19.3606      0.00000
+      4      19.3606      0.00000
+      5      19.7728      0.00000
+      6      19.7728      0.00000
+
+ k-point  11 :       0.0526    0.0526    0.0000
+  band No.  band energies     occupation 
+      1      -3.0110      1.00000
+      2      19.7769      0.00000
+      3      19.7769      0.00000
+      4      20.0217      0.00000
+      5      22.0175      0.00000
+      6      23.3543      0.00000
+
+ k-point  12 :       0.1053    0.0526    0.0000
+  band No.  band energies     occupation 
+      1      -2.8347      1.00000
+      2      17.9371      0.00000
+      3      19.1664      0.00000
+      4      20.0798      0.00000
+      5      22.1588      0.00000
+      6      23.7455      0.00000
+
+ k-point  13 :       0.1579    0.0526    0.0000
+  band No.  band energies     occupation 
+      1      -2.5079      1.00000
+      2      15.8269      0.00000
+      3      18.6600      0.00000
+      4      19.8509      0.00000
+      5      22.8094      0.00000
+      6      23.6922      0.00000
+
+ k-point  14 :       0.2105    0.0526    0.0000
+  band No.  band energies     occupation 
+      1      -2.0316      1.00000
+      2      13.7427      0.00000
+      3      18.2716      0.00000
+      4      19.5571      0.00000
+      5      22.4897      0.00000
+      6      23.4984      0.00000
+
+ k-point  15 :       0.2632    0.0526    0.0000
+  band No.  band energies     occupation 
+      1      -1.4074      1.00000
+      2      11.7372      0.00000
+      3      18.0064      0.00000
+      4      19.3308      0.00000
+      5      21.4806      0.00000
+      6      23.3620      0.00000
+
+ k-point  16 :       0.3158    0.0526    0.0000
+  band No.  band energies     occupation 
+      1      -0.6371      1.00000
+      2       9.8324     -0.00055
+      3      17.8664      0.00000
+      4      19.2104      0.00000
+      5      20.5290      0.00000
+      6      23.1781      0.00000
+
+ k-point  17 :       0.3684    0.0526    0.0000
+  band No.  band energies     occupation 
+      1       0.2769      1.00000
+      2       8.0402      0.52344
+      3      17.8531      0.00000
+      4      19.2072      0.00000
+      5      19.6913      0.00000
+      6      22.3695      0.00000
+
+ k-point  18 :       0.4211    0.0526    0.0000
+  band No.  band energies     occupation 
+      1       1.3317      1.00000
+      2       6.3684      1.00000
+      3      17.9670      0.00000
+      4      18.9590      0.00000
+      5      19.3471      0.00000
+      6      21.6725      0.00000
+
+ k-point  19 :       0.4737    0.0526    0.0000
+  band No.  band energies     occupation 
+      1       2.5226      1.00000
+      2       4.8241      1.00000
+      3      18.2088      0.00000
+      4      18.3724      0.00000
+      5      19.5967      0.00000
+      6      21.0959      0.00000
+
+ k-point  20 :      -0.4737    0.0526    0.0000
+  band No.  band energies     occupation 
+      1       3.3722      1.00000
+      2       3.8862      1.00000
+      3      17.9106      0.00000
+      4      18.5787      0.00000
+      5      19.9792      0.00000
+      6      20.6435      0.00000
+
+ k-point  21 :      -0.4211    0.0526    0.0000
+  band No.  band energies     occupation 
+      1       2.1111      1.00000
+      2       5.3239      1.00000
+      3      17.5784      0.00000
+      4      19.0761      0.00000
+      5      20.3173      0.00000
+      6      20.4896      0.00000
+
+ k-point  22 :      -0.3684    0.0526    0.0000
+  band No.  band energies     occupation 
+      1       0.9647      1.00000
+      2       6.9116      1.06330
+      3      17.3765      0.00000
+      4      19.6958      0.00000
+      5      20.1217      0.00000
+      6      21.1246      0.00000
+
+ k-point  23 :      -0.3158    0.0526    0.0000
+  band No.  band energies     occupation 
+      1      -0.0436      1.00000
+      2       8.6239      0.09710
+      3      17.3048      0.00000
+      4      20.0243      0.00000
+      5      20.4670      0.00000
+      6      21.8769      0.00000
+
+ k-point  24 :      -0.2632    0.0526    0.0000
+  band No.  band energies     occupation 
+      1      -0.9099      1.00000
+      2      10.4538      0.00000
+      3      17.3630      0.00000
+      4      20.0751      0.00000
+      5      21.3307      0.00000
+      6      22.7076      0.00000
+
+ k-point  25 :      -0.2105    0.0526    0.0000
+  band No.  band energies     occupation 
+      1      -1.6318      1.00000
+      2      12.3919      0.00000
+      3      17.5506      0.00000
+      4      20.2381      0.00000
+      5      22.2949      0.00000
+      6      23.0515      0.00000
+
+ k-point  26 :      -0.1579    0.0526    0.0000
+  band No.  band energies     occupation 
+      1      -2.2069      1.00000
+      2      14.4216      0.00000
+      3      17.8675      0.00000
+      4      20.5031      0.00000
+      5      23.1834      0.00000
+      6      23.1899      0.00000
+
+ k-point  27 :      -0.1053    0.0526    0.0000
+  band No.  band energies     occupation 
+      1      -2.6335      1.00000
+      2      16.5028      0.00000
+      3      18.3206      0.00000
+      4      20.8164      0.00000
+      5      22.8892      0.00000
+      6      23.2903      0.00000
+
+ k-point  28 :      -0.0526    0.0526    0.0000
+  band No.  band energies     occupation 
+      1      -2.9102      1.00000
+      2      18.4101      0.00000
+      3      19.0462      0.00000
+      4      20.9176      0.00000
+      5      22.3888      0.00000
+      6      23.1628      0.00000
+
+ k-point  29 :       0.1053    0.1053    0.0000
+  band No.  band energies     occupation 
+      1      -2.7089      1.00000
+      2      18.4817      0.00000
+      3      18.4817      0.00000
+      4      18.7367      0.00000
+      5      21.3935      0.00000
+      6      23.7805      0.00000
+
+ k-point  30 :       0.1579    0.1053    0.0000
+  band No.  band energies     occupation 
+      1      -2.4325      1.00000
+      2      16.6239      0.00000
+      3      17.9175      0.00000
+      4      18.9626      0.00000
+      5      21.4076      0.00000
+      6      22.4674      0.00000
+
+ k-point  31 :       0.2105    0.1053    0.0000
+  band No.  band energies     occupation 
+      1      -2.0066      1.00000
+      2      14.5696      0.00000
+      3      17.4779      0.00000
+      4      18.9070      0.00000
+      5      21.1258      0.00000
+      6      22.2390      0.00000
+
+ k-point  32 :       0.2632    0.1053    0.0000
+  band No.  band energies     occupation 
+      1      -1.4323      1.00000
+      2      12.5565      0.00000
+      3      17.1647      0.00000
+      4      18.7277      0.00000
+      5      20.0097      0.00000
+      6      23.3234      0.00000
+
+ k-point  33 :       0.3158    0.1053    0.0000
+  band No.  band energies     occupation 
+      1      -0.7115      1.00000
+      2      10.6284      0.00000
+      3      16.9787      0.00000
+      4      18.5719      0.00000
+      5      19.0123      0.00000
+      6      24.5063      0.00000
+
+ k-point  34 :       0.3684    0.1053    0.0000
+  band No.  band energies     occupation 
+      1       0.1536      1.00000
+      2       8.8050      0.00249
+      3      16.9205      0.00000
+      4      18.0355      0.00000
+      5      18.6187      0.00000
+      6      23.8805      0.00000
+
+ k-point  35 :       0.4211    0.1053    0.0000
+  band No.  band energies     occupation 
+      1       1.1602      1.00000
+      2       7.0973      1.06837
+      3      16.9903      0.00000
+      4      17.2760      0.00000
+      5      18.6970      0.00000
+      6      23.1564      0.00000
+
+ k-point  36 :       0.4737    0.1053    0.0000
+  band No.  band energies     occupation 
+      1       2.3046      1.00000
+      2       5.5132      1.00000
+      3      16.6331      0.00000
+      4      17.1886      0.00000
+      5      18.9183      0.00000
+      6      22.5457      0.00000
+
+ k-point  37 :      -0.4737    0.1053    0.0000
+  band No.  band energies     occupation 
+      1       3.5614      1.00000
+      2       4.0800      1.00000
+      3      16.1200      0.00000
+      4      17.5155      0.00000
+      5      19.2738      0.00000
+      6      22.0553      0.00000
+
+ k-point  38 :      -0.4211    0.1053    0.0000
+  band No.  band energies     occupation 
+      1       2.7157      1.00000
+      2       5.0131      1.00000
+      3      15.7398      0.00000
+      4      17.9710      0.00000
+      5      19.7615      0.00000
+      6      21.6884      0.00000
+
+ k-point  39 :      -0.3684    0.1053    0.0000
+  band No.  band energies     occupation 
+      1       1.5268      1.00000
+      2       6.5526      1.00541
+      3      15.4942      0.00000
+      4      18.5543      0.00000
+      5      20.3784      0.00000
+      6      21.4463      0.00000
+
+ k-point  40 :      -0.3158    0.1053    0.0000
+  band No.  band energies     occupation 
+      1       0.4737      1.00000
+      2       8.2172      0.38903
+      3      15.3849      0.00000
+      4      19.2629      0.00000
+      5      21.1196      0.00000
+      6      21.3290      0.00000
+
+ k-point  41 :      -0.2632    0.1053    0.0000
+  band No.  band energies     occupation 
+      1      -0.4390      1.00000
+      2       9.9967      0.00000
+      3      15.4142      0.00000
+      4      20.0885      0.00000
+      5      21.3371      0.00000
+      6      21.9771      0.00000
+
+ k-point  42 :      -0.2105    0.1053    0.0000
+  band No.  band energies     occupation 
+      1      -1.2082      1.00000
+      2      11.8750      0.00000
+      3      15.5894      0.00000
+      4      20.9877      0.00000
+      5      21.4885      0.00000
+      6      22.9367      0.00000
+
+ k-point  43 :      -0.1579    0.1053    0.0000
+  band No.  band energies     occupation 
+      1      -1.8315      1.00000
+      2      13.8062      0.00000
+      3      15.9407      0.00000
+      4      21.5297      0.00000
+      5      22.0959      0.00000
+      6      23.8658      0.00000
+
+ k-point  44 :      -0.1053    0.1053    0.0000
+  band No.  band energies     occupation 
+      1      -2.3071      1.00000
+      2      15.5410      0.00000
+      3      16.6866      0.00000
+      4      21.5051      0.00000
+      5      22.5764      0.00000
+      6      23.7902      0.00000
+
+ k-point  45 :       0.1579    0.1579    0.0000
+  band No.  band energies     occupation 
+      1      -2.2069      1.00000
+      2      17.3016      0.00000
+      3      17.3016      0.00000
+      4      17.4526      0.00000
+      5      20.5861      0.00000
+      6      21.0353      0.00000
+
+ k-point  46 :       0.2105    0.1579    0.0000
+  band No.  band energies     occupation 
+      1      -1.8315      1.00000
+      2      15.4550      0.00000
+      3      16.8136      0.00000
+      4      17.8327      0.00000
+      5      19.7120      0.00000
+      6      20.5973      0.00000
+
+ k-point  47 :       0.2632    0.1579    0.0000
+  band No.  band energies     occupation 
+      1      -1.3077      1.00000
+      2      13.4750      0.00000
+      3      16.4539      0.00000
+      4      17.8713      0.00000
+      5      18.5303      0.00000
+      6      21.3581      0.00000
+
+ k-point  48 :       0.3158    0.1579    0.0000
+  band No.  band energies     occupation 
+      1      -0.6372      1.00000
+      2      11.5417      0.00000
+      3      16.2227      0.00000
+      4      17.3485      0.00000
+      5      17.8907      0.00000
+      6      22.5443      0.00000
+
+ k-point  49 :       0.3684    0.1579    0.0000
+  band No.  band energies     occupation 
+      1       0.1780      1.00000
+      2       9.6966     -0.00474
+      3      16.1199      0.00000
+      4      16.4196      0.00000
+      5      17.8232      0.00000
+      6      23.9245      0.00000
+
+ k-point  50 :       0.4211    0.1579    0.0000
+  band No.  band energies     occupation 
+      1       1.1352      1.00000
+      2       7.9589      0.58878
+      3      15.5939      0.00000
+      4      16.1456      0.00000
+      5      17.8845      0.00000
+      6      24.7557      0.00000
+
+ k-point  51 :       0.4737    0.1579    0.0000
+  band No.  band energies     occupation 
+      1       2.2310      1.00000
+      2       6.3394      1.00000
+      3      14.8966      0.00000
+      4      16.3001      0.00000
+      5      18.0737      0.00000
+      6      24.1169      0.00000
+
+ k-point  52 :      -0.4737    0.1579    0.0000
+  band No.  band energies     occupation 
+      1       3.4566      1.00000
+      2       4.8505      1.00000
+      3      14.3329      0.00000
+      4      16.5836      0.00000
+      5      18.3959      0.00000
+      6      23.5923      0.00000
+
+ k-point  53 :      -0.4211    0.1579    0.0000
+  band No.  band energies     occupation 
+      1       3.4586      1.00000
+      2       4.8464      1.00000
+      3      13.9057      0.00000
+      4      16.9961      0.00000
+      5      18.8520      0.00000
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+
+ k-point 162 :      -0.3684    0.4211    0.0526
+  band No.  band energies     occupation 
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+
+ k-point 163 :      -0.4737    0.4737    0.0526
+  band No.  band energies     occupation 
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+
+ k-point 164 :      -0.4211    0.4737    0.0526
+  band No.  band energies     occupation 
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+      5      16.1536      0.00000
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+
+ k-point 165 :       0.3158    0.2105    0.1053
+  band No.  band energies     occupation 
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+      6      21.9683      0.00000
+
+ k-point 166 :       0.3684    0.2105    0.1053
+  band No.  band energies     occupation 
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+      4      17.5887      0.00000
+      5      20.4277      0.00000
+      6      22.7652      0.00000
+
+ k-point 167 :       0.4211    0.2105    0.1053
+  band No.  band energies     occupation 
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+      3      13.6447      0.00000
+      4      16.6324      0.00000
+      5      20.5060      0.00000
+      6      23.4475      0.00000
+
+ k-point 168 :       0.4737    0.2105    0.1053
+  band No.  band energies     occupation 
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+      2       8.1260      0.45806
+      3      13.6303      0.00000
+      4      15.8071      0.00000
+      5      20.6054      0.00000
+      6      22.8041      0.00000
+
+ k-point 169 :      -0.4737    0.2105    0.1053
+  band No.  band energies     occupation 
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+      3      13.7618      0.00000
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+      5      20.7943      0.00000
+      6      22.1528      0.00000
+
+ k-point 170 :      -0.4211    0.2105    0.1053
+  band No.  band energies     occupation 
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+      3      13.9937      0.00000
+      4      14.6139      0.00000
+      5      21.0662      0.00000
+      6      21.6405      0.00000
+
+ k-point 171 :       0.3684    0.2632    0.1053
+  band No.  band energies     occupation 
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+      5      19.2494      0.00000
+      6      21.2624      0.00000
+
+ k-point 172 :       0.4211    0.2632    0.1053
+  band No.  band energies     occupation 
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+      3      13.0247      0.00000
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+      5      19.6670      0.00000
+      6      22.1520      0.00000
+
+ k-point 173 :       0.4737    0.2632    0.1053
+  band No.  band energies     occupation 
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+      3      12.8888      0.00000
+      4      14.2507      0.00000
+      5      19.8503      0.00000
+      6      23.4513      0.00000
+
+ k-point 174 :      -0.4737    0.2632    0.1053
+  band No.  band energies     occupation 
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+      2       7.4661      0.95090
+      3      12.8992      0.00000
+      4      13.5698      0.00000
+      5      20.0487      0.00000
+      6      23.7498      0.00000
+
+ k-point 175 :      -0.4211    0.2632    0.1053
+  band No.  band energies     occupation 
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+      4      13.3816      0.00000
+      5      20.3381      0.00000
+      6      23.2278      0.00000
+
+ k-point 176 :      -0.3684    0.2632    0.1053
+  band No.  band energies     occupation 
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+      3      12.3063      0.00000
+      4      13.6916      0.00000
+      5      20.7382      0.00000
+      6      22.7715      0.00000
+
+ k-point 177 :      -0.3158    0.2632    0.1053
+  band No.  band energies     occupation 
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+      2       6.4318      1.00000
+      3      11.9977      0.00000
+      4      14.1935      0.00000
+      5      21.2471      0.00000
+      6      22.4284      0.00000
+
+ k-point 178 :      -0.2632    0.2632    0.1053
+  band No.  band energies     occupation 
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+      3      11.8388      0.00000
+      4      14.8424      0.00000
+      5      21.8012      0.00000
+      6      22.2450      0.00000
+
+ k-point 179 :      -0.2105    0.2632    0.1053
+  band No.  band energies     occupation 
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+      3      11.8866      0.00000
+      4      15.6284      0.00000
+      5      21.8634      0.00000
+      6      22.6456      0.00000
+
+ k-point 180 :      -0.1579    0.2632    0.1053
+  band No.  band energies     occupation 
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+      2      10.9182      0.00000
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+      4      16.5460      0.00000
+      5      21.4250      0.00000
+      6      22.8621      0.00000
+
+ k-point 181 :       0.4211    0.3158    0.1053
+  band No.  band energies     occupation 
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+      3      12.8043      0.00000
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+
+ k-point 182 :       0.4737    0.3158    0.1053
+  band No.  band energies     occupation 
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+
+ k-point 183 :      -0.4737    0.3158    0.1053
+  band No.  band energies     occupation 
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+
+ k-point 184 :      -0.4211    0.3158    0.1053
+  band No.  band energies     occupation 
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+
+ k-point 185 :      -0.3684    0.3158    0.1053
+  band No.  band energies     occupation 
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+
+ k-point 186 :      -0.3158    0.3158    0.1053
+  band No.  band energies     occupation 
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+      3      10.3554      0.00000
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+      5      20.5031      0.00000
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+
+ k-point 187 :      -0.2632    0.3158    0.1053
+  band No.  band energies     occupation 
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+      3      10.2219      0.00000
+      4      14.0059      0.00000
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+
+ k-point 188 :      -0.2105    0.3158    0.1053
+  band No.  band energies     occupation 
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+      3      10.5821      0.00000
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+
+ k-point 189 :       0.4737    0.3684    0.1053
+  band No.  band energies     occupation 
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+      3      11.2452      0.00000
+      4      12.4667      0.00000
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+      6      20.1677      0.00000
+
+ k-point 190 :      -0.4737    0.3684    0.1053
+  band No.  band energies     occupation 
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+      3      10.4523      0.00000
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+
+ k-point 191 :      -0.4211    0.3684    0.1053
+  band No.  band energies     occupation 
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+      3       9.7705      0.00000
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+
+ k-point 192 :      -0.3684    0.3684    0.1053
+  band No.  band energies     occupation 
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+      2       6.7071      1.00822
+      3       9.2321     -0.01561
+      4      12.3263      0.00000
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+
+ k-point 193 :      -0.3158    0.3684    0.1053
+  band No.  band energies     occupation 
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+      3       8.9035     -0.00832
+      4      12.7417      0.00000
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+      6      25.7047      0.00000
+
+ k-point 194 :      -0.2632    0.3684    0.1053
+  band No.  band energies     occupation 
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+      3       9.0754      0.00000
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+      6      25.1166      0.00000
+
+ k-point 195 :      -0.4737    0.4211    0.1053
+  band No.  band energies     occupation 
+      1       3.5601      1.00000
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+      3      10.5471      0.00000
+      4      12.0538      0.00000
+      5      17.6294      0.00000
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+
+ k-point 196 :      -0.4211    0.4211    0.1053
+  band No.  band energies     occupation 
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+      3       9.3976      0.00000
+      4      11.7352      0.00000
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+
+ k-point 197 :      -0.3684    0.4211    0.1053
+  band No.  band energies     occupation 
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+      3       8.1775      0.04018
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+
+ k-point 198 :      -0.3158    0.4211    0.1053
+  band No.  band energies     occupation 
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+      4      12.2301      0.00000
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+      6      24.4554      0.00000
+
+ k-point 199 :      -0.4211    0.4737    0.1053
+  band No.  band energies     occupation 
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+      3      10.3611      0.00000
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+
+ k-point 200 :      -0.3684    0.4737    0.1053
+  band No.  band energies     occupation 
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+      4      11.6382      0.00000
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+      6      20.9094      0.00000
+
+ k-point 201 :       0.4737    0.3158    0.1579
+  band No.  band energies     occupation 
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+
+ k-point 202 :      -0.4737    0.3158    0.1579
+  band No.  band energies     occupation 
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+
+ k-point 203 :      -0.4211    0.3158    0.1579
+  band No.  band energies     occupation 
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+
+ k-point 204 :      -0.3684    0.3158    0.1579
+  band No.  band energies     occupation 
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+
+ k-point 205 :      -0.4737    0.3684    0.1579
+  band No.  band energies     occupation 
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+
+ k-point 206 :      -0.4211    0.3684    0.1579
+  band No.  band energies     occupation 
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+      3      10.5687      0.00000
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+      5      20.8748      0.00000
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+
+ k-point 207 :      -0.3684    0.3684    0.1579
+  band No.  band energies     occupation 
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+      3      10.2964      0.00000
+      4      11.1087      0.00000
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+      6      24.1036      0.00000
+
+ k-point 208 :      -0.3158    0.3684    0.1579
+  band No.  band energies     occupation 
+      1       5.6205      1.00000
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+      3       9.9353      0.00000
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+      5      21.7361      0.00000
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+
+ k-point 209 :      -0.2632    0.3684    0.1579
+  band No.  band energies     occupation 
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+
+ k-point 210 :      -0.2105    0.3684    0.1579
+  band No.  band energies     occupation 
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+      2       8.5044      0.17657
+      3       9.9954      0.00000
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+
+ k-point 211 :      -0.4211    0.4211    0.1579
+  band No.  band energies     occupation 
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+
+ k-point 212 :      -0.3684    0.4211    0.1579
+  band No.  band energies     occupation 
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+
+ k-point 213 :      -0.3158    0.4211    0.1579
+  band No.  band energies     occupation 
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+      3       8.5966     -0.01660
+      4      10.8192      0.00000
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+
+ k-point 214 :      -0.2632    0.4211    0.1579
+  band No.  band energies     occupation 
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+      2       7.2070      1.00013
+      3       8.6719     -0.00125
+      4      11.2561      0.00000
+      5      21.6602      0.00000
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+
+ k-point 215 :      -0.3684    0.4737    0.1579
+  band No.  band energies     occupation 
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+
+ k-point 216 :      -0.3158    0.4737    0.1579
+  band No.  band energies     occupation 
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+      3       8.1449      0.02051
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+
+ k-point 217 :      -0.3684    0.4211    0.2105
+  band No.  band energies     occupation 
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+      3       9.4964      0.00000
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+      6      23.5208      0.00000
+
+ k-point 218 :      -0.3158    0.4211    0.2105
+  band No.  band energies     occupation 
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+
+ k-point 219 :      -0.3158    0.4737    0.2105
+  band No.  band energies     occupation 
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+
+ k-point 220 :      -0.2632    0.4737    0.2105
+  band No.  band energies     occupation 
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+      6      24.6219      0.00000
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+ soft charge-density along one line, spin component            1
+         0         1         2         3         4         5         6         7         8         9
+ total charge-density along one line
+ 
+ soft charge-density along one line, spin component            2
+         0         1         2         3         4         5         6         7         8         9
+ total charge-density along one line
+ 
+ pseudopotential strength for first ion, spin component:            1
+  8.442  -0.006   0.000   0.000   0.000   0.000   0.000   0.000
+ -0.006   0.000   0.000   0.000   0.000   0.000   0.000   0.000
+  0.000   0.000   1.988   0.000   0.000  -0.027   0.000   0.000
+  0.000   0.000   0.000   1.988   0.000   0.000  -0.027   0.000
+  0.000   0.000   0.000   0.000   1.988   0.000   0.000  -0.027
+  0.000   0.000  -0.027   0.000   0.000  -0.012   0.000   0.000
+  0.000   0.000   0.000  -0.027   0.000   0.000  -0.012   0.000
+  0.000   0.000   0.000   0.000  -0.027   0.000   0.000  -0.012
+ pseudopotential strength for first ion, spin component:            2
+  8.442  -0.006   0.000   0.000   0.000   0.000   0.000   0.000
+ -0.006   0.000   0.000   0.000   0.000   0.000   0.000   0.000
+  0.000   0.000   1.988   0.000   0.000  -0.027   0.000   0.000
+  0.000   0.000   0.000   1.988   0.000   0.000  -0.027   0.000
+  0.000   0.000   0.000   0.000   1.988   0.000   0.000  -0.027
+  0.000   0.000  -0.027   0.000   0.000  -0.012   0.000   0.000
+  0.000   0.000   0.000  -0.027   0.000   0.000  -0.012   0.000
+  0.000   0.000   0.000   0.000  -0.027   0.000   0.000  -0.012
+ total augmentation occupancy for first ion, spin component:            1
+  1.315  -0.489   0.000   0.000   0.000   0.000   0.000   0.000
+ -0.489   0.477   0.000   0.000   0.000   0.000   0.000   0.000
+  0.000   0.000   0.742   0.000   0.000  -0.149   0.000   0.000
+  0.000   0.000   0.000   0.742   0.000   0.000  -0.149   0.000
+  0.000   0.000   0.000   0.000   0.742   0.000   0.000  -0.149
+  0.000   0.000  -0.149   0.000   0.000   0.035   0.000   0.000
+  0.000   0.000   0.000  -0.149   0.000   0.000   0.035   0.000
+  0.000   0.000   0.000   0.000  -0.149   0.000   0.000   0.035
+ total augmentation occupancy for first ion, spin component:            2
+  0.000   0.000   0.000   0.000   0.000   0.000   0.000   0.000
+  0.000   0.000   0.000   0.000   0.000   0.000   0.000   0.000
+  0.000   0.000   0.000   0.000   0.000   0.000   0.000   0.000
+  0.000   0.000   0.000   0.000   0.000   0.000   0.000   0.000
+  0.000   0.000   0.000   0.000   0.000   0.000   0.000   0.000
+  0.000   0.000   0.000   0.000   0.000   0.000   0.000   0.000
+  0.000   0.000   0.000   0.000   0.000   0.000   0.000   0.000
+  0.000   0.000   0.000   0.000   0.000   0.000   0.000   0.000
+
+
+------------------------ aborting loop because EDIFF is reached ----------------------------------------
+
+
+ 
+
+
+ total charge     
+ 
+# of ion     s       p       d       tot
+----------------------------------------
+  1        0.425   0.343   0.000   0.768
+ 
+
+
+ magnetization (x)
+ 
+# of ion     s       p       d       tot
+----------------------------------------
+  1        0.000   0.000   0.000   0.000
+ 
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+
+  FREE ENERGIE OF THE ION-ELECTRON SYSTEM (eV)
+  ---------------------------------------------------
+  free  energy   TOTEN  =        -3.743359 eV
+
+  energy  without entropy=       -3.743359  energy(sigma->0) =       -3.743359
+ 
+    CHARGE:  cpu time    0.10: real time    0.10
+    FORLOC:  cpu time    0.00: real time    0.00
+    FORNL :  cpu time    0.28: real time    0.28
+    STRESS:  cpu time    0.82: real time    0.82
+    FORCOR:  cpu time    0.06: real time    0.06
+    FORHAR:  cpu time    0.01: real time    0.01
+    MIXING:  cpu time    0.00: real time    0.00
+
+  FORCE on cell =-STRESS in cart. coord.  units (eV):
+  Direction    XX          YY          ZZ          XY          YZ          ZX
+  --------------------------------------------------------------------------------------
+  Alpha Z    -0.20487    -0.20487    -0.20487
+  Ewald     -24.55751   -24.55751   -24.55751     0.00000     0.00000     0.00000
+  Hartree     0.03549     0.03549     0.03549     0.00000     0.00000     0.00000
+  E(xc)      -8.57786    -8.57786    -8.57786     0.00000     0.00000     0.00000
+  Local       0.39110     0.39110     0.39110     0.00000     0.00000     0.00000
+  n-local    18.94530    18.59888    19.03840     0.46272    -0.60732     0.54193
+  augment    -1.01915    -1.01915    -1.01915     0.00000     0.00000     0.00000
+  Kinetic    12.48013    11.05239    21.71112    -9.68929     8.44714    -6.26264
+  Fock        0.00000     0.00000     0.00000     0.00000     0.00000     0.00000
+  -------------------------------------------------------------------------------------
+  Total       0.00927     0.00927     0.00927     0.00000     0.00000     0.00000
+  in kB       0.90594     0.90594     0.90594     0.00000     0.00000     0.00000
+  external pressure =        0.91 kB  Pullay stress =        0.00 kB
+
+
+ VOLUME and BASIS-vectors are now :
+ -----------------------------------------------------------------------------
+  energy-cutoff  :      520.00
+  volume of cell :       16.39
+      direct lattice vectors                 reciprocal lattice vectors
+     0.000000000  2.016319000  2.016319000    -0.247976635  0.247976635  0.247976635
+     2.016319000  0.000000000  2.016319000     0.247976635 -0.247976635  0.247976635
+     2.016319000  2.016319000  0.000000000     0.247976635  0.247976635 -0.247976635
+
+  length of vectors
+     2.851505676  2.851505676  2.851505676     0.429508130  0.429508130  0.429508130
+
+
+ FORCES acting on ions
+    electron-ion (+dipol)            ewald-force                    non-local-force                 convergence-correction
+ -----------------------------------------------------------------------------------------------
+   -.178E-15 0.423E-16 -.250E-14   -.794E-16 -.361E-16 0.105E-15   0.000E+00 -.207E-24 0.207E-24   -.803E-17 -.461E-17 -.195E-17
+ -----------------------------------------------------------------------------------------------
+   -.178E-15 0.423E-16 -.250E-14   -.794E-16 -.361E-16 0.105E-15   0.000E+00 -.207E-24 0.207E-24   -.803E-17 -.461E-17 -.195E-17
+ 
+ 
+ POSITION                                       TOTAL-FORCE (eV/Angst)
+ -----------------------------------------------------------------------------------
+      0.00000      0.00000      0.00000         0.000000      0.000000      0.000000
+ -----------------------------------------------------------------------------------
+    total drift:                                0.000000      0.000000      0.000000
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+    POTLOK:  cpu time    0.03: real time    0.03
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+  FORCES: max atom, RMS     0.000000    0.000000
+  FORCE total and by dimension    0.000000    0.000000
+     LOOP+:  cpu time   46.44: real time   46.60
+    4ORBIT:  cpu time    0.00: real time    0.00
+ 
+
+
+ total charge     
+ 
+# of ion     s       p       d       tot
+----------------------------------------
+  1        0.425   0.343   0.000   0.768
+ 
+
+
+ magnetization (x)
+ 
+# of ion     s       p       d       tot
+----------------------------------------
+  1        0.000   0.000   0.000   0.000
+ 
+ BZINTS: Fermi energy:  8.094245;  3.000000 electrons
+         Band energy:  10.876169;  BLOECHL correction: -0.041851
+
+ total amount of memory used by VASP on root node  33617. kBytes
+========================================================================
+
+   base      :    30000. kBytes
+   nonl-proj :      451. kBytes
+   fftplans  :      185. kBytes
+   grid      :     2131. kBytes
+   one-center:        6. kBytes
+   wavefun   :      844. kBytes
+ 
+  
+  
+ General timing and accounting informations for this job:
+ ========================================================
+  
+                  Total CPU time used (sec):       50.194
+                            User time (sec):       49.602
+                          System time (sec):        0.592
+                         Elapsed time (sec):       52.337
+  
+                   Maximum memory used (kb):       62900.
+                   Average memory used (kb):           0.
+  
+                          Minor page faults:       277580
+                          Major page faults:            5
+                 Voluntary context switches:        18669
diff --git a/notebooks/Al-relax/POSCAR b/notebooks/Al-relax/POSCAR
new file mode 100644
index 0000000..f5f2674
--- /dev/null
+++ b/notebooks/Al-relax/POSCAR
@@ -0,0 +1,9 @@
+Al1
+1.0
+   0.8248881578741932    2.3331360406132857    1.4287482000000002
+   0.8248881578741932    2.3331360406132857   -1.4287481999999998
+  -1.6497763157483862    2.3331360406132857   -0.0000000000000000
+Al
+1
+direct
+   0.0000000000000000    0.0000000000000000    0.0000000000000000 Al
diff --git a/notebooks/Al-relax/POTCAR b/notebooks/Al-relax/POTCAR
new file mode 100644
index 0000000..c8d9ecb
--- /dev/null
+++ b/notebooks/Al-relax/POTCAR
@@ -0,0 +1,1768 @@
+ PAW_PBE Al 04Jan2001
+ 3.00000000000000000
+ parameters from PSCTR are:
+   VRHFIN =Al: s2p1
+   LEXCH  = PE
+   EATOM  =    53.5387 eV,    3.9350 Ry
+
+   TITEL  = PAW_PBE Al 04Jan2001
+   LULTRA =        F    use ultrasoft PP ?
+   IUNSCR =        1    unscreen: 0-lin 1-nonlin 2-no
+   RPACOR =    1.500    partial core radius
+   POMASS =   26.982; ZVAL   =    3.000    mass and valenz
+   RCORE  =    1.900    outmost cutoff radius
+   RWIGS  =    2.650; RWIGS  =    1.402    wigner-seitz radius (au A)
+   ENMAX  =  240.300; ENMIN  =  180.225 eV
+   ICORE  =        2    local potential
+   LCOR   =        T    correct aug charges
+   LPAW   =        T    paw PP
+   EAUG   =  291.052
+   DEXC   =    -.041
+   RMAX   =    2.974    core radius for proj-oper
+   RAUG   =    1.300    factor for augmentation sphere
+   RDEP   =    1.966    radius for radial grids
+   QCUT   =   -4.203; QGAM   =    8.405    optimization parameters
+ 
+   Description
+     l     E      TYP  RCUT    TYP  RCUT
+     0   .000     23  1.900
+     0   .000     23  1.900
+     1   .000     23  1.900
+     1  1.000     23  1.900
+     2   .000      7  1.900
+   Error from kinetic energy argument (eV)
+   NDATA  =      100
+   STEP   =   20.000   1.050
+  2.17      1.95      1.85      1.68      1.61      1.48      1.37      1.32
+  1.24      1.17      1.14      1.08      1.03      .977      .931      .886
+  .843      .801      .758      .695      .653      .611      .549      .509
+  .469      .413      .359      .325      .278      .235      .197      .163
+  .133      .107      .858E-01  .676E-01  .483E-01  .370E-01  .256E-01  .193E-01
+  .132E-01  .922E-02  .676E-02  .535E-02  .461E-02  .426E-02  .410E-02  .397E-02
+  .383E-02  .358E-02  .322E-02  .288E-02  .243E-02  .199E-02  .152E-02  .120E-02
+  .964E-03  .771E-03  .660E-03  .604E-03  .576E-03  .555E-03  .527E-03  .479E-03
+  .425E-03  .355E-03  .288E-03  .231E-03  .185E-03  .161E-03  .147E-03  .140E-03
+  .133E-03  .123E-03  .108E-03  .913E-04  .740E-04  .607E-04  .519E-04  .482E-04
+  .459E-04  .430E-04  .384E-04  .320E-04  .261E-04  .219E-04  .198E-04  .188E-04
+  .176E-04  .155E-04  .128E-04  .107E-04  .933E-05  .881E-05  .825E-05  .723E-05
+  .594E-05  .506E-05  .462E-05  .439E-05
+END of PSCTR-controll parameters
+ local part
+ 98.2657514061040160
+  -.11196040E+01  -.11177563E+01  -.11049391E+01  -.10835857E+01  -.10537102E+01
+  -.10153337E+01  -.96848653E+00  -.91320931E+00  -.84955472E+00  -.77758869E+00
+  -.69739125E+00  -.60905702E+00  -.51269522E+00  -.40842942E+00  -.29639696E+00
+  -.17674840E+00  -.49646910E-01   .84732128E-01   .22620132E+00   .37456122E+00
+   .52960001E+00   .69109312E+00   .85880261E+00   .10324767E+01   .12118494E+01
+   .13966402E+01   .15865537E+01   .17812803E+01   .19804960E+01   .21838631E+01
+   .23910305E+01   .26016344E+01   .28152987E+01   .30316358E+01   .32502469E+01
+   .34707226E+01   .36926434E+01   .39155809E+01   .41390977E+01   .43627492E+01
+   .45860841E+01   .48086459E+01   .50299739E+01   .52496049E+01   .54670742E+01
+   .56819175E+01   .58936719E+01   .61018779E+01   .63060802E+01   .65058297E+01
+   .67006847E+01   .68902126E+01   .70739913E+01   .72516109E+01   .74226751E+01
+   .75868032E+01   .77436311E+01   .78928134E+01   .80340244E+01   .81669598E+01
+   .82913377E+01   .84069000E+01   .85134133E+01   .86106704E+01   .86984902E+01
+   .87767197E+01   .88452338E+01   .89039366E+01   .89527612E+01   .89916710E+01
+   .90206591E+01   .90397490E+01   .90489941E+01   .90484779E+01   .90383136E+01
+   .90186433E+01   .89896376E+01   .89514949E+01   .89044406E+01   .88487257E+01
+   .87846262E+01   .87124416E+01   .86324938E+01   .85451255E+01   .84506988E+01
+   .83495936E+01   .82422058E+01   .81289454E+01   .80102351E+01   .78865077E+01
+   .77582050E+01   .76257751E+01   .74896708E+01   .73503477E+01   .72082620E+01
+   .70638688E+01   .69176200E+01   .67699625E+01   .66213364E+01   .64721729E+01
+   .63228932E+01   .61739059E+01   .60256063E+01   .58783742E+01   .57325732E+01
+   .55885488E+01   .54466274E+01   .53071157E+01   .51702992E+01   .50364417E+01
+   .49057846E+01   .47785463E+01   .46549220E+01   .45350830E+01   .44191768E+01
+   .43073272E+01   .41996341E+01   .40961740E+01   .39970001E+01   .39021431E+01
+   .38116117E+01   .37253931E+01   .36434544E+01   .35657426E+01   .34921864E+01
+   .34226972E+01   .33571695E+01   .32954831E+01   .32375038E+01   .31830845E+01
+   .31320672E+01   .30842840E+01   .30395585E+01   .29977073E+01   .29585414E+01
+   .29218677E+01   .28874903E+01   .28552118E+01   .28248347E+01   .27961629E+01
+   .27690023E+01   .27431629E+01   .27184590E+01   .26947108E+01   .26717452E+01
+   .26493969E+01   .26275089E+01   .26059335E+01   .25845330E+01   .25631799E+01
+   .25417576E+01   .25201610E+01   .24982963E+01   .24760814E+01   .24534460E+01
+   .24303316E+01   .24066915E+01   .23824903E+01   .23577042E+01   .23323202E+01
+   .23063359E+01   .22797592E+01   .22526073E+01   .22249067E+01   .21966922E+01
+   .21680063E+01   .21388985E+01   .21094246E+01   .20796458E+01   .20496280E+01
+   .20194410E+01   .19891578E+01   .19588534E+01   .19286048E+01   .18984891E+01
+   .18685840E+01   .18389659E+01   .18097100E+01   .17808892E+01   .17525735E+01
+   .17248297E+01   .16977205E+01   .16713039E+01   .16456335E+01   .16207571E+01
+   .15967173E+01   .15735503E+01   .15512867E+01   .15299505E+01   .15095593E+01
+   .14901245E+01   .14716508E+01   .14541366E+01   .14375742E+01   .14219496E+01
+   .14072432E+01   .13934295E+01   .13804780E+01   .13683532E+01   .13570150E+01
+   .13464191E+01   .13365178E+01   .13272599E+01   .13185916E+01   .13104567E+01
+   .13027974E+01   .12955544E+01   .12886679E+01   .12820776E+01   .12757238E+01
+   .12695472E+01   .12634899E+01   .12574955E+01   .12515099E+01   .12454814E+01
+   .12393609E+01   .12331030E+01   .12266652E+01   .12200092E+01   .12131006E+01
+   .12059089E+01   .11984084E+01   .11905774E+01   .11823990E+01   .11738609E+01
+   .11649554E+01   .11556790E+01   .11460332E+01   .11360233E+01   .11256591E+01
+   .11149544E+01   .11039267E+01   .10925970E+01   .10809897E+01   .10691322E+01
+   .10570544E+01   .10447889E+01   .10323701E+01   .10198341E+01   .10072184E+01
+   .99456157E+00   .98190254E+00   .96928066E+00   .95673512E+00   .94430466E+00
+   .93202719E+00   .91993953E+00   .90807705E+00   .89647343E+00   .88516034E+00
+   .87416725E+00   .86352116E+00   .85324641E+00   .84336455E+00   .83389411E+00
+   .82485055E+00   .81624616E+00   .80808994E+00   .80038765E+00   .79314177E+00
+   .78635153E+00   .78001295E+00   .77411896E+00   .76865948E+00   .76362154E+00
+   .75898945E+00   .75474496E+00   .75086744E+00   .74733410E+00   .74412021E+00
+   .74119930E+00   .73854345E+00   .73612354E+00   .73390947E+00   .73187046E+00
+   .72997532E+00   .72819269E+00   .72649130E+00   .72484025E+00   .72320923E+00
+   .72156876E+00   .71989041E+00   .71814702E+00   .71631290E+00   .71436401E+00
+   .71227812E+00   .71003497E+00   .70761640E+00   .70500645E+00   .70219144E+00
+   .69916008E+00   .69590344E+00   .69241507E+00   .68869088E+00   .68472926E+00
+   .68053091E+00   .67609888E+00   .67143844E+00   .66655704E+00   .66146414E+00
+   .65617115E+00   .65069124E+00   .64503924E+00   .63923144E+00   .63328543E+00
+   .62721994E+00   .62105463E+00   .61480989E+00   .60850669E+00   .60216637E+00
+   .59581042E+00   .58946034E+00   .58313743E+00   .57686262E+00   .57065631E+00
+   .56453816E+00   .55852699E+00   .55264061E+00   .54689569E+00   .54130761E+00
+   .53589042E+00   .53065665E+00   .52561734E+00   .52078189E+00   .51615804E+00
+   .51175188E+00   .50756777E+00   .50360837E+00   .49987464E+00   .49636590E+00
+   .49307982E+00   .49001248E+00   .48715848E+00   .48451095E+00   .48206169E+00
+   .47980125E+00   .47771902E+00   .47580340E+00   .47404184E+00   .47242104E+00
+   .47092705E+00   .46954540E+00   .46826124E+00   .46705948E+00   .46592488E+00
+   .46484227E+00   .46379657E+00   .46277299E+00   .46175715E+00   .46073512E+00
+   .45969364E+00   .45862012E+00   .45750279E+00   .45633075E+00   .45509406E+00
+   .45378380E+00   .45239211E+00   .45091224E+00   .44933855E+00   .44766658E+00
+   .44589301E+00   .44401568E+00   .44203358E+00   .43994683E+00   .43775665E+00
+   .43546528E+00   .43307601E+00   .43059306E+00   .42802151E+00   .42536728E+00
+   .42263700E+00   .41983797E+00   .41697805E+00   .41406555E+00   .41110920E+00
+   .40811802E+00   .40510122E+00   .40206815E+00   .39902816E+00   .39599055E+00
+   .39296446E+00   .38995882E+00   .38698221E+00   .38404286E+00   .38114852E+00
+   .37830644E+00   .37552327E+00   .37280509E+00   .37015726E+00   .36758449E+00
+   .36509075E+00   .36267929E+00   .36035258E+00   .35811235E+00   .35595957E+00
+   .35389448E+00   .35191657E+00   .35002463E+00   .34821677E+00   .34649046E+00
+   .34484257E+00   .34326943E+00   .34176684E+00   .34033018E+00   .33895442E+00
+   .33763421E+00   .33636392E+00   .33513771E+00   .33394960E+00   .33279351E+00
+   .33166334E+00   .33055302E+00   .32945660E+00   .32836826E+00   .32728240E+00
+   .32619367E+00   .32509703E+00   .32398781E+00   .32286171E+00   .32171486E+00
+   .32054384E+00   .31934568E+00   .31811795E+00   .31685867E+00   .31556640E+00
+   .31424021E+00   .31287967E+00   .31148487E+00   .31005638E+00   .30859525E+00
+   .30710298E+00   .30558148E+00   .30403308E+00   .30246045E+00   .30086657E+00
+   .29925473E+00   .29762844E+00   .29599140E+00   .29434749E+00   .29270065E+00
+   .29105493E+00   .28941437E+00   .28778299E+00   .28616474E+00   .28456345E+00
+   .28298281E+00   .28142629E+00   .27989715E+00   .27839838E+00   .27693268E+00
+   .27550242E+00   .27410965E+00   .27275604E+00   .27144291E+00   .27017118E+00
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+ gradient corrections used for XC
+ 5
+ core charge-density (partial)
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+   .50526239E+01   .46452503E+01   .42484496E+01   .38642423E+01   .34944874E+01
+   .31408551E+01   .28048028E+01   .24875556E+01   .21900922E+01   .19131367E+01
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+   .69070857E+00   .55673541E+00   .44052363E+00   .34092076E+00   .25667855E+00
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+  -.29913685E-01  -.27554490E-01  -.24109477E-01  -.20061646E-01  -.15797484E-01
+  -.11614647E-01  -.77308590E-02  -.42936222E-02  -.13903576E-02   .94138527E-03
+   .27039652E-02   .39302082E-02   .46747130E-02   .50060754E-02   .50001483E-02
+   .47344072E-02   .42834371E-02   .37155182E-02   .30902480E-02   .24571077E-02
+   .18548572E-02   .13116297E-02   .84558522E-03   .46598444E-03   .17454639E-03
+  -.33035122E-04  -.16552831E-03  -.23464831E-03  -.25366604E-03  -.23619783E-03
+ Reciprocal Space Part
+   .22782613E+02   .23315036E+02   .24902461E+02   .27515550E+02   .31106045E+02
+   .35607707E+02   .40937615E+02   .46997770E+02   .53677000E+02   .60853104E+02
+   .68395199E+02   .76166219E+02   .84025512E+02   .91831484E+02   .99444233E+02
+   .10672812E+03   .11355423E+03   .11980265E+03   .12536457E+03   .13014412E+03
+   .13405990E+03   .13704626E+03   .13905420E+03   .14005194E+03   .14002513E+03
+   .13897680E+03   .13692684E+03   .13391124E+03   .12998106E+03   .12520107E+03
+   .11964820E+03   .11340978E+03   .10658163E+03   .99266060E+02   .91569770E+02
+   .83601783E+02   .75471360E+02   .67286004E+02   .59149575E+02   .51160538E+02
+   .43410401E+02   .35982338E+02   .28950054E+02   .22376876E+02   .16315096E+02
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+  -.74847025E+00  -.61481243E+00  -.46932237E+00  -.31847831E+00  -.16838293E+00
+ Real Space Part
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+   .67765642E+03   .67653890E+03   .67472952E+03   .67201476E+03   .66817044E+03
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+   .50004563E+03   .47159452E+03   .44132659E+03   .40948792E+03   .37636085E+03
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+   .23015018E+02  -.17530555E-02  -.20552589E+02  -.38558389E+02  -.53985185E+02
+  -.66842894E+02  -.77183055E+02  -.85095653E+02  -.90705160E+02  -.94165948E+02
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+  -.80896089E+02  -.75040500E+02  -.68713826E+02  -.62106548E+02  -.55392046E+02
+  -.48724413E+02  -.42236960E+02  -.36041382E+02  -.30227573E+02  -.24864026E+02
+  -.19998753E+02  -.15660655E+02  -.11861258E+02  -.85967224E+01  -.58500506E+01
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+   .15854000E+01   .13186656E+01   .10410237E+01   .77027522E+00   .51963802E+00
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+  -.51387033E-01  -.29662701E-01  -.13337670E-01  -.20265672E-02   .49177022E-02
+ Non local Part
+ 1 2 1.57396957515338021
+ 2.08596921736620722 -0.219845133596054454 -0.219845133596054454 0.318470468308045818E-01
+ Reciprocal Space Part
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+   .77198561E+01   .72832654E+01   .68229055E+01   .63451509E+01   .58562434E+01
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+   .14748080E-02   .41388000E-02   .64128687E-02   .82390791E-02   .95819716E-02
+ Real Space Part
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+ Reciprocal Space Part
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+ Real Space Part
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+ PAW radial sets
+ 323 1.04059493489918520
+(5E20.12)                                
+ augmentation charges (non sperical)
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+   .601327217851E-03
+ uccopancies in atom
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+ grid
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+ kinetic energy-density
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+ pspotential
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+  -.220380384758E+02  -.217680844180E+02  -.215405378949E+02
+ core charge-density (pseudized)
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+   .312434410583E-07   .333083950054E-07   .355098267098E-07   .378567563134E-07   .403588001211E-07
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+   .112371398891E-06   .119798293963E-06   .127716050314E-06   .136157110139E-06   .145156059816E-06
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+ pseudo wavefunction
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+ ae wavefunction
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+   .209425579900E-02   .255877148356E-02   .303197903813E-02   .351289038583E-02   .400045935951E-02
+   .449358491434E-02   .499111449780E-02   .549184789751E-02   .599454203852E-02   .649791720417E-02
+   .700066495056E-02   .750145762264E-02   .799895902097E-02   .849183558674E-02   .897876752013E-02
+   .945845942579E-02   .992965024698E-02   .103911223243E-01   .108417093948E-01   .112803032765E-01
+   .117058588972E-01   .121173972601E-01   .125140058923E-01   .128948362979E-01   .132590979347E-01
+   .136060482342E-01   .139349781989E-01   .142451931268E-01   .145359880292E-01   .148066173351E-01
+   .150562584989E-01   .152839691643E-01   .154886375714E-01   .156689259419E-01   .158232066241E-01
+   .159494908365E-01   .160453499067E-01   .161078289685E-01   .161333531430E-01   .161176262967E-01
+   .160555225330E-01   .159409706311E-01   .157668317025E-01   .155247703815E-01   .152051199191E-01
+   .147967416081E-01   .142868790633E-01   .136610080333E-01   .129026826654E-01   .119933795112E-01
+   .109123410538E-01   .963642112230E-02   .813993513239E-02   .639451848116E-02   .436899635077E-02
+   .202926726703E-02  -.661799589696E-03  -.374445792893E-02  -.726218107493E-02  -.112617840548E-01
+  -.157935974468E-01  -.209116960300E-01  -.266741034650E-01  -.331427650790E-01  -.403830423964E-01
+  -.484627327506E-01  -.574510452014E-01  -.674180448767E-01  -.784346356823E-01  -.905727218722E-01
+  -.103905208579E+00  -.118505750633E+00  -.134448326467E+00
+ pseudo wavefunction
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+   .183334456260E-08   .195451470241E-08   .208369326740E-08   .222140955360E-08   .236822783949E-08
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+   .347690290587E-08   .370669975883E-08   .395168443700E-08   .421286074014E-08   .449129881161E-08
+   .478813952305E-08   .510459914909E-08   .544197435083E-08   .580164748884E-08   .618509228720E-08
+   .659387987194E-08   .702968520859E-08   .749429396517E-08   .798960982877E-08   .851766230572E-08
+   .908061503730E-08   .968077466501E-08   .103206002818E-07   .110027135081E-07   .117299092333E-07
+   .125051670679E-07   .133316635520E-07   .142127851706E-07   .151521422299E-07   .161535836498E-07
+   .172212127344E-07   .183594039852E-07   .195728210249E-07   .208664357062E-07   .222455484833E-07
+   .237158101304E-07   .252832448946E-07   .269542751801E-07   .287357478631E-07   .306349623463E-07
+   .326597004672E-07   .348182583838E-07   .371194805669E-07   .395727960394E-07   .421882570112E-07
+   .449765800663E-07   .479491900739E-07   .511182669997E-07   .544967958124E-07   .580986196887E-07
+   .619384967333E-07   .660321604498E-07   .703963842063E-07   .750490499627E-07   .800092215405E-07
+   .852972227344E-07   .909347205873E-07   .969448141681E-07   .103352129219E-06   .110182919054E-06
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+   .546511115461E-05   .582631261717E-05   .621138663568E-05   .662191098893E-05   .705956773270E-05
+   .752615009147E-05   .802356980543E-05   .855386496313E-05   .911920835169E-05   .972191635886E-05
+   .103644584634E-04   .110494673526E-04   .117797497084E-04   .125582977061E-04   .133883012737E-04
+   .142731611601E-04   .152165028680E-04   .162221915069E-04   .172943476278E-04   .184373641041E-04
+   .196559241281E-04   .209550203968E-04   .223399755647E-04   .238164640491E-04   .253905352753E-04
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+   .372768211008E-04   .397404963976E-04   .423669965479E-04   .451670823054E-04   .481522255278E-04
+   .513346561620E-04   .547274123325E-04   .583443937379E-04   .622004185747E-04   .663112842199E-04
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+   .184622403081E-03   .196823578222E-03   .209831026887E-03   .223698019683E-03   .238481345548E-03
+   .254241543954E-03   .271043152408E-03   .288954970255E-03   .308050339867E-03   .328407446344E-03
+   .350109636944E-03   .373245761542E-03   .397910535495E-03   .424204926370E-03   .452236566111E-03
+   .482120190301E-03   .513978106289E-03   .547940692074E-03   .584146927946E-03   .622744963025E-03
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+   .914173344703E-03   .974569647200E-03   .103895446282E-02   .110759096184E-02   .118075964800E-02
+   .125875949591E-02   .134190916251E-02   .143054827732E-02   .152503881654E-02   .162576656628E-02
+   .173314268072E-02   .184760534097E-02   .196962152135E-02   .209968886953E-02   .223833770784E-02
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+   .328482362453E-02   .350162020869E-02   .373270371981E-02   .397901272557E-02   .424154704933E-02
+   .452137171268E-02   .481962112414E-02   .513750352831E-02   .547630573036E-02   .583739811165E-02
+   .622223995268E-02   .663238508052E-02   .706948785838E-02   .753530953579E-02   .803172497818E-02
+   .856072979583E-02   .912444789202E-02   .972513945132E-02   .103652093890E-01   .110472162826E-01
+   .117738818084E-01   .125481007026E-01   .133729512699E-01   .142517064607E-01   .151878455364E-01
+   .161850663428E-01   .172472982095E-01   .183787154915E-01   .195837517683E-01   .208671147088E-01
+   .222338016123E-01   .236891156275E-01   .252386826469E-01   .268884688684E-01   .286447990070E-01
+   .305143751326E-01   .325042960946E-01   .346220774867E-01   .368756720868E-01   .392734906897E-01
+   .418244232320E-01   .445378600833E-01   .474237133502E-01   .504924380113E-01   .537550526608E-01
+   .572231596002E-01   .609089639691E-01   .648252915511E-01   .689856048286E-01   .734040167922E-01
+   .780953019260E-01   .830749037029E-01   .883589378200E-01   .939641902873E-01   .999081093538E-01
+   .106208790109E+00   .112884950436E+00   .119955896798E+00   .127441478171E+00   .135362026158E+00
+   .143738279134E+00   .152591287954E+00   .161942300494E+00   .171812621956E+00   .182223447546E+00
+   .193195663779E+00   .204749614243E+00   .216904825343E+00   .229679687068E+00   .243091083498E+00
+   .257153967352E+00   .271880872583E+00   .287281358692E+00   .303361380299E+00   .320122575380E+00
+   .337561465696E+00   .355668563209E+00   .374427376879E+00   .393813315081E+00   .413792480267E+00
+   .434320354257E+00   .455340375011E+00   .476782408851E+00   .498561126029E+00   .520574292433E+00
+   .542700996041E+00   .564799833758E+00   .586707092354E+00   .608234966517E+00   .629169867457E+00
+   .649270886979E+00   .668262260299E+00   .685893169926E+00
+ ae wavefunction
+  -.149505582373E-06  -.158684965801E-06  -.168373300955E-06  -.178601994723E-06  -.189404262408E-06
+  -.200815242302E-06  -.212872117373E-06  -.225614244418E-06  -.239083291145E-06  -.253323381732E-06
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+  -.476448250092E-06  -.504519943256E-06  -.534245370089E-06  -.565724634229E-06  -.599063971277E-06
+  -.634376135665E-06  -.671780812241E-06  -.711405054173E-06  -.753383748909E-06  -.797860113989E-06
+  -.844986224696E-06  -.894923575589E-06  -.947843678147E-06  -.100392869688E-05  -.106337212641E-05
+  -.112637951221E-05  -.119316921779E-05  -.126397324152E-05  -.133903808605E-05  -.141862568413E-05
+  -.150301438409E-05  -.159249999928E-05  -.168739692528E-05  -.178803932958E-05  -.189478241826E-05
+  -.200800378480E-05  -.212810484629E-05  -.225551237281E-05  -.239068011599E-05  -.253409054315E-05
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+  -.105518094467E+00  -.110234646902E+00  -.115092198098E+00  -.120088797993E+00  -.125221809366E+00
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+  -.189088587304E+00  -.195331656713E+00  -.201591101926E+00  -.207849609871E+00  -.214088595263E+00
+  -.220288195385E+00  -.226427260488E+00  -.232483334149E+00  -.238432619583E+00  -.244249932105E+00
+  -.249908644235E+00  -.255380636697E+00  -.260636273486E+00  -.265644419670E+00  -.270372514978E+00
+  -.274786704899E+00  -.278852018072E+00  -.282532570444E+00  -.285791777038E+00  -.288592559744E+00
+  -.290897548690E+00  -.292669280874E+00  -.293870401343E+00  -.294463870745E+00  -.294413180554E+00
+  -.293682574976E+00  -.292237277195E+00  -.290043717032E+00  -.287069757193E+00  -.283284915648E+00
+  -.278660582246E+00  -.273170228144E+00  -.266789607105E+00  -.259496948068E+00  -.251273138693E+00
+  -.242101899829E+00  -.231969950973E+00  -.220867166935E+00  -.208786725890E+00  -.195725248958E+00
+  -.181682931238E+00  -.166663663928E+00  -.150675146767E+00  -.133728989485E+00  -.115840800401E+00
+  -.970302596804E-01  -.773211742724E-01  -.567415111985E-01  -.353234059014E-01  -.131031429059E-01
+   .987889271489E-02   .335782925354E-01   .579467273280E-01   .829320684585E-01   .108478518711E+00
+   .134526741605E+00   .161013979627E+00   .187874157546E+00   .215037978724E+00   .242433041116E+00
+   .269984027290E+00   .297613060516E+00   .325240366777E+00   .352785425661E+00   .380168774790E+00
+   .407314412127E+00   .434152115512E+00   .460617977852E+00   .486650873420E+00   .512184171168E+00
+   .537136184083E+00   .561405621993E+00   .584875060089E+00   .607419122107E+00   .628912003402E+00
+   .649231811059E+00   .668262260299E+00   .685893169926E+00
+ pseudo wavefunction
+   .282759401026E-09   .301447648040E-09   .321371046118E-09   .342611229356E-09   .365255227241E-09
+   .389395821249E-09   .415131925007E-09   .442568989578E-09   .471819435541E-09   .503003113617E-09
+   .536247795753E-09   .571689698646E-09   .609474041883E-09   .649755642960E-09   .692699551632E-09
+   .738481726189E-09   .787289754423E-09   .839323622256E-09   .894796533154E-09   .953935781713E-09
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diff --git a/notebooks/Al-static/INCAR b/notebooks/Al-static/INCAR
new file mode 100644
index 0000000..41617cb
--- /dev/null
+++ b/notebooks/Al-static/INCAR
@@ -0,0 +1,23 @@
+ALGO = All
+EDIFF = 1e-05
+ENAUG = 1360.0
+ENCUT = 680.0
+ICHARG = 1
+ISMEAR = -5
+ISPIN = 2
+KPOINT_BSE = -1 0 0 0
+LAECHG = True
+LASPH = True
+LCHARG = True
+LELF = True
+LMIXTAU = -1
+LORBIT = 11
+LREAL = False
+LVTOT = True
+LWAVE = False
+MAGMOM = 1*0.6
+METAGGA = R2scan
+NELM = 60
+NSW = 0
+PREC = Accurate
+SIGMA = 0.5
diff --git a/notebooks/Al-static/KPOINTS b/notebooks/Al-static/KPOINTS
new file mode 100644
index 0000000..0594750
--- /dev/null
+++ b/notebooks/Al-static/KPOINTS
@@ -0,0 +1,4 @@
+pymatgen with grid density = 1503 / number of atoms
+0
+Gamma
+11 11 11
diff --git a/notebooks/Al-static/OUTCAR b/notebooks/Al-static/OUTCAR
new file mode 100644
index 0000000..831bddd
--- /dev/null
+++ b/notebooks/Al-static/OUTCAR
@@ -0,0 +1,6202 @@
+ vasp.5.2.2 15Apr09 complex 
+ executed on              unknown date 2014.10.30  16:25:45
+ running on   32 nodes
+ distr:  one band on   16 nodes,    2 groups
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+ INCAR:
+ POTCAR:   PAW_PBE Al 04Jan2001                   
+ POTCAR:   PAW_PBE Al 04Jan2001                   
+   VRHFIN =Al: s2p1                                                             
+   LEXCH  = PE                                                                  
+   EATOM  =    53.5387 eV,    3.9350 Ry                                         
+                                                                                
+   TITEL  = PAW_PBE Al 04Jan2001                                                
+   LULTRA =        F    use ultrasoft PP ?                                      
+   IUNSCR =        1    unscreen: 0-lin 1-nonlin 2-no                           
+   RPACOR =    1.500    partial core radius                                     
+   POMASS =   26.982; ZVAL   =    3.000    mass and valenz                      
+   RCORE  =    1.900    outmost cutoff radius                                   
+   RWIGS  =    2.650; RWIGS  =    1.402    wigner-seitz radius (au A)           
+   ENMAX  =  240.300; ENMIN  =  180.225 eV                                      
+   ICORE  =        2    local potential                                         
+   LCOR   =        T    correct aug charges                                     
+   LPAW   =        T    paw PP                                                  
+   EAUG   =  291.052                                                            
+   DEXC   =    -.041                                                            
+   RMAX   =    2.974    core radius for proj-oper                               
+   RAUG   =    1.300    factor for augmentation sphere                          
+   RDEP   =    1.966    radius for radial grids                                 
+   QCUT   =   -4.203; QGAM   =    8.405    optimization parameters              
+                                                                                
+   Description                                                                  
+     l     E      TYP  RCUT    TYP  RCUT                                        
+     0   .000     23  1.900                                                     
+     0   .000     23  1.900                                                     
+     1   .000     23  1.900                                                     
+     1  1.000     23  1.900                                                     
+     2   .000      7  1.900                                                     
+  local pseudopotential read in
+  partial core-charges read in
+  atomic valenz-charges read in
+  non local Contribution for L=            0  read in
+    real space projection operators read in
+  non local Contribution for L=            0  read in
+    real space projection operators read in
+  non local Contribution for L=            1  read in
+    real space projection operators read in
+  non local Contribution for L=            1  read in
+    real space projection operators read in
+    PAW grid and wavefunctions read in
+ 
+   number of l-projection  operators is LMAX  =            4
+   number of lm-projection operators is LMMAX =            8
+ 
+ PAW_PBE Al 04Jan2001                   :
+ energy of atom  1       EATOM=  -53.5387
+ kinetic energy error for atom=    0.0002 (will be added to EATOM!!)
+ 
+ 
+ POSCAR: Al1                                     
+  positions in direct lattice
+  No initial velocities read in
+ exchange correlation table for  LEXCH =        8
+   RHO(1)=    0.500       N(1)  =     2000
+   RHO(2)=  100.500       N(2)  =     4000
+
+ VTST: version 2.03d, (02/18/09)
+
+ CHAIN: initializing optimizer
+ 
+ OPT: Using VASP Dynamics algorithm
+ CHAIN: Read ICHAIN             0
+ 
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+ ion  position               nearest neighbor table
+   1  0.000  0.000  0.000-
+ 
+  LATTYP: Found a face centered cubic cell.
+ ALAT       =     4.0326380000
+  
+  Lattice vectors:
+  
+ A1 = (   0.0000000000,   2.0163190000,   2.0163190000)
+ A2 = (   2.0163190000,   0.0000000000,   2.0163190000)
+ A3 = (   2.0163190000,   2.0163190000,   0.0000000000)
+ Subroutine PRICEL returns:
+ Original cell was already a primitive cell.
+ 
+
+Analysis of symmetry for initial positions (statically):
+
+ Routine SETGRP: Setting up the symmetry group for a 
+ face centered cubic supercell.
+
+
+ Subroutine GETGRP returns: Found 48 space group operations
+ (whereof 48 operations were pure point group operations)
+ out of a pool of 48 trial point group operations.
+
+
+The static configuration has the point symmetry O_h .
+
+Analysis of symmetry for dynamics (positions and initial velocities):
+
+ Subroutine DYNSYM returns: Found 48 space group operations
+ (whereof 48 operations were pure point group operations)
+ out of a pool of 48 trial space group operations
+ (whereof 48 operations were pure point group operations)
+ and found also     1 'primitive' translations
+
+
+The dynamic configuration has the point symmetry O_h .
+
+Analysis of magnetic symmetry:
+
+ Subroutine MAGSYM returns: Found 48 space group operations
+ (whereof 48 operations were pure point group operations)
+ out of a pool of 48 trial space group operations
+ (whereof 48 operations were pure point group operations)
+ and found also     1 'primitive' translations
+
+
+The magnetic configuration has the point symmetry O_h .
+ 
+ 
+ KPOINTS: Automatic kpoint scheme                 
+
+Automatic generation of k-mesh.
+ 
+ Subroutine IBZKPT returns following result:
+ ===========================================
+ 
+ Found    220 irreducible k-points:
+ 
+ Following reciprocal coordinates:
+            Coordinates               Weight
+  0.000000  0.000000  0.000000      1.000000
+  0.052632  0.000000  0.000000      8.000000
+  0.105263  0.000000  0.000000      8.000000
+  0.157895  0.000000  0.000000      8.000000
+  0.210526  0.000000  0.000000      8.000000
+  0.263158  0.000000  0.000000      8.000000
+  0.315789  0.000000  0.000000      8.000000
+  0.368421  0.000000  0.000000      8.000000
+  0.421053  0.000000  0.000000      8.000000
+  0.473684  0.000000  0.000000      8.000000
+  0.052632  0.052632  0.000000      6.000000
+  0.105263  0.052632  0.000000     24.000000
+  0.157895  0.052632  0.000000     24.000000
+  0.210526  0.052632  0.000000     24.000000
+  0.263158  0.052632  0.000000     24.000000
+  0.315789  0.052632  0.000000     24.000000
+  0.368421  0.052632  0.000000     24.000000
+  0.421053  0.052632  0.000000     24.000000
+  0.473684  0.052632  0.000000     24.000000
+ -0.473684  0.052632  0.000000     24.000000
+ -0.421053  0.052632  0.000000     24.000000
+ -0.368421  0.052632  0.000000     24.000000
+ -0.315789  0.052632  0.000000     24.000000
+ -0.263158  0.052632  0.000000     24.000000
+ -0.210526  0.052632  0.000000     24.000000
+ -0.157895  0.052632  0.000000     24.000000
+ -0.105263  0.052632  0.000000     24.000000
+ -0.052632  0.052632  0.000000     12.000000
+  0.105263  0.105263  0.000000      6.000000
+  0.157895  0.105263  0.000000     24.000000
+  0.210526  0.105263  0.000000     24.000000
+  0.263158  0.105263  0.000000     24.000000
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+ -0.210526  0.105263  0.000000     24.000000
+ -0.157895  0.105263  0.000000     24.000000
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+  0.210526  0.157895  0.000000     24.000000
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+  0.315789  0.157895  0.000000     24.000000
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+ -0.368421  0.157895  0.000000     24.000000
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+ -0.263158  0.157895  0.000000     24.000000
+ -0.210526  0.157895  0.000000     24.000000
+ -0.157895  0.157895  0.000000     12.000000
+  0.210526  0.210526  0.000000      6.000000
+  0.263158  0.210526  0.000000     24.000000
+  0.315789  0.210526  0.000000     24.000000
+  0.368421  0.210526  0.000000     24.000000
+  0.421053  0.210526  0.000000     24.000000
+  0.473684  0.210526  0.000000     24.000000
+ -0.473684  0.210526  0.000000     24.000000
+ -0.421053  0.210526  0.000000     24.000000
+ -0.368421  0.210526  0.000000     24.000000
+ -0.315789  0.210526  0.000000     24.000000
+ -0.263158  0.210526  0.000000     24.000000
+ -0.210526  0.210526  0.000000     12.000000
+  0.263158  0.263158  0.000000      6.000000
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+ -0.315789  0.263158  0.000000     24.000000
+ -0.263158  0.263158  0.000000     12.000000
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+  0.368421  0.315789  0.000000     24.000000
+  0.421053  0.315789  0.000000     24.000000
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+ -0.368421  0.315789  0.000000     24.000000
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+  0.473684  0.157895  0.052632     48.000000
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+ -0.421053  0.157895  0.052632     48.000000
+ -0.368421  0.157895  0.052632     48.000000
+ -0.315789  0.157895  0.052632     48.000000
+ -0.263158  0.157895  0.052632     48.000000
+ -0.210526  0.157895  0.052632     48.000000
+ -0.157895  0.157895  0.052632     48.000000
+ -0.105263  0.157895  0.052632     24.000000
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+  0.315789  0.210526  0.052632     48.000000
+  0.368421  0.210526  0.052632     48.000000
+  0.421053  0.210526  0.052632     48.000000
+  0.473684  0.210526  0.052632     48.000000
+ -0.473684  0.210526  0.052632     48.000000
+ -0.421053  0.210526  0.052632     48.000000
+ -0.368421  0.210526  0.052632     48.000000
+ -0.315789  0.210526  0.052632     48.000000
+ -0.263158  0.210526  0.052632     48.000000
+ -0.210526  0.210526  0.052632     48.000000
+ -0.157895  0.210526  0.052632     24.000000
+  0.315789  0.263158  0.052632     24.000000
+  0.368421  0.263158  0.052632     48.000000
+  0.421053  0.263158  0.052632     48.000000
+  0.473684  0.263158  0.052632     48.000000
+ -0.473684  0.263158  0.052632     48.000000
+ -0.421053  0.263158  0.052632     48.000000
+ -0.368421  0.263158  0.052632     48.000000
+ -0.315789  0.263158  0.052632     48.000000
+ -0.263158  0.263158  0.052632     48.000000
+ -0.210526  0.263158  0.052632     24.000000
+  0.368421  0.315789  0.052632     24.000000
+  0.421053  0.315789  0.052632     48.000000
+  0.473684  0.315789  0.052632     48.000000
+ -0.473684  0.315789  0.052632     48.000000
+ -0.421053  0.315789  0.052632     48.000000
+ -0.368421  0.315789  0.052632     48.000000
+ -0.315789  0.315789  0.052632     48.000000
+ -0.263158  0.315789  0.052632     24.000000
+  0.421053  0.368421  0.052632     24.000000
+  0.473684  0.368421  0.052632     48.000000
+ -0.473684  0.368421  0.052632     48.000000
+ -0.421053  0.368421  0.052632     48.000000
+ -0.368421  0.368421  0.052632     48.000000
+ -0.315789  0.368421  0.052632     24.000000
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+ -0.473684  0.421053  0.052632     48.000000
+ -0.421053  0.421053  0.052632     48.000000
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+ -0.473684  0.473684  0.052632     24.000000
+ -0.421053  0.473684  0.052632     24.000000
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+ -0.421053  0.210526  0.105263     48.000000
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+ -0.421053  0.263158  0.105263     48.000000
+ -0.368421  0.263158  0.105263     48.000000
+ -0.315789  0.263158  0.105263     48.000000
+ -0.263158  0.263158  0.105263     48.000000
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+ -0.368421  0.421053  0.105263     48.000000
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+ -0.473684  0.315789  0.157895     48.000000
+ -0.421053  0.315789  0.157895     48.000000
+ -0.368421  0.315789  0.157895     48.000000
+ -0.473684  0.368421  0.157895     24.000000
+ -0.421053  0.368421  0.157895     48.000000
+ -0.368421  0.368421  0.157895     48.000000
+ -0.315789  0.368421  0.157895     48.000000
+ -0.263158  0.368421  0.157895     48.000000
+ -0.210526  0.368421  0.157895     24.000000
+ -0.421053  0.421053  0.157895     24.000000
+ -0.368421  0.421053  0.157895     48.000000
+ -0.315789  0.421053  0.157895     48.000000
+ -0.263158  0.421053  0.157895     24.000000
+ -0.368421  0.473684  0.157895     24.000000
+ -0.315789  0.473684  0.157895     24.000000
+ -0.368421  0.421053  0.210526     24.000000
+ -0.315789  0.421053  0.210526     48.000000
+ -0.315789  0.473684  0.210526     24.000000
+ -0.263158  0.473684  0.210526     24.000000
+ 
+ Following cartesian coordinates:
+            Coordinates               Weight
+  0.000000  0.000000  0.000000      1.000000
+ -0.013051  0.013051  0.013051      8.000000
+ -0.026103  0.026103  0.026103      8.000000
+ -0.039154  0.039154  0.039154      8.000000
+ -0.052206  0.052206  0.052206      8.000000
+ -0.065257  0.065257  0.065257      8.000000
+ -0.078308  0.078308  0.078308      8.000000
+ -0.091360  0.091360  0.091360      8.000000
+ -0.104411  0.104411  0.104411      8.000000
+ -0.117463  0.117463  0.117463      8.000000
+  0.000000  0.000000  0.026103      6.000000
+ -0.013051  0.013051  0.039154     24.000000
+ -0.026103  0.026103  0.052206     24.000000
+ -0.039154  0.039154  0.065257     24.000000
+ -0.052206  0.052206  0.078308     24.000000
+ -0.065257  0.065257  0.091360     24.000000
+ -0.078308  0.078308  0.104411     24.000000
+ -0.091360  0.091360  0.117463     24.000000
+ -0.104411  0.104411  0.130514     24.000000
+  0.130514 -0.130514 -0.104411     24.000000
+  0.117463 -0.117463 -0.091360     24.000000
+  0.104411 -0.104411 -0.078308     24.000000
+  0.091360 -0.091360 -0.065257     24.000000
+  0.078308 -0.078308 -0.052206     24.000000
+  0.065257 -0.065257 -0.039154     24.000000
+  0.052206 -0.052206 -0.026103     24.000000
+  0.039154 -0.039154 -0.013051     24.000000
+  0.026103 -0.026103  0.000000     12.000000
+  0.000000  0.000000  0.052206      6.000000
+ -0.013051  0.013051  0.065257     24.000000
+ -0.026103  0.026103  0.078308     24.000000
+ -0.039154  0.039154  0.091360     24.000000
+ -0.052206  0.052206  0.104411     24.000000
+ -0.065257  0.065257  0.117463     24.000000
+ -0.078308  0.078308  0.130514     24.000000
+ -0.091360  0.091360  0.143565     24.000000
+  0.143565 -0.143565 -0.091360     24.000000
+  0.130514 -0.130514 -0.078308     24.000000
+  0.117463 -0.117463 -0.065257     24.000000
+  0.104411 -0.104411 -0.052206     24.000000
+  0.091360 -0.091360 -0.039154     24.000000
+  0.078308 -0.078308 -0.026103     24.000000
+  0.065257 -0.065257 -0.013051     24.000000
+  0.052206 -0.052206  0.000000     12.000000
+  0.000000  0.000000  0.078308      6.000000
+ -0.013051  0.013051  0.091360     24.000000
+ -0.026103  0.026103  0.104411     24.000000
+ -0.039154  0.039154  0.117463     24.000000
+ -0.052206  0.052206  0.130514     24.000000
+ -0.065257  0.065257  0.143565     24.000000
+ -0.078308  0.078308  0.156617     24.000000
+  0.156617 -0.156617 -0.078308     24.000000
+  0.143565 -0.143565 -0.065257     24.000000
+  0.130514 -0.130514 -0.052206     24.000000
+  0.117463 -0.117463 -0.039154     24.000000
+  0.104411 -0.104411 -0.026103     24.000000
+  0.091360 -0.091360 -0.013051     24.000000
+  0.078308 -0.078308  0.000000     12.000000
+  0.000000  0.000000  0.104411      6.000000
+ -0.013051  0.013051  0.117463     24.000000
+ -0.026103  0.026103  0.130514     24.000000
+ -0.039154  0.039154  0.143565     24.000000
+ -0.052206  0.052206  0.156617     24.000000
+ -0.065257  0.065257  0.169668     24.000000
+  0.169668 -0.169668 -0.065257     24.000000
+  0.156617 -0.156617 -0.052206     24.000000
+  0.143565 -0.143565 -0.039154     24.000000
+  0.130514 -0.130514 -0.026103     24.000000
+  0.117463 -0.117463 -0.013051     24.000000
+  0.104411 -0.104411  0.000000     12.000000
+  0.000000  0.000000  0.130514      6.000000
+ -0.013051  0.013051  0.143565     24.000000
+ -0.026103  0.026103  0.156617     24.000000
+ -0.039154  0.039154  0.169668     24.000000
+ -0.052206  0.052206  0.182720     24.000000
+  0.182720 -0.182720 -0.052206     24.000000
+  0.169668 -0.169668 -0.039154     24.000000
+  0.156617 -0.156617 -0.026103     24.000000
+  0.143565 -0.143565 -0.013051     24.000000
+  0.130514 -0.130514  0.000000     12.000000
+  0.000000  0.000000  0.156617      6.000000
+ -0.013051  0.013051  0.169668     24.000000
+ -0.026103  0.026103  0.182720     24.000000
+ -0.039154  0.039154  0.195771     24.000000
+  0.195771 -0.195771 -0.039154     24.000000
+  0.182720 -0.182720 -0.026103     24.000000
+  0.169668 -0.169668 -0.013051     24.000000
+  0.156617 -0.156617  0.000000     12.000000
+  0.000000  0.000000  0.182720      6.000000
+ -0.013051  0.013051  0.195771     24.000000
+ -0.026103  0.026103  0.208822     24.000000
+  0.208822 -0.208822 -0.026103     24.000000
+  0.195771 -0.195771 -0.013051     24.000000
+  0.182720 -0.182720  0.000000     12.000000
+  0.000000  0.000000  0.208822      6.000000
+ -0.013051  0.013051  0.221874     24.000000
+  0.221874 -0.221874 -0.013051     24.000000
+  0.208822 -0.208822  0.000000     12.000000
+  0.000000  0.000000  0.234925      6.000000
+  0.234925 -0.234925  0.000000     12.000000
+  0.000000  0.026103  0.052206     24.000000
+ -0.013051  0.039154  0.065257     48.000000
+ -0.026103  0.052206  0.078308     48.000000
+ -0.039154  0.065257  0.091360     48.000000
+ -0.052206  0.078308  0.104411     48.000000
+ -0.065257  0.091360  0.117463     48.000000
+ -0.078308  0.104411  0.130514     48.000000
+  0.156617 -0.130514 -0.104411     48.000000
+  0.000000  0.026103  0.078308     24.000000
+ -0.013051  0.039154  0.091360     48.000000
+ -0.026103  0.052206  0.104411     48.000000
+ -0.039154  0.065257  0.117463     48.000000
+ -0.052206  0.078308  0.130514     48.000000
+ -0.065257  0.091360  0.143565     48.000000
+  0.169668 -0.143565 -0.091360     48.000000
+  0.156617 -0.130514 -0.078308     48.000000
+  0.143565 -0.117463 -0.065257     48.000000
+  0.130514 -0.104411 -0.052206     48.000000
+  0.117463 -0.091360 -0.039154     48.000000
+  0.104411 -0.078308 -0.026103     48.000000
+  0.091360 -0.065257 -0.013051     48.000000
+  0.078308 -0.052206  0.000000     24.000000
+  0.000000  0.026103  0.104411     24.000000
+ -0.013051  0.039154  0.117463     48.000000
+ -0.026103  0.052206  0.130514     48.000000
+ -0.039154  0.065257  0.143565     48.000000
+ -0.052206  0.078308  0.156617     48.000000
+  0.182720 -0.156617 -0.078308     48.000000
+  0.169668 -0.143565 -0.065257     48.000000
+  0.156617 -0.130514 -0.052206     48.000000
+  0.143565 -0.117463 -0.039154     48.000000
+  0.130514 -0.104411 -0.026103     48.000000
+  0.117463 -0.091360 -0.013051     48.000000
+  0.104411 -0.078308  0.000000     24.000000
+  0.000000  0.026103  0.130514     24.000000
+ -0.013051  0.039154  0.143565     48.000000
+ -0.026103  0.052206  0.156617     48.000000
+ -0.039154  0.065257  0.169668     48.000000
+  0.195771 -0.169668 -0.065257     48.000000
+  0.182720 -0.156617 -0.052206     48.000000
+  0.169668 -0.143565 -0.039154     48.000000
+  0.156617 -0.130514 -0.026103     48.000000
+  0.143565 -0.117463 -0.013051     48.000000
+  0.130514 -0.104411  0.000000     24.000000
+  0.000000  0.026103  0.156617     24.000000
+ -0.013051  0.039154  0.169668     48.000000
+ -0.026103  0.052206  0.182720     48.000000
+  0.208822 -0.182720 -0.052206     48.000000
+  0.195771 -0.169668 -0.039154     48.000000
+  0.182720 -0.156617 -0.026103     48.000000
+  0.169668 -0.143565 -0.013051     48.000000
+  0.156617 -0.130514  0.000000     24.000000
+  0.000000  0.026103  0.182720     24.000000
+ -0.013051  0.039154  0.195771     48.000000
+  0.221874 -0.195771 -0.039154     48.000000
+  0.208822 -0.182720 -0.026103     48.000000
+  0.195771 -0.169668 -0.013051     48.000000
+  0.182720 -0.156617  0.000000     24.000000
+  0.000000  0.026103  0.208822     24.000000
+  0.234925 -0.208822 -0.026103     48.000000
+  0.221874 -0.195771 -0.013051     48.000000
+  0.208822 -0.182720  0.000000     24.000000
+  0.247977 -0.221874 -0.013051     24.000000
+  0.234925 -0.208822  0.000000     24.000000
+  0.000000  0.052206  0.104411     24.000000
+ -0.013051  0.065257  0.117463     48.000000
+ -0.026103  0.078308  0.130514     48.000000
+ -0.039154  0.091360  0.143565     48.000000
+  0.195771 -0.143565 -0.091360     48.000000
+  0.182720 -0.130514 -0.078308     48.000000
+  0.000000  0.052206  0.130514     24.000000
+ -0.013051  0.065257  0.143565     48.000000
+ -0.026103  0.078308  0.156617     48.000000
+  0.208822 -0.156617 -0.078308     48.000000
+  0.195771 -0.143565 -0.065257     48.000000
+  0.182720 -0.130514 -0.052206     48.000000
+  0.169668 -0.117463 -0.039154     48.000000
+  0.156617 -0.104411 -0.026103     48.000000
+  0.143565 -0.091360 -0.013051     48.000000
+  0.130514 -0.078308  0.000000     24.000000
+  0.000000  0.052206  0.156617     24.000000
+ -0.013051  0.065257  0.169668     48.000000
+  0.221874 -0.169668 -0.065257     48.000000
+  0.208822 -0.156617 -0.052206     48.000000
+  0.195771 -0.143565 -0.039154     48.000000
+  0.182720 -0.130514 -0.026103     48.000000
+  0.169668 -0.117463 -0.013051     48.000000
+  0.156617 -0.104411  0.000000     24.000000
+  0.000000  0.052206  0.182720     24.000000
+  0.234925 -0.182720 -0.052206     48.000000
+  0.221874 -0.169668 -0.039154     48.000000
+  0.208822 -0.156617 -0.026103     48.000000
+  0.195771 -0.143565 -0.013051     48.000000
+  0.182720 -0.130514  0.000000     24.000000
+  0.247977 -0.195771 -0.039154     24.000000
+  0.234925 -0.182720 -0.026103     48.000000
+  0.221874 -0.169668 -0.013051     48.000000
+  0.208822 -0.156617  0.000000     24.000000
+  0.247977 -0.195771 -0.013051     24.000000
+  0.234925 -0.182720  0.000000     24.000000
+  0.000000  0.078308  0.156617     24.000000
+  0.234925 -0.156617 -0.078308     48.000000
+  0.221874 -0.143565 -0.065257     48.000000
+  0.208822 -0.130514 -0.052206     48.000000
+  0.247977 -0.169668 -0.065257     24.000000
+  0.234925 -0.156617 -0.052206     48.000000
+  0.221874 -0.143565 -0.039154     48.000000
+  0.208822 -0.130514 -0.026103     48.000000
+  0.195771 -0.117463 -0.013051     48.000000
+  0.182720 -0.104411  0.000000     24.000000
+  0.247977 -0.169668 -0.039154     24.000000
+  0.234925 -0.156617 -0.026103     48.000000
+  0.221874 -0.143565 -0.013051     48.000000
+  0.208822 -0.130514  0.000000     24.000000
+  0.247977 -0.169668 -0.013051     24.000000
+  0.234925 -0.156617  0.000000     24.000000
+  0.247977 -0.143565 -0.039154     24.000000
+  0.234925 -0.130514 -0.026103     48.000000
+  0.247977 -0.143565 -0.013051     24.000000
+  0.234925 -0.130514  0.000000     24.000000
+ 
+ TETIRR: Found    955 inequivalent tetrahedra from    41154
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+
+
+ Dimension of arrays:
+   k-points           NKPTS =    220   k-points in BZ     NKDIM =    220   number of bands    NBANDS=      6
+   number of dos      NEDOS =    301   number of ions     NIONS =      1
+   non local maximal  LDIM  =      4   non local SUM 2l+1 LMDIM =      8
+   total plane-waves  NPLWV =  13824
+   max r-space proj   IRMAX =      1   max aug-charges    IRDMAX=  33012
+   dimension x,y,z NGX =    24 NGY =   24 NGZ =   24
+   dimension x,y,z NGXF=    48 NGYF=   48 NGZF=   48
+   support grid    NGXF=    48 NGYF=   48 NGZF=   48
+   ions per type =               1
+ NGX,Y,Z   is equivalent  to a cutoff of  13.99, 13.99, 13.99 a.u.
+ NGXF,Y,Z  is equivalent  to a cutoff of  27.98, 27.98, 27.98 a.u.
+
+
+ I would recommend the setting:
+   dimension x,y,z NGX =    21 NGY =   21 NGZ =   21
+ SYSTEM =  unknown system                          
+ POSCAR =  Al1                                     
+
+ Startparameter for this run:
+   NWRITE =      2    write-flag & timer
+   PREC   = accura    medium, high low
+   ISTART =      0    job   : 0-new  1-cont  2-samecut
+   ICHARG =      2    charge: 1-file 2-atom 10-const
+   ISPIN  =      2    spin polarized calculation?
+   LNONCOLLINEAR =      F non collinear calculations
+   LSORBIT =      F    spin-orbit coupling
+   INIWAV =      1    electr: 0-lowe 1-rand  2-diag
+   LASPH  =      F    aspherical Exc in radial PAW
+   METAGGA=      F    non-selfconsistent MetaGGA calc.
+
+ Electronic Relaxation 1
+   ENCUT  =  520.0 eV  38.22 Ry    6.18 a.u.   5.30  5.30  5.30*2*pi/ulx,y,z
+   ENINI  =  520.0     initial cutoff
+   ENAUG  =  291.1 eV  augmentation charge cutoff
+   NELM   =    100;   NELMIN=  2; NELMDL=  0     # of ELM steps 
+   EDIFF  = 0.1E-05   stopping-criterion for ELM
+   LREAL  =      F    real-space projection
+   LCOMPAT=      F    compatible to vasp.4.4
+   LREAL_COMPAT= F    compatible to vasp.4.5.1-3
+   GGA_COMPAT  = T    GGA compatible to vasp.4.4-vasp.4.6
+   LMAXPAW     = -100 max onsite density
+   LMAXMIX     =    2 max onsite mixed and CHGCAR
+   VOSKOWN=      0    Vosko Wilk Nusair interpolation
+   ROPT   =    0.00000
+ Ionic relaxation
+   EDIFFG = 0.1E-04   stopping-criterion for IOM
+   NSW    =      0    number of steps for IOM
+   NBLOCK =      1;   KBLOCK =      1    inner block; outer block 
+   IBRION =     -1    ionic relax: 0-MD 1-quasi-New 2-CG
+   NFREE  =      0    steps in history (QN), initial steepest desc. (CG)
+   ISIF   =      3    stress and relaxation
+   IWAVPR =     10    prediction:  0-non 1-charg 2-wave 3-comb
+   ISYM   =      2    0-nonsym 1-usesym 2-fastsym
+   LCORR  =      T    Harris-Foulkes like correction to forces
+
+   POTIM  = 0.5000    time-step for ionic-motion
+   TEIN   =    0.0    initial temperature
+   TEBEG  =    0.0;   TEEND  =   0.0 temperature during run
+   SMASS  =  -3.00    Nose mass-parameter (am)
+   estimated Nose-frequenzy (Omega)   =  0.10E-29 period in steps =****** mass=  -0.186E-27a.u.
+   NPACO  =    256;   APACO  = 16.0  distance and # of slots for P.C.
+   PSTRESS=    0.0 pullay stress
+
+  Mass of Ions in am
+   POMASS =  26.98
+  Ionic Valenz
+   ZVAL   =   3.00
+  Atomic Wigner-Seitz radii
+   RWIGS  =  -1.00
+   NELECT =       3.0000    total number of electrons
+   NUPDOWN=      -1.0000    fix difference up-down
+
+ DOS related values:
+   EMIN   =  10.00;   EMAX   =-10.00  energy-range for DOS
+   EFERMI =   0.00
+   ISMEAR =    -5;   SIGMA  =   0.20  broadening in eV -4-tet -1-fermi 0-gaus
+
+ Electronic relaxation 2 (details)
+   IALGO  =     38    algorithm
+   LDIAG  =      T    sub-space diagonalisation
+   IMIX   =      4    mixing-type and parameters
+     AMIX     =   0.40;   BMIX     =  1.00
+     AMIX_MAG =   1.60;   BMIX_MAG =  1.00
+     AMIN     =   0.10
+     WC   =   100.;   INIMIX=   1;  MIXPRE=   1
+
+ Intra band minimization:
+   WEIMIN = 0.0000     energy-eigenvalue tresh-hold
+   EBREAK =  0.50E-07  absolut break condition
+   DEPER  =   0.30     relativ break condition  
+
+   TIME   =   0.40     timestep for ELM
+
+  volume/ion in A,a.u.               =      16.39       110.64
+  Fermi-wavevector in a.u.,A,eV,Ry     =   0.929421  1.756352 11.753041  0.863824
+  Thomas-Fermi vector in A             =   2.055702
+ 
+ Write flags
+   LWAVE  =      F    write WAVECAR
+   LCHARG =      T    write CHGCAR
+   LVTOT  =      F    write LOCPOT, local potential
+   LELF   =      F    write electronic localiz. function (ELF)
+   LORBIT =     11    0 simple, 1 ext, 2 COOP (PROOUT)
+
+
+ Dipole corrections
+   LMONO  =      F    monopole corrections only (constant potential shift)
+   LDIPOL =      F    correct potential (dipole corrections)
+   IDIPOL =      0    1-x, 2-y, 3-z, 4-all directions 
+   EPSILON=  1.0000000 bulk dielectric constant
+
+ Exchange correlation treatment:
+   GGA     =    --    GGA type
+   LEXCH   =     8    internal setting for exchange type
+   VOSKOWN=      0    Vosko Wilk Nusair interpolation
+   LHFCALC =     F    Hartree Fock is set to
+   LHFONE  =     F    Hartree Fock one center treatment
+   AEXX    =    0.0000 exact exchange contribution
+
+ Linear response parameters
+   LEPSILON=     F    determine dielectric tensor
+   LRPA    =     F    only Hartree local field effects (RPA)
+   LNABLA  =     F    use nabla operator in PAW spheres
+   LVEL    =     F    velocity operator in full k-point grid
+   LINTERFAST=   F  fast interpolation
+   KINTER  =     0    interpolate to denser k-point grid
+   CSHIFT  =0.1000    complex shift for real part using Kramers Kronig
+   OMEGAMAX=  -1.0    maximum frequency
+
+ Orbital magnetization related:
+   ORBITALMAG=     F  switch on orbital magnetization
+   LCHIMAG   =     F  perturbation theory with respect to B field
+
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+ Static calculation
+ charge density and potential will be updated during run
+ spin polarized calculation
+ Variant of blocked Davidson
+ Davidson routine will perform the subspace rotation
+ perform sub-space diagonalisation
+    after iterative eigenvector-optimisation
+ modified Broyden-mixing scheme, WC =      100.0
+ initial mixing is a Kerker type mixing with AMIX =  0.4000 and BMIX =      1.0000
+ Hartree-type preconditioning will be used
+ using additional bands             4
+ reciprocal scheme for non local part
+ use partial core corrections
+ calculate Harris-corrections to forces 
+   (improved forces if not selfconsistent)
+ use gradient corrections 
+ use of overlap-Matrix (Vanderbilt PP)
+ Fermi weights with tetrahedron method with Bloechl corrections
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+  energy-cutoff  :      520.00
+  volume of cell :       16.39
+      direct lattice vectors                 reciprocal lattice vectors
+     0.000000000  2.016319000  2.016319000    -0.247976635  0.247976635  0.247976635
+     2.016319000  0.000000000  2.016319000     0.247976635 -0.247976635  0.247976635
+     2.016319000  2.016319000  0.000000000     0.247976635  0.247976635 -0.247976635
+
+  length of vectors
+     2.851505676  2.851505676  2.851505676     0.429508130  0.429508130  0.429508130
+
+
+ 
+ k-points in units of 2pi/SCALE and weight: Automatic kpoint scheme                 
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+ 
+ k-points in reciprocal lattice and weights: Automatic kpoint scheme                 
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+ k-point ** :  -.31580.42110.1053  plane waves:     439
+ k-point ** :  -.42110.47370.1053  plane waves:     446
+ k-point ** :  -.36840.47370.1053  plane waves:     445
+ k-point ** :  0.47370.31580.1579  plane waves:     435
+ k-point ** :  -.47370.31580.1579  plane waves:     442
+ k-point ** :  -.42110.31580.1579  plane waves:     439
+ k-point ** :  -.36840.31580.1579  plane waves:     436
+ k-point ** :  -.47370.36840.1579  plane waves:     438
+ k-point ** :  -.42110.36840.1579  plane waves:     441
+ k-point ** :  -.36840.36840.1579  plane waves:     438
+ k-point ** :  -.31580.36840.1579  plane waves:     440
+ k-point ** :  -.26320.36840.1579  plane waves:     439
+ k-point ** :  -.21050.36840.1579  plane waves:     440
+ k-point ** :  -.42110.42110.1579  plane waves:     440
+ k-point ** :  -.36840.42110.1579  plane waves:     439
+ k-point ** :  -.31580.42110.1579  plane waves:     439
+ k-point ** :  -.26320.42110.1579  plane waves:     442
+ k-point ** :  -.36840.47370.1579  plane waves:     440
+ k-point ** :  -.31580.47370.1579  plane waves:     439
+ k-point ** :  -.36840.42110.2105  plane waves:     442
+ k-point ** :  -.31580.42110.2105  plane waves:     442
+ k-point ** :  -.31580.47370.2105  plane waves:     441
+ k-point ** :  -.26320.47370.2105  plane waves:     444
+
+ maximum and minimum number of plane-waves per node :      35     21
+
+ maximum number of plane-waves:     459
+ maximal index in each direction: 
+   IXMAX=  5   IYMAX=  5   IZMAX=  5
+   IXMIN= -5   IYMIN= -5   IZMIN= -5
+
+ NGX is ok and might be reduce to  22
+ NGY is ok and might be reduce to  22
+ NGZ is ok and might be reduce to  22
+
+ parallel 3D FFT for wavefunctions:
+    minimum data exchange during FFTs selected (reduces bandwidth)
+ parallel 3D FFT for charge:
+    minimum data exchange during FFTs selected (reduces bandwidth)
+
+
+ total amount of memory used by VASP on root node  33617. kBytes
+========================================================================
+
+   base      :    30000. kBytes
+   nonl-proj :      451. kBytes
+   fftplans  :      185. kBytes
+   grid      :     2131. kBytes
+   one-center:        6. kBytes
+   wavefun   :      844. kBytes
+ 
+ Broyden mixing: mesh for mixing (old mesh)
+   NGX = 11   NGY = 11   NGZ = 11
+  (NGX  = 48   NGY  = 48   NGZ  = 48)
+  gives a total of   1331 points
+
+ initial charge density was supplied:
+ charge density of overlapping atoms calculated
+ number of electron    3.0000000 magnetization    0.6000000
+ keeping initial charge density in first step
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+ Maximum index for augmentation-charges          1603 (set IRDMAX)
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+ First call to EWALD:  gamma=   0.698
+ Maximum number of real-space cells 3x 3x 3
+ Maximum number of reciprocal cells 3x 3x 3
+
+    FEWALD:  cpu time    0.00: real time    0.00
+   RESPFUN:  cpu time    0.00: real time    0.00
+
+
+----------------------------------------- Iteration    1(   1)  ---------------------------------------
+
+
+    POTLOK:  cpu time    0.19: real time    0.22
+    SETDIJ:  cpu time    0.01: real time    0.02
+     EDDAV:  cpu time    3.31: real time    3.39
+ BZINTS: Fermi energy:  9.578122;  3.000000 electrons
+         Band energy:  12.818451;  BLOECHL correction: -0.111649
+       DOS:  cpu time    0.03: real time    0.03
+    --------------------------------------------
+      LOOP:  cpu time    3.54: real time    3.66
+
+ eigenvalue-minimisations  :  5364
+ total energy-change (2. order) :-0.1839857E+01  (-0.8490176E+02)
+ number of electron    3.0000000 magnetization    0.6000000
+ augmentation part     3.0000000 magnetization    0.6000000
+
+ Free energy of the ion-electron system (eV)
+  ---------------------------------------------------
+  alpha Z        PSCENC =        -0.20486981
+  Ewald energy   TEWEN  =       -73.67253674
+  -1/2 Hartree   DENC   =        -0.09905503
+  -exchange  EXHF       =         0.00000000
+  -V(xc)+E(xc)   XCENC  =       -26.17475841
+  PAW double counting   =        35.53514605       -3.58069100
+  entropy T*S    EENTRO =         0.00000000
+  eigenvalues    EBANDS =        12.81845108
+  atomic energy  EATOM  =        53.53845706
+  ---------------------------------------------------
+  free energy    TOTEN  =        -1.83985680 eV
+
+  energy without entropy =       -1.83985680  energy(sigma->0) =       -1.83985680
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+
+
+----------------------------------------- Iteration    1(   2)  ---------------------------------------
+
+
+     EDDAV:  cpu time    3.90: real time    3.90
+ BZINTS: Fermi energy:  8.133411;  3.000000 electrons
+         Band energy:  10.991366;  BLOECHL correction: -0.045115
+       DOS:  cpu time    0.02: real time    0.02
+    --------------------------------------------
+      LOOP:  cpu time    3.92: real time    3.92
+
+ eigenvalue-minimisations  :  6840
+ total energy-change (2. order) :-0.1827085E+01  (-0.1781267E+01)
+ number of electron    3.0000000 magnetization    0.6000000
+ augmentation part     3.0000000 magnetization    0.6000000
+
+ Free energy of the ion-electron system (eV)
+  ---------------------------------------------------
+  alpha Z        PSCENC =        -0.20486981
+  Ewald energy   TEWEN  =       -73.67253674
+  -1/2 Hartree   DENC   =        -0.09905503
+  -exchange  EXHF       =         0.00000000
+  -V(xc)+E(xc)   XCENC  =       -26.17475841
+  PAW double counting   =        35.53514605       -3.58069100
+  entropy T*S    EENTRO =         0.00000000
+  eigenvalues    EBANDS =        10.99136572
+  atomic energy  EATOM  =        53.53845706
+  ---------------------------------------------------
+  free energy    TOTEN  =        -3.66694216 eV
+
+  energy without entropy =       -3.66694216  energy(sigma->0) =       -3.66694216
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+
+
+----------------------------------------- Iteration    1(   3)  ---------------------------------------
+
+
+     EDDAV:  cpu time    4.01: real time    4.01
+ BZINTS: Fermi energy:  8.120605;  3.000000 electrons
+         Band energy:  10.976373;  BLOECHL correction: -0.044931
+       DOS:  cpu time    0.02: real time    0.02
+    --------------------------------------------
+      LOOP:  cpu time    4.03: real time    4.04
+
+ eigenvalue-minimisations  :  7050
+ total energy-change (2. order) :-0.1499319E-01  (-0.1501025E-01)
+ number of electron    3.0000000 magnetization    0.6000000
+ augmentation part     3.0000000 magnetization    0.6000000
+
+ Free energy of the ion-electron system (eV)
+  ---------------------------------------------------
+  alpha Z        PSCENC =        -0.20486981
+  Ewald energy   TEWEN  =       -73.67253674
+  -1/2 Hartree   DENC   =        -0.09905503
+  -exchange  EXHF       =         0.00000000
+  -V(xc)+E(xc)   XCENC  =       -26.17475841
+  PAW double counting   =        35.53514605       -3.58069100
+  entropy T*S    EENTRO =         0.00000000
+  eigenvalues    EBANDS =        10.97637253
+  atomic energy  EATOM  =        53.53845706
+  ---------------------------------------------------
+  free energy    TOTEN  =        -3.68193534 eV
+
+  energy without entropy =       -3.68193534  energy(sigma->0) =       -3.68193534
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+
+
+----------------------------------------- Iteration    1(   4)  ---------------------------------------
+
+
+     EDDAV:  cpu time    4.04: real time    4.04
+ BZINTS: Fermi energy:  8.120565;  3.000000 electrons
+         Band energy:  10.976334;  BLOECHL correction: -0.044930
+       DOS:  cpu time    0.02: real time    0.02
+    --------------------------------------------
+      LOOP:  cpu time    4.06: real time    4.07
+
+ eigenvalue-minimisations  :  7044
+ total energy-change (2. order) :-0.3812864E-04  (-0.3835956E-04)
+ number of electron    3.0000000 magnetization    0.6000000
+ augmentation part     3.0000000 magnetization    0.6000000
+
+ Free energy of the ion-electron system (eV)
+  ---------------------------------------------------
+  alpha Z        PSCENC =        -0.20486981
+  Ewald energy   TEWEN  =       -73.67253674
+  -1/2 Hartree   DENC   =        -0.09905503
+  -exchange  EXHF       =         0.00000000
+  -V(xc)+E(xc)   XCENC  =       -26.17475841
+  PAW double counting   =        35.53514605       -3.58069100
+  entropy T*S    EENTRO =         0.00000000
+  eigenvalues    EBANDS =        10.97633440
+  atomic energy  EATOM  =        53.53845706
+  ---------------------------------------------------
+  free energy    TOTEN  =        -3.68197347 eV
+
+  energy without entropy =       -3.68197347  energy(sigma->0) =       -3.68197347
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+
+
+----------------------------------------- Iteration    1(   5)  ---------------------------------------
+
+
+     EDDAV:  cpu time    4.08: real time    4.08
+ BZINTS: Fermi energy:  8.120565;  3.000000 electrons
+         Band energy:  10.976334;  BLOECHL correction: -0.044930
+       DOS:  cpu time    0.02: real time    0.02
+    CHARGE:  cpu time    0.11: real time    0.11
+    MIXING:  cpu time    0.00: real time    0.01
+    --------------------------------------------
+      LOOP:  cpu time    4.21: real time    4.22
+
+ eigenvalue-minimisations  :  7146
+ total energy-change (2. order) :-0.1967941E-06  (-0.1963461E-06)
+ number of electron    3.0000000 magnetization   -0.0426071
+ augmentation part    -0.0369119 magnetization   -0.1858986
+
+ Broyden mixing:
+  rms(total) = 0.14891E+00    rms(broyden)= 0.14891E+00
+  rms(prec ) = 0.37033E+00
+  weight for this iteration     100.00
+
+ Free energy of the ion-electron system (eV)
+  ---------------------------------------------------
+  alpha Z        PSCENC =        -0.20486981
+  Ewald energy   TEWEN  =       -73.67253674
+  -1/2 Hartree   DENC   =        -0.09905503
+  -exchange  EXHF       =         0.00000000
+  -V(xc)+E(xc)   XCENC  =       -26.17475841
+  PAW double counting   =        35.53514605       -3.58069100
+  entropy T*S    EENTRO =         0.00000000
+  eigenvalues    EBANDS =        10.97633421
+  atomic energy  EATOM  =        53.53845706
+  ---------------------------------------------------
+  free energy    TOTEN  =        -3.68197367 eV
+
+  energy without entropy =       -3.68197367  energy(sigma->0) =       -3.68197367
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+
+
+----------------------------------------- Iteration    1(   6)  ---------------------------------------
+
+
+    POTLOK:  cpu time    0.02: real time    0.02
+    SETDIJ:  cpu time    0.01: real time    0.01
+     EDDAV:  cpu time    3.51: real time    3.51
+ BZINTS: Fermi energy:  8.109014;  3.000000 electrons
+         Band energy:  10.911058;  BLOECHL correction: -0.041621
+       DOS:  cpu time    0.02: real time    0.02
+    CHARGE:  cpu time    0.10: real time    0.10
+    MIXING:  cpu time    0.00: real time    0.00
+    --------------------------------------------
+      LOOP:  cpu time    3.67: real time    3.67
+
+ eigenvalue-minimisations  :  5952
+ total energy-change (2. order) :-0.7030407E-01  (-0.5750471E-03)
+ number of electron    3.0000000 magnetization    0.0494010
+ augmentation part    -0.0370819 magnetization    0.0567525
+
+ Broyden mixing:
+  rms(total) = 0.61067E-01    rms(broyden)= 0.61067E-01
+  rms(prec ) = 0.22482E+00
+  weight for this iteration     100.00
+
+ eigenvalues of (default mixing * dielectric matrix)
+  average eigenvalue GAMMA=   0.9444
+  0.9444
+
+ Free energy of the ion-electron system (eV)
+  ---------------------------------------------------
+  alpha Z        PSCENC =        -0.20486981
+  Ewald energy   TEWEN  =       -73.67253674
+  -1/2 Hartree   DENC   =        -0.08405912
+  -exchange  EXHF       =         0.00000000
+  -V(xc)+E(xc)   XCENC  =       -26.19176888
+  PAW double counting   =        35.59867548       -3.64723334
+  entropy T*S    EENTRO =         0.00000000
+  eigenvalues    EBANDS =        10.91105761
+  atomic energy  EATOM  =        53.53845706
+  ---------------------------------------------------
+  free energy    TOTEN  =        -3.75227774 eV
+
+  energy without entropy =       -3.75227774  energy(sigma->0) =       -3.75227774
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+
+
+----------------------------------------- Iteration    1(   7)  ---------------------------------------
+
+
+    POTLOK:  cpu time    0.02: real time    0.02
+    SETDIJ:  cpu time    0.01: real time    0.01
+     EDDAV:  cpu time    3.61: real time    3.61
+ BZINTS: Fermi energy:  8.097372;  3.000000 electrons
+         Band energy:  10.882812;  BLOECHL correction: -0.041776
+       DOS:  cpu time    0.02: real time    0.02
+    CHARGE:  cpu time    0.10: real time    0.10
+    MIXING:  cpu time    0.00: real time    0.00
+    --------------------------------------------
+      LOOP:  cpu time    3.76: real time    3.76
+
+ eigenvalue-minimisations  :  5964
+ total energy-change (2. order) : 0.8846572E-02  (-0.7642311E-03)
+ number of electron    3.0000000 magnetization   -0.0048252
+ augmentation part    -0.0378173 magnetization   -0.0127380
+
+ Broyden mixing:
+  rms(total) = 0.26746E-01    rms(broyden)= 0.26746E-01
+  rms(prec ) = 0.71804E-01
+  weight for this iteration     100.00
+
+ eigenvalues of (default mixing * dielectric matrix)
+  average eigenvalue GAMMA=   1.3346
+  0.8791  1.7900
+
+ Free energy of the ion-electron system (eV)
+  ---------------------------------------------------
+  alpha Z        PSCENC =        -0.20486981
+  Ewald energy   TEWEN  =       -73.67253674
+  -1/2 Hartree   DENC   =        -0.09204508
+  -exchange  EXHF       =         0.00000000
+  -V(xc)+E(xc)   XCENC  =       -26.14171949
+  PAW double counting   =        35.63226269       -3.68579144
+  entropy T*S    EENTRO =         0.00000000
+  eigenvalues    EBANDS =        10.88281164
+  atomic energy  EATOM  =        53.53845706
+  ---------------------------------------------------
+  free energy    TOTEN  =        -3.74343117 eV
+
+  energy without entropy =       -3.74343117  energy(sigma->0) =       -3.74343117
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+
+
+----------------------------------------- Iteration    1(   8)  ---------------------------------------
+
+
+    POTLOK:  cpu time    0.02: real time    0.02
+    SETDIJ:  cpu time    0.01: real time    0.01
+     EDDAV:  cpu time    3.41: real time    3.41
+ BZINTS: Fermi energy:  8.093775;  3.000000 electrons
+         Band energy:  10.874623;  BLOECHL correction: -0.041847
+       DOS:  cpu time    0.02: real time    0.02
+    CHARGE:  cpu time    0.10: real time    0.10
+    MIXING:  cpu time    0.00: real time    0.00
+    --------------------------------------------
+      LOOP:  cpu time    3.56: real time    3.56
+
+ eigenvalue-minimisations  :  5700
+ total energy-change (2. order) :-0.3575765E-04  (-0.2563445E-03)
+ number of electron    3.0000000 magnetization   -0.0002771
+ augmentation part    -0.0381739 magnetization   -0.0009017
+
+ Broyden mixing:
+  rms(total) = 0.88922E-02    rms(broyden)= 0.88922E-02
+  rms(prec ) = 0.95960E-02
+  weight for this iteration     100.00
+
+ eigenvalues of (default mixing * dielectric matrix)
+  average eigenvalue GAMMA=   1.4006
+  2.5744  0.9389  0.6885
+
+ Free energy of the ion-electron system (eV)
+  ---------------------------------------------------
+  alpha Z        PSCENC =        -0.20486981
+  Ewald energy   TEWEN  =       -73.67253674
+  -1/2 Hartree   DENC   =        -0.10476980
+  -exchange  EXHF       =         0.00000000
+  -V(xc)+E(xc)   XCENC  =       -26.11802900
+  PAW double counting   =        35.65312182       -3.70946333
+  entropy T*S    EENTRO =         0.00000000
+  eigenvalues    EBANDS =        10.87462287
+  atomic energy  EATOM  =        53.53845706
+  ---------------------------------------------------
+  free energy    TOTEN  =        -3.74346693 eV
+
+  energy without entropy =       -3.74346693  energy(sigma->0) =       -3.74346693
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+
+
+----------------------------------------- Iteration    1(   9)  ---------------------------------------
+
+
+    POTLOK:  cpu time    0.02: real time    0.02
+    SETDIJ:  cpu time    0.01: real time    0.01
+     EDDAV:  cpu time    3.81: real time    3.80
+ BZINTS: Fermi energy:  8.093928;  3.000000 electrons
+         Band energy:  10.875150;  BLOECHL correction: -0.041849
+       DOS:  cpu time    0.02: real time    0.02
+    CHARGE:  cpu time    0.10: real time    0.10
+    MIXING:  cpu time    0.00: real time    0.00
+    --------------------------------------------
+      LOOP:  cpu time    3.96: real time    3.96
+
+ eigenvalue-minimisations  :  6606
+ total energy-change (2. order) : 0.1090099E-03  (-0.6682625E-05)
+ number of electron    3.0000000 magnetization    0.0001953
+ augmentation part    -0.0381911 magnetization    0.0004059
+
+ Broyden mixing:
+  rms(total) = 0.16276E-02    rms(broyden)= 0.16276E-02
+  rms(prec ) = 0.30007E-02
+  weight for this iteration     100.00
+
+ eigenvalues of (default mixing * dielectric matrix)
+  average eigenvalue GAMMA=   1.2690
+  2.6225  0.9707  0.8497  0.6331
+
+ Free energy of the ion-electron system (eV)
+  ---------------------------------------------------
+  alpha Z        PSCENC =        -0.20486981
+  Ewald energy   TEWEN  =       -73.67253674
+  -1/2 Hartree   DENC   =        -0.10535854
+  -exchange  EXHF       =         0.00000000
+  -V(xc)+E(xc)   XCENC  =       -26.11741776
+  PAW double counting   =        35.65916718       -3.71594965
+  entropy T*S    EENTRO =         0.00000000
+  eigenvalues    EBANDS =        10.87515034
+  atomic energy  EATOM  =        53.53845706
+  ---------------------------------------------------
+  free energy    TOTEN  =        -3.74335792 eV
+
+  energy without entropy =       -3.74335792  energy(sigma->0) =       -3.74335792
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+
+
+----------------------------------------- Iteration    1(  10)  ---------------------------------------
+
+
+    POTLOK:  cpu time    0.02: real time    0.02
+    SETDIJ:  cpu time    0.01: real time    0.01
+     EDDAV:  cpu time    4.05: real time    4.05
+ BZINTS: Fermi energy:  8.094086;  3.000000 electrons
+         Band energy:  10.875646;  BLOECHL correction: -0.041850
+       DOS:  cpu time    0.02: real time    0.02
+    CHARGE:  cpu time    0.10: real time    0.10
+    MIXING:  cpu time    0.00: real time    0.00
+    --------------------------------------------
+      LOOP:  cpu time    4.21: real time    4.20
+
+ eigenvalue-minimisations  :  7116
+ total energy-change (2. order) : 0.1876910E-05  (-0.8060209E-06)
+ number of electron    3.0000000 magnetization   -0.0000056
+ augmentation part    -0.0381999 magnetization   -0.0000720
+
+ Broyden mixing:
+  rms(total) = 0.73926E-03    rms(broyden)= 0.73926E-03
+  rms(prec ) = 0.15734E-02
+  weight for this iteration     100.00
+
+ eigenvalues of (default mixing * dielectric matrix)
+  average eigenvalue GAMMA=   1.3757
+  2.6231  1.8389  0.9607  0.8275  0.6284
+
+ Free energy of the ion-electron system (eV)
+  ---------------------------------------------------
+  alpha Z        PSCENC =        -0.20486981
+  Ewald energy   TEWEN  =       -73.67253674
+  -1/2 Hartree   DENC   =        -0.10582417
+  -exchange  EXHF       =         0.00000000
+  -V(xc)+E(xc)   XCENC  =       -26.11693323
+  PAW double counting   =        35.66596946       -3.72326493
+  entropy T*S    EENTRO =         0.00000000
+  eigenvalues    EBANDS =        10.87564632
+  atomic energy  EATOM  =        53.53845706
+  ---------------------------------------------------
+  free energy    TOTEN  =        -3.74335604 eV
+
+  energy without entropy =       -3.74335604  energy(sigma->0) =       -3.74335604
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+
+
+----------------------------------------- Iteration    1(  11)  ---------------------------------------
+
+
+    POTLOK:  cpu time    0.02: real time    0.02
+    SETDIJ:  cpu time    0.01: real time    0.01
+     EDDAV:  cpu time    3.41: real time    3.41
+ BZINTS: Fermi energy:  8.094246;  3.000000 electrons
+         Band energy:  10.876169;  BLOECHL correction: -0.041851
+       DOS:  cpu time    0.02: real time    0.02
+    CHARGE:  cpu time    0.11: real time    0.11
+    MIXING:  cpu time    0.00: real time    0.00
+    --------------------------------------------
+      LOOP:  cpu time    3.57: real time    3.57
+
+ eigenvalue-minimisations  :  5718
+ total energy-change (2. order) :-0.2318165E-05  (-0.2318034E-06)
+ number of electron    3.0000000 magnetization    0.0000082
+ augmentation part    -0.0382086 magnetization   -0.0000018
+
+ Broyden mixing:
+  rms(total) = 0.12175E-03    rms(broyden)= 0.12175E-03
+  rms(prec ) = 0.14755E-03
+  weight for this iteration     100.00
+
+ eigenvalues of (default mixing * dielectric matrix)
+  average eigenvalue GAMMA=   1.4001
+  2.6387  2.5571  0.9682  0.8619  0.7479  0.6265
+
+ Free energy of the ion-electron system (eV)
+  ---------------------------------------------------
+  alpha Z        PSCENC =        -0.20486981
+  Ewald energy   TEWEN  =       -73.67253674
+  -1/2 Hartree   DENC   =        -0.10642957
+  -exchange  EXHF       =         0.00000000
+  -V(xc)+E(xc)   XCENC  =       -26.11626805
+  PAW double counting   =        35.67330599       -3.73118626
+  entropy T*S    EENTRO =         0.00000000
+  eigenvalues    EBANDS =        10.87616902
+  atomic energy  EATOM  =        53.53845706
+  ---------------------------------------------------
+  free energy    TOTEN  =        -3.74335836 eV
+
+  energy without entropy =       -3.74335836  energy(sigma->0) =       -3.74335836
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+
+
+----------------------------------------- Iteration    1(  12)  ---------------------------------------
+
+
+    POTLOK:  cpu time    0.02: real time    0.02
+    SETDIJ:  cpu time    0.01: real time    0.01
+     EDDAV:  cpu time    2.29: real time    2.29
+ BZINTS: Fermi energy:  8.094245;  3.000000 electrons
+         Band energy:  10.876169;  BLOECHL correction: -0.041851
+       DOS:  cpu time    0.02: real time    0.02
+    --------------------------------------------
+      LOOP:  cpu time    2.34: real time    2.34
+
+ eigenvalue-minimisations  :  3078
+ total energy-change (2. order) :-0.3140946E-06  (-0.3960422E-07)
+ number of electron    3.0000000 magnetization    0.0000082
+ augmentation part    -0.0382086 magnetization   -0.0000018
+
+ Free energy of the ion-electron system (eV)
+  ---------------------------------------------------
+  alpha Z        PSCENC =        -0.20486981
+  Ewald energy   TEWEN  =       -73.67253674
+  -1/2 Hartree   DENC   =        -0.10646068
+  -exchange  EXHF       =         0.00000000
+  -V(xc)+E(xc)   XCENC  =       -26.11623001
+  PAW double counting   =        35.67323357       -3.73112122
+  entropy T*S    EENTRO =         0.00000000
+  eigenvalues    EBANDS =        10.87616915
+  atomic energy  EATOM  =        53.53845706
+  ---------------------------------------------------
+  free energy    TOTEN  =        -3.74335867 eV
+
+  energy without entropy =       -3.74335867  energy(sigma->0) =       -3.74335867
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+
+
+ average (electrostatic) potential at core
+  the test charge radii are     1.0406
+  (the norm of the test charge is              1.0000)
+       1 -72.5590
+ 
+ 
+ 
+ E-fermi :   8.0942     XC(G=0): -10.2200     alpha+bet :-14.9718
+   add alpha+bet to get absolut eigen values
+
+ spin component 1
+
+ k-point   1 :       0.0000    0.0000    0.0000
+  band No.  band energies     occupation 
+      1      -3.1118      1.00000
+      2      20.7214      0.00000
+      3      20.7214      0.00000
+      4      20.7214      0.00000
+      5      22.2613      0.00000
+      6      22.2613      0.00000
+
+ k-point   2 :       0.0526    0.0000    0.0000
+  band No.  band energies     occupation 
+      1      -3.0362      1.00000
+      2      19.3192      0.00000
+      3      20.4408      0.00000
+      4      20.4408      0.00000
+      5      22.6602      0.00000
+      6      22.6602      0.00000
+
+ k-point   3 :       0.1053    0.0000    0.0000
+  band No.  band energies     occupation 
+      1      -2.8095      1.00000
+      2      17.2163      0.00000
+      3      19.9594      0.00000
+      4      19.9594      0.00000
+      5      22.8939      0.00000
+      6      23.4741      0.00000
+
+ k-point   4 :       0.1579    0.0000    0.0000
+  band No.  band energies     occupation 
+      1      -2.4326      1.00000
+      2      15.0838      0.00000
+      3      19.5256      0.00000
+      4      19.5256      0.00000
+      5      22.7469      0.00000
+      6      24.1771      0.00000
+
+ k-point   5 :       0.2105    0.0000    0.0000
+  band No.  band energies     occupation 
+      1      -1.9065      1.00000
+      2      13.0128      0.00000
+      3      19.1937      0.00000
+      4      19.1937      0.00000
+      5      22.5768      0.00000
+      6      23.6003      0.00000
+
+ k-point   6 :       0.2632    0.0000    0.0000
+  band No.  band energies     occupation 
+      1      -1.2331      1.00000
+      2      11.0340      0.00000
+      3      18.9786      0.00000
+      4      18.9786      0.00000
+      5      22.4609      0.00000
+      6      22.6497      0.00000
+
+ k-point   7 :       0.3158    0.0000    0.0000
+  band No.  band energies     occupation 
+      1      -0.4142      1.00000
+      2       9.1627     -0.06441
+      3      18.8857      0.00000
+      4      18.8857      0.00000
+      5      21.7585      0.00000
+      6      21.7585      0.00000
+
+ k-point   8 :       0.3684    0.0000    0.0000
+  band No.  band energies     occupation 
+      1       0.5475      1.00000
+      2       7.4080      0.96988
+      3      18.9177      0.00000
+      4      18.9177      0.00000
+      5      20.9749      0.00000
+      6      20.9749      0.00000
+
+ k-point   9 :       0.4211    0.0000    0.0000
+  band No.  band energies     occupation 
+      1       1.6490      1.00000
+      2       5.7764      1.00000
+      3      19.0758      0.00000
+      4      19.0758      0.00000
+      5      20.3114      0.00000
+      6      20.3114      0.00000
+
+ k-point  10 :       0.4737    0.0000    0.0000
+  band No.  band energies     occupation 
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+      2       4.2769      1.00000
+      3      19.3606      0.00000
+      4      19.3606      0.00000
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+      6      19.7728      0.00000
+
+ k-point  11 :       0.0526    0.0526    0.0000
+  band No.  band energies     occupation 
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+      3      19.7769      0.00000
+      4      20.0217      0.00000
+      5      22.0175      0.00000
+      6      23.3543      0.00000
+
+ k-point  12 :       0.1053    0.0526    0.0000
+  band No.  band energies     occupation 
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+      4      20.0798      0.00000
+      5      22.1588      0.00000
+      6      23.7455      0.00000
+
+ k-point  13 :       0.1579    0.0526    0.0000
+  band No.  band energies     occupation 
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+
+ k-point  14 :       0.2105    0.0526    0.0000
+  band No.  band energies     occupation 
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+
+ k-point  15 :       0.2632    0.0526    0.0000
+  band No.  band energies     occupation 
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+      3      18.0064      0.00000
+      4      19.3308      0.00000
+      5      21.4806      0.00000
+      6      23.3620      0.00000
+
+ k-point  16 :       0.3158    0.0526    0.0000
+  band No.  band energies     occupation 
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+      5      20.5290      0.00000
+      6      23.1781      0.00000
+
+ k-point  17 :       0.3684    0.0526    0.0000
+  band No.  band energies     occupation 
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+      3      17.8531      0.00000
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+      5      19.6913      0.00000
+      6      22.3695      0.00000
+
+ k-point  18 :       0.4211    0.0526    0.0000
+  band No.  band energies     occupation 
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+      3      17.9670      0.00000
+      4      18.9590      0.00000
+      5      19.3471      0.00000
+      6      21.6725      0.00000
+
+ k-point  19 :       0.4737    0.0526    0.0000
+  band No.  band energies     occupation 
+      1       2.5226      1.00000
+      2       4.8241      1.00000
+      3      18.2088      0.00000
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+      5      19.5967      0.00000
+      6      21.0959      0.00000
+
+ k-point  20 :      -0.4737    0.0526    0.0000
+  band No.  band energies     occupation 
+      1       3.3722      1.00000
+      2       3.8862      1.00000
+      3      17.9106      0.00000
+      4      18.5787      0.00000
+      5      19.9792      0.00000
+      6      20.6435      0.00000
+
+ k-point  21 :      -0.4211    0.0526    0.0000
+  band No.  band energies     occupation 
+      1       2.1111      1.00000
+      2       5.3239      1.00000
+      3      17.5784      0.00000
+      4      19.0761      0.00000
+      5      20.3173      0.00000
+      6      20.4896      0.00000
+
+ k-point  22 :      -0.3684    0.0526    0.0000
+  band No.  band energies     occupation 
+      1       0.9647      1.00000
+      2       6.9116      1.06330
+      3      17.3765      0.00000
+      4      19.6958      0.00000
+      5      20.1217      0.00000
+      6      21.1246      0.00000
+
+ k-point  23 :      -0.3158    0.0526    0.0000
+  band No.  band energies     occupation 
+      1      -0.0436      1.00000
+      2       8.6239      0.09710
+      3      17.3048      0.00000
+      4      20.0243      0.00000
+      5      20.4670      0.00000
+      6      21.8769      0.00000
+
+ k-point  24 :      -0.2632    0.0526    0.0000
+  band No.  band energies     occupation 
+      1      -0.9099      1.00000
+      2      10.4538      0.00000
+      3      17.3630      0.00000
+      4      20.0751      0.00000
+      5      21.3307      0.00000
+      6      22.7076      0.00000
+
+ k-point  25 :      -0.2105    0.0526    0.0000
+  band No.  band energies     occupation 
+      1      -1.6318      1.00000
+      2      12.3919      0.00000
+      3      17.5506      0.00000
+      4      20.2381      0.00000
+      5      22.2949      0.00000
+      6      23.0515      0.00000
+
+ k-point  26 :      -0.1579    0.0526    0.0000
+  band No.  band energies     occupation 
+      1      -2.2069      1.00000
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+      3      17.8675      0.00000
+      4      20.5031      0.00000
+      5      23.1834      0.00000
+      6      23.1899      0.00000
+
+ k-point  27 :      -0.1053    0.0526    0.0000
+  band No.  band energies     occupation 
+      1      -2.6335      1.00000
+      2      16.5028      0.00000
+      3      18.3206      0.00000
+      4      20.8164      0.00000
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+      6      23.2903      0.00000
+
+ k-point  28 :      -0.0526    0.0526    0.0000
+  band No.  band energies     occupation 
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+      3      19.0462      0.00000
+      4      20.9176      0.00000
+      5      22.3888      0.00000
+      6      23.1628      0.00000
+
+ k-point  29 :       0.1053    0.1053    0.0000
+  band No.  band energies     occupation 
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+      3      18.4817      0.00000
+      4      18.7367      0.00000
+      5      21.3935      0.00000
+      6      23.7805      0.00000
+
+ k-point  30 :       0.1579    0.1053    0.0000
+  band No.  band energies     occupation 
+      1      -2.4325      1.00000
+      2      16.6239      0.00000
+      3      17.9175      0.00000
+      4      18.9626      0.00000
+      5      21.4076      0.00000
+      6      22.4674      0.00000
+
+ k-point  31 :       0.2105    0.1053    0.0000
+  band No.  band energies     occupation 
+      1      -2.0066      1.00000
+      2      14.5696      0.00000
+      3      17.4779      0.00000
+      4      18.9070      0.00000
+      5      21.1258      0.00000
+      6      22.2390      0.00000
+
+ k-point  32 :       0.2632    0.1053    0.0000
+  band No.  band energies     occupation 
+      1      -1.4323      1.00000
+      2      12.5565      0.00000
+      3      17.1647      0.00000
+      4      18.7277      0.00000
+      5      20.0097      0.00000
+      6      23.3234      0.00000
+
+ k-point  33 :       0.3158    0.1053    0.0000
+  band No.  band energies     occupation 
+      1      -0.7115      1.00000
+      2      10.6284      0.00000
+      3      16.9787      0.00000
+      4      18.5719      0.00000
+      5      19.0123      0.00000
+      6      24.5063      0.00000
+
+ k-point  34 :       0.3684    0.1053    0.0000
+  band No.  band energies     occupation 
+      1       0.1536      1.00000
+      2       8.8050      0.00249
+      3      16.9205      0.00000
+      4      18.0355      0.00000
+      5      18.6187      0.00000
+      6      23.8805      0.00000
+
+ k-point  35 :       0.4211    0.1053    0.0000
+  band No.  band energies     occupation 
+      1       1.1602      1.00000
+      2       7.0973      1.06837
+      3      16.9903      0.00000
+      4      17.2760      0.00000
+      5      18.6970      0.00000
+      6      23.1564      0.00000
+
+ k-point  36 :       0.4737    0.1053    0.0000
+  band No.  band energies     occupation 
+      1       2.3046      1.00000
+      2       5.5132      1.00000
+      3      16.6331      0.00000
+      4      17.1886      0.00000
+      5      18.9183      0.00000
+      6      22.5457      0.00000
+
+ k-point  37 :      -0.4737    0.1053    0.0000
+  band No.  band energies     occupation 
+      1       3.5614      1.00000
+      2       4.0800      1.00000
+      3      16.1200      0.00000
+      4      17.5155      0.00000
+      5      19.2738      0.00000
+      6      22.0553      0.00000
+
+ k-point  38 :      -0.4211    0.1053    0.0000
+  band No.  band energies     occupation 
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+      3      15.7398      0.00000
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+
+ k-point  39 :      -0.3684    0.1053    0.0000
+  band No.  band energies     occupation 
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+      3      15.4942      0.00000
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+
+ k-point  40 :      -0.3158    0.1053    0.0000
+  band No.  band energies     occupation 
+      1       0.4737      1.00000
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+      3      15.3849      0.00000
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+      5      21.1196      0.00000
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+
+ k-point  41 :      -0.2632    0.1053    0.0000
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+
+ k-point  42 :      -0.2105    0.1053    0.0000
+  band No.  band energies     occupation 
+      1      -1.2082      1.00000
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+      3      15.5894      0.00000
+      4      20.9877      0.00000
+      5      21.4885      0.00000
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+
+ k-point  43 :      -0.1579    0.1053    0.0000
+  band No.  band energies     occupation 
+      1      -1.8315      1.00000
+      2      13.8062      0.00000
+      3      15.9407      0.00000
+      4      21.5297      0.00000
+      5      22.0959      0.00000
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+
+ k-point  44 :      -0.1053    0.1053    0.0000
+  band No.  band energies     occupation 
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+
+ k-point  45 :       0.1579    0.1579    0.0000
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+
+ k-point  46 :       0.2105    0.1579    0.0000
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+
+ k-point  47 :       0.2632    0.1579    0.0000
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+
+ k-point  48 :       0.3158    0.1579    0.0000
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+
+ k-point  49 :       0.3684    0.1579    0.0000
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+
+ k-point  50 :       0.4211    0.1579    0.0000
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+
+ k-point  51 :       0.4737    0.1579    0.0000
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+
+ k-point  52 :      -0.4737    0.1579    0.0000
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+
+ k-point  53 :      -0.4211    0.1579    0.0000
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+
+ k-point  54 :      -0.3684    0.1579    0.0000
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+
+ k-point  55 :      -0.3158    0.1579    0.0000
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+
+ k-point  56 :      -0.2632    0.1579    0.0000
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+
+ k-point  57 :      -0.2105    0.1579    0.0000
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+
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+
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+
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+
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+      5      20.7943      0.00000
+      6      22.1528      0.00000
+
+ k-point 170 :      -0.4211    0.2105    0.1053
+  band No.  band energies     occupation 
+      1       3.6483      1.00000
+      2       5.0375      1.00000
+      3      13.9937      0.00000
+      4      14.6139      0.00000
+      5      21.0662      0.00000
+      6      21.6405      0.00000
+
+ k-point 171 :       0.3684    0.2632    0.1053
+  band No.  band energies     occupation 
+      1      -0.2167      1.00000
+      2      12.2191      0.00000
+      3      13.5971      0.00000
+      4      16.1228      0.00000
+      5      19.2494      0.00000
+      6      21.2624      0.00000
+
+ k-point 172 :       0.4211    0.2632    0.1053
+  band No.  band energies     occupation 
+      1       0.5467      1.00000
+      2      10.7600      0.00000
+      3      13.0247      0.00000
+      4      15.1172      0.00000
+      5      19.6670      0.00000
+      6      22.1520      0.00000
+
+ k-point 173 :       0.4737    0.2632    0.1053
+  band No.  band energies     occupation 
+      1       1.4521      1.00000
+      2       9.0868     -0.05895
+      3      12.8888      0.00000
+      4      14.2507      0.00000
+      5      19.8503      0.00000
+      6      23.4513      0.00000
+
+ k-point 174 :      -0.4737    0.2632    0.1053
+  band No.  band energies     occupation 
+      1       2.4960      1.00000
+      2       7.4661      0.95090
+      3      12.8992      0.00000
+      4      13.5698      0.00000
+      5      20.0487      0.00000
+      6      23.7498      0.00000
+
+ k-point 175 :      -0.4211    0.2632    0.1053
+  band No.  band energies     occupation 
+      1       3.6722      1.00000
+      2       5.9521      1.00000
+      3      12.7092      0.00000
+      4      13.3816      0.00000
+      5      20.3381      0.00000
+      6      23.2278      0.00000
+
+ k-point 176 :      -0.3684    0.2632    0.1053
+  band No.  band energies     occupation 
+      1       4.5050      1.00000
+      2       5.0320      1.00000
+      3      12.3063      0.00000
+      4      13.6916      0.00000
+      5      20.7382      0.00000
+      6      22.7715      0.00000
+
+ k-point 177 :      -0.3158    0.2632    0.1053
+  band No.  band energies     occupation 
+      1       3.2682      1.00000
+      2       6.4318      1.00000
+      3      11.9977      0.00000
+      4      14.1935      0.00000
+      5      21.2471      0.00000
+      6      22.4284      0.00000
+
+ k-point 178 :      -0.2632    0.2632    0.1053
+  band No.  band energies     occupation 
+      1       2.1339      1.00000
+      2       7.9679      0.60014
+      3      11.8388      0.00000
+      4      14.8424      0.00000
+      5      21.8012      0.00000
+      6      22.2450      0.00000
+
+ k-point 179 :      -0.2105    0.2632    0.1053
+  band No.  band energies     occupation 
+      1       1.1352      1.00000
+      2       9.5556     -0.00880
+      3      11.8866      0.00000
+      4      15.6284      0.00000
+      5      21.8634      0.00000
+      6      22.6456      0.00000
+
+ k-point 180 :      -0.1579    0.2632    0.1053
+  band No.  band energies     occupation 
+      1       0.2765      1.00000
+      2      10.9182      0.00000
+      3      12.4103      0.00000
+      4      16.5460      0.00000
+      5      21.4250      0.00000
+      6      22.8621      0.00000
+
+ k-point 181 :       0.4211    0.3158    0.1053
+  band No.  band energies     occupation 
+      1       0.8649      1.00000
+      2      11.4765      0.00000
+      3      12.8043      0.00000
+      4      13.7504      0.00000
+      5      18.5353      0.00000
+      6      20.6501      0.00000
+
+ k-point 182 :       0.4737    0.3158    0.1053
+  band No.  band energies     occupation 
+      1       1.7187      1.00000
+      2      10.1056      0.00000
+      3      12.2400      0.00000
+      4      12.9007      0.00000
+      5      19.0514      0.00000
+      6      21.6270      0.00000
+
+ k-point 183 :      -0.4737    0.3158    0.1053
+  band No.  band energies     occupation 
+      1       2.7107      1.00000
+      2       8.5215      0.13872
+      3      11.7809      0.00000
+      4      12.5305      0.00000
+      5      19.3331      0.00000
+      6      23.0753      0.00000
+
+ k-point 184 :      -0.4211    0.3158    0.1053
+  band No.  band energies     occupation 
+      1       3.8349      1.00000
+      2       6.9932      1.07147
+      3      11.1940      0.00000
+      4      12.6272      0.00000
+      5      19.6263      0.00000
+      6      24.5002      0.00000
+
+ k-point 185 :      -0.3684    0.3158    0.1053
+  band No.  band energies     occupation 
+      1       5.0547      1.00000
+      2       5.6005      1.00000
+      3      10.6999      0.00000
+      4      12.9343      0.00000
+      5      20.0092      0.00000
+      6      24.4570      0.00000
+
+ k-point 186 :      -0.3158    0.3158    0.1053
+  band No.  band energies     occupation 
+      1       4.2465      1.00000
+      2       6.4667      1.00000
+      3      10.3554      0.00000
+      4      13.3983      0.00000
+      5      20.5031      0.00000
+      6      24.0803      0.00000
+
+ k-point 187 :      -0.2632    0.3158    0.1053
+  band No.  band energies     occupation 
+      1       3.0760      1.00000
+      2       7.8779      0.80414
+      3      10.2219      0.00000
+      4      14.0059      0.00000
+      5      21.1106      0.00000
+      6      23.7134      0.00000
+
+ k-point 188 :      -0.2105    0.3158    0.1053
+  band No.  band energies     occupation 
+      1       2.0367      1.00000
+      2       9.0611     -0.09706
+      3      10.5821      0.00000
+      4      14.7509      0.00000
+      5      21.8204      0.00000
+      6      23.0969      0.00000
+
+ k-point 189 :       0.4737    0.3684    0.1053
+  band No.  band energies     occupation 
+      1       2.1293      1.00000
+      2      10.9190      0.00000
+      3      11.2452      0.00000
+      4      12.4667      0.00000
+      5      17.9930      0.00000
+      6      20.1677      0.00000
+
+ k-point 190 :      -0.4737    0.3684    0.1053
+  band No.  band energies     occupation 
+      1       3.0670      1.00000
+      2       9.6202      0.00000
+      3      10.4523      0.00000
+      4      12.0391      0.00000
+      5      18.6040      0.00000
+      6      21.2334      0.00000
+
+ k-point 191 :      -0.4211    0.3684    0.1053
+  band No.  band energies     occupation 
+      1       4.1338      1.00000
+      2       8.1333      0.46401
+      3       9.7705      0.00000
+      4      12.0738      0.00000
+      5      18.9806      0.00000
+      6      22.7831      0.00000
+
+ k-point 192 :      -0.3684    0.3684    0.1053
+  band No.  band energies     occupation 
+      1       5.3085      1.00000
+      2       6.7071      1.00822
+      3       9.2321     -0.01561
+      4      12.3263      0.00000
+      5      19.3664      0.00000
+      6      24.5033      0.00000
+
+ k-point 193 :      -0.3158    0.3684    0.1053
+  band No.  band energies     occupation 
+      1       5.3520      1.00000
+      2       6.5755      1.00000
+      3       8.9035     -0.00832
+      4      12.7417      0.00000
+      5      19.8401      0.00000
+      6      25.7047      0.00000
+
+ k-point 194 :      -0.2632    0.3684    0.1053
+  band No.  band energies     occupation 
+      1       4.1526      1.00000
+      2       7.5774      1.00899
+      3       9.0754      0.00000
+      4      13.3040      0.00000
+      5      20.4220      0.00000
+      6      25.1166      0.00000
+
+ k-point 195 :      -0.4737    0.4211    0.1053
+  band No.  band energies     occupation 
+      1       3.5601      1.00000
+      2       9.1691     -0.05435
+      3      10.5471      0.00000
+      4      12.0538      0.00000
+      5      17.6294      0.00000
+      6      19.8366      0.00000
+
+ k-point 196 :      -0.4211    0.4211    0.1053
+  band No.  band energies     occupation 
+      1       4.5577      1.00000
+      2       8.4122      0.21353
+      3       9.3976      0.00000
+      4      11.7352      0.00000
+      5      18.3334      0.00000
+      6      20.9911      0.00000
+
+ k-point 197 :      -0.3684    0.4211    0.1053
+  band No.  band energies     occupation 
+      1       5.6225      1.00000
+      2       7.7148      1.02543
+      3       8.1775      0.04018
+      4      11.8781      0.00000
+      5      18.8026      0.00000
+      6      22.6307      0.00000
+
+ k-point 198 :      -0.3158    0.4211    0.1053
+  band No.  band energies     occupation 
+      1       6.4667      1.00000
+      2       6.5650      1.00000
+      3       7.9527      0.34011
+      4      12.2301      0.00000
+      5      19.2790      0.00000
+      6      24.4554      0.00000
+
+ k-point 199 :      -0.4211    0.4737    0.1053
+  band No.  band energies     occupation 
+      1       5.0619      1.00000
+      2       7.3288      1.02599
+      3      10.3611      0.00000
+      4      11.8617      0.00000
+      5      17.4471      0.00000
+      6      19.6684      0.00000
+
+ k-point 200 :      -0.3684    0.4737    0.1053
+  band No.  band energies     occupation 
+      1       5.7275      1.00000
+      2       7.0860      1.02472
+      3       9.2918     -0.01587
+      4      11.6382      0.00000
+      5      18.2429      0.00000
+      6      20.9094      0.00000
+
+ k-point 201 :       0.4737    0.3158    0.1579
+  band No.  band energies     occupation 
+      1       1.3544      1.00000
+      2      10.1754      0.00000
+      3      11.6584      0.00000
+      4      14.1482      0.00000
+      5      20.7407      0.00000
+      6      22.4635      0.00000
+
+ k-point 202 :      -0.4737    0.3158    0.1579
+  band No.  band energies     occupation 
+      1       2.3022      1.00000
+      2       8.9019     -0.03514
+      3      11.2163      0.00000
+      4      13.3140      0.00000
+      5      21.3026      0.00000
+      6      23.2586      0.00000
+
+ k-point 203 :      -0.4211    0.3158    0.1579
+  band No.  band energies     occupation 
+      1       3.3857      1.00000
+      2       7.4032      1.00313
+      3      11.2426      0.00000
+      4      12.6291      0.00000
+      5      21.6170      0.00000
+      6      23.0141      0.00000
+
+ k-point 204 :      -0.3684    0.3158    0.1579
+  band No.  band energies     occupation 
+      1       4.5932      1.00000
+      2       5.9647      1.00000
+      3      11.4182      0.00000
+      4      12.1461      0.00000
+      5      21.9121      0.00000
+      6      22.5539      0.00000
+
+ k-point 205 :      -0.4737    0.3684    0.1579
+  band No.  band energies     occupation 
+      1       2.6140      1.00000
+      2       9.6183      0.00000
+      3      10.9939      0.00000
+      4      11.9717      0.00000
+      5      20.2106      0.00000
+      6      22.0534      0.00000
+
+ k-point 206 :      -0.4211    0.3684    0.1579
+  band No.  band energies     occupation 
+      1       3.6439      1.00000
+      2       8.4319      0.18290
+      3      10.5687      0.00000
+      4      11.3029      0.00000
+      5      20.8748      0.00000
+      6      23.1770      0.00000
+
+ k-point 207 :      -0.3684    0.3684    0.1579
+  band No.  band energies     occupation 
+      1       4.7984      1.00000
+      2       7.0256      1.07347
+      3      10.2964      0.00000
+      4      11.1087      0.00000
+      5      21.2977      0.00000
+      6      24.1036      0.00000
+
+ k-point 208 :      -0.3158    0.3684    0.1579
+  band No.  band energies     occupation 
+      1       5.6205      1.00000
+      2       6.1184      1.00000
+      3       9.9353      0.00000
+      4      11.3747      0.00000
+      5      21.7361      0.00000
+      6      23.7835      0.00000
+
+ k-point 209 :      -0.2632    0.3684    0.1579
+  band No.  band energies     occupation 
+      1       4.4085      1.00000
+      2       7.4103      1.03163
+      3       9.7253      0.00000
+      4      11.8641      0.00000
+      5      22.2478      0.00000
+      6      23.3342      0.00000
+
+ k-point 210 :      -0.2105    0.3684    0.1579
+  band No.  band energies     occupation 
+      1       3.2897      1.00000
+      2       8.5044      0.17657
+      3       9.9954      0.00000
+      4      12.5159      0.00000
+      5      22.5927      0.00000
+      6      22.8157      0.00000
+
+ k-point 211 :      -0.4211    0.4211    0.1579
+  band No.  band energies     occupation 
+      1       4.0386      1.00000
+      2       9.2469     -0.05375
+      3       9.5712      0.00000
+      4      10.9065      0.00000
+      5      19.8524      0.00000
+      6      21.7564      0.00000
+
+ k-point 212 :      -0.3684    0.4211    0.1579
+  band No.  band energies     occupation 
+      1       5.1251      1.00000
+      2       8.1306      0.62678
+      3       8.9981      0.00000
+      4      10.6153      0.00000
+      5      20.6126      0.00000
+      6      22.9978      0.00000
+
+ k-point 213 :      -0.3158    0.4211    0.1579
+  band No.  band energies     occupation 
+      1       6.2630      1.00000
+      2       6.8311      1.00084
+      3       8.5966     -0.01660
+      4      10.8192      0.00000
+      5      21.1306      0.00000
+      6      24.5947      0.00000
+
+ k-point 214 :      -0.2632    0.4211    0.1579
+  band No.  band energies     occupation 
+      1       5.5547      1.00000
+      2       7.2070      1.00013
+      3       8.6719     -0.00125
+      4      11.2561      0.00000
+      5      21.6602      0.00000
+      6      24.7904      0.00000
+
+ k-point 215 :      -0.3684    0.4737    0.1579
+  band No.  band energies     occupation 
+      1       5.5300      1.00000
+      2       7.7896      0.91748
+      3       9.0612      0.00000
+      4      10.6629      0.00000
+      5      19.6722      0.00000
+      6      21.6029      0.00000
+
+ k-point 216 :      -0.3158    0.4737    0.1579
+  band No.  band energies     occupation 
+      1       6.2818      1.00000
+      2       7.5875      1.00147
+      3       8.1449      0.02051
+      4      10.4946      0.00000
+      5      20.5246      0.00000
+      6      22.9307      0.00000
+
+ k-point 217 :      -0.3684    0.4211    0.2105
+  band No.  band energies     occupation 
+      1       4.7052      1.00000
+      2       8.1335      0.61614
+      3       9.4964      0.00000
+      4      10.5372      0.00000
+      5      22.2451      0.00000
+      6      23.5208      0.00000
+
+ k-point 218 :      -0.3158    0.4211    0.2105
+  band No.  band energies     occupation 
+      1       5.8741      1.00000
+      2       7.1294      1.01462
+      3       9.2563      0.00000
+      4      10.0727      0.00000
+      5      22.9952      0.00000
+      6      23.5935      0.00000
+
+ k-point 219 :      -0.3158    0.4737    0.2105
+  band No.  band energies     occupation 
+      1       6.1827      1.00000
+      2       7.9481      1.01234
+      3       8.3597      0.00000
+      4       9.6617      0.00000
+      5      22.0690      0.00000
+      6      23.5832      0.00000
+
+ k-point 220 :      -0.2632    0.4737    0.2105
+  band No.  band energies     occupation 
+      1       7.0104      1.00000
+      2       7.0218      1.00000
+      3       8.3554      0.00000
+      4       9.5848      0.00000
+      5      22.9451      0.00000
+      6      24.6219      0.00000
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+ soft charge-density along one line, spin component            1
+         0         1         2         3         4         5         6         7         8         9
+ total charge-density along one line
+ 
+ soft charge-density along one line, spin component            2
+         0         1         2         3         4         5         6         7         8         9
+ total charge-density along one line
+ 
+ pseudopotential strength for first ion, spin component:            1
+  8.442  -0.006   0.000   0.000   0.000   0.000   0.000   0.000
+ -0.006   0.000   0.000   0.000   0.000   0.000   0.000   0.000
+  0.000   0.000   1.988   0.000   0.000  -0.027   0.000   0.000
+  0.000   0.000   0.000   1.988   0.000   0.000  -0.027   0.000
+  0.000   0.000   0.000   0.000   1.988   0.000   0.000  -0.027
+  0.000   0.000  -0.027   0.000   0.000  -0.012   0.000   0.000
+  0.000   0.000   0.000  -0.027   0.000   0.000  -0.012   0.000
+  0.000   0.000   0.000   0.000  -0.027   0.000   0.000  -0.012
+ pseudopotential strength for first ion, spin component:            2
+  8.442  -0.006   0.000   0.000   0.000   0.000   0.000   0.000
+ -0.006   0.000   0.000   0.000   0.000   0.000   0.000   0.000
+  0.000   0.000   1.988   0.000   0.000  -0.027   0.000   0.000
+  0.000   0.000   0.000   1.988   0.000   0.000  -0.027   0.000
+  0.000   0.000   0.000   0.000   1.988   0.000   0.000  -0.027
+  0.000   0.000  -0.027   0.000   0.000  -0.012   0.000   0.000
+  0.000   0.000   0.000  -0.027   0.000   0.000  -0.012   0.000
+  0.000   0.000   0.000   0.000  -0.027   0.000   0.000  -0.012
+ total augmentation occupancy for first ion, spin component:            1
+  1.315  -0.489   0.000   0.000   0.000   0.000   0.000   0.000
+ -0.489   0.477   0.000   0.000   0.000   0.000   0.000   0.000
+  0.000   0.000   0.742   0.000   0.000  -0.149   0.000   0.000
+  0.000   0.000   0.000   0.742   0.000   0.000  -0.149   0.000
+  0.000   0.000   0.000   0.000   0.742   0.000   0.000  -0.149
+  0.000   0.000  -0.149   0.000   0.000   0.035   0.000   0.000
+  0.000   0.000   0.000  -0.149   0.000   0.000   0.035   0.000
+  0.000   0.000   0.000   0.000  -0.149   0.000   0.000   0.035
+ total augmentation occupancy for first ion, spin component:            2
+  0.000   0.000   0.000   0.000   0.000   0.000   0.000   0.000
+  0.000   0.000   0.000   0.000   0.000   0.000   0.000   0.000
+  0.000   0.000   0.000   0.000   0.000   0.000   0.000   0.000
+  0.000   0.000   0.000   0.000   0.000   0.000   0.000   0.000
+  0.000   0.000   0.000   0.000   0.000   0.000   0.000   0.000
+  0.000   0.000   0.000   0.000   0.000   0.000   0.000   0.000
+  0.000   0.000   0.000   0.000   0.000   0.000   0.000   0.000
+  0.000   0.000   0.000   0.000   0.000   0.000   0.000   0.000
+
+
+------------------------ aborting loop because EDIFF is reached ----------------------------------------
+
+
+ 
+
+
+ total charge     
+ 
+# of ion     s       p       d       tot
+----------------------------------------
+  1        0.425   0.343   0.000   0.768
+ 
+
+
+ magnetization (x)
+ 
+# of ion     s       p       d       tot
+----------------------------------------
+  1        0.000   0.000   0.000   0.000
+ 
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+
+  FREE ENERGIE OF THE ION-ELECTRON SYSTEM (eV)
+  ---------------------------------------------------
+  free  energy   TOTEN  =        -3.743359 eV
+
+  energy  without entropy=       -3.743359  energy(sigma->0) =       -3.743359
+ 
+    CHARGE:  cpu time    0.10: real time    0.10
+    FORLOC:  cpu time    0.00: real time    0.00
+    FORNL :  cpu time    0.28: real time    0.28
+    STRESS:  cpu time    0.82: real time    0.82
+    FORCOR:  cpu time    0.06: real time    0.06
+    FORHAR:  cpu time    0.01: real time    0.01
+    MIXING:  cpu time    0.00: real time    0.00
+
+  FORCE on cell =-STRESS in cart. coord.  units (eV):
+  Direction    XX          YY          ZZ          XY          YZ          ZX
+  --------------------------------------------------------------------------------------
+  Alpha Z    -0.20487    -0.20487    -0.20487
+  Ewald     -24.55751   -24.55751   -24.55751     0.00000     0.00000     0.00000
+  Hartree     0.03549     0.03549     0.03549     0.00000     0.00000     0.00000
+  E(xc)      -8.57786    -8.57786    -8.57786     0.00000     0.00000     0.00000
+  Local       0.39110     0.39110     0.39110     0.00000     0.00000     0.00000
+  n-local    18.94530    18.59888    19.03840     0.46272    -0.60732     0.54193
+  augment    -1.01915    -1.01915    -1.01915     0.00000     0.00000     0.00000
+  Kinetic    12.48013    11.05239    21.71112    -9.68929     8.44714    -6.26264
+  Fock        0.00000     0.00000     0.00000     0.00000     0.00000     0.00000
+  -------------------------------------------------------------------------------------
+  Total       0.00927     0.00927     0.00927     0.00000     0.00000     0.00000
+  in kB       0.90594     0.90594     0.90594     0.00000     0.00000     0.00000
+  external pressure =        0.91 kB  Pullay stress =        0.00 kB
+
+
+ VOLUME and BASIS-vectors are now :
+ -----------------------------------------------------------------------------
+  energy-cutoff  :      520.00
+  volume of cell :       16.39
+      direct lattice vectors                 reciprocal lattice vectors
+     0.000000000  2.016319000  2.016319000    -0.247976635  0.247976635  0.247976635
+     2.016319000  0.000000000  2.016319000     0.247976635 -0.247976635  0.247976635
+     2.016319000  2.016319000  0.000000000     0.247976635  0.247976635 -0.247976635
+
+  length of vectors
+     2.851505676  2.851505676  2.851505676     0.429508130  0.429508130  0.429508130
+
+
+ FORCES acting on ions
+    electron-ion (+dipol)            ewald-force                    non-local-force                 convergence-correction
+ -----------------------------------------------------------------------------------------------
+   -.178E-15 0.423E-16 -.250E-14   -.794E-16 -.361E-16 0.105E-15   0.000E+00 -.207E-24 0.207E-24   -.803E-17 -.461E-17 -.195E-17
+ -----------------------------------------------------------------------------------------------
+   -.178E-15 0.423E-16 -.250E-14   -.794E-16 -.361E-16 0.105E-15   0.000E+00 -.207E-24 0.207E-24   -.803E-17 -.461E-17 -.195E-17
+ 
+ 
+ POSITION                                       TOTAL-FORCE (eV/Angst)
+ -----------------------------------------------------------------------------------
+      0.00000      0.00000      0.00000         0.000000      0.000000      0.000000
+ -----------------------------------------------------------------------------------
+    total drift:                                0.000000      0.000000      0.000000
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+    POTLOK:  cpu time    0.03: real time    0.03
+
+
+--------------------------------------------------------------------------------------------------------
+
+
+  FORCES: max atom, RMS     0.000000    0.000000
+  FORCE total and by dimension    0.000000    0.000000
+     LOOP+:  cpu time   46.44: real time   46.60
+    4ORBIT:  cpu time    0.00: real time    0.00
+ 
+
+
+ total charge     
+ 
+# of ion     s       p       d       tot
+----------------------------------------
+  1        0.425   0.343   0.000   0.768
+ 
+
+
+ magnetization (x)
+ 
+# of ion     s       p       d       tot
+----------------------------------------
+  1        0.000   0.000   0.000   0.000
+ 
+ BZINTS: Fermi energy:  8.094245;  3.000000 electrons
+         Band energy:  10.876169;  BLOECHL correction: -0.041851
+
+ total amount of memory used by VASP on root node  33617. kBytes
+========================================================================
+
+   base      :    30000. kBytes
+   nonl-proj :      451. kBytes
+   fftplans  :      185. kBytes
+   grid      :     2131. kBytes
+   one-center:        6. kBytes
+   wavefun   :      844. kBytes
+ 
+  
+  
+ General timing and accounting informations for this job:
+ ========================================================
+  
+                  Total CPU time used (sec):       50.194
+                            User time (sec):       49.602
+                          System time (sec):        0.592
+                         Elapsed time (sec):       52.337
+  
+                   Maximum memory used (kb):       62900.
+                   Average memory used (kb):           0.
+  
+                          Minor page faults:       277580
+                          Major page faults:            5
+                 Voluntary context switches:        18669
diff --git a/notebooks/Al-static/POSCAR b/notebooks/Al-static/POSCAR
new file mode 100644
index 0000000..8e43408
--- /dev/null
+++ b/notebooks/Al-static/POSCAR
@@ -0,0 +1,9 @@
+Al1
+1.0
+  -0.0000000000000001    2.0205550799999998    2.0205550799999998
+   2.0205550799999998    0.0000000000000000    2.0205550799999998
+   2.0205550799999998    2.0205550799999998    0.0000000000000002
+Al
+1
+direct
+   0.0000000000000000    0.0000000000000000    0.0000000000000000 Al
diff --git a/notebooks/Al-static/POTCAR b/notebooks/Al-static/POTCAR
new file mode 100644
index 0000000..c8d9ecb
--- /dev/null
+++ b/notebooks/Al-static/POTCAR
@@ -0,0 +1,1768 @@
+ PAW_PBE Al 04Jan2001
+ 3.00000000000000000
+ parameters from PSCTR are:
+   VRHFIN =Al: s2p1
+   LEXCH  = PE
+   EATOM  =    53.5387 eV,    3.9350 Ry
+
+   TITEL  = PAW_PBE Al 04Jan2001
+   LULTRA =        F    use ultrasoft PP ?
+   IUNSCR =        1    unscreen: 0-lin 1-nonlin 2-no
+   RPACOR =    1.500    partial core radius
+   POMASS =   26.982; ZVAL   =    3.000    mass and valenz
+   RCORE  =    1.900    outmost cutoff radius
+   RWIGS  =    2.650; RWIGS  =    1.402    wigner-seitz radius (au A)
+   ENMAX  =  240.300; ENMIN  =  180.225 eV
+   ICORE  =        2    local potential
+   LCOR   =        T    correct aug charges
+   LPAW   =        T    paw PP
+   EAUG   =  291.052
+   DEXC   =    -.041
+   RMAX   =    2.974    core radius for proj-oper
+   RAUG   =    1.300    factor for augmentation sphere
+   RDEP   =    1.966    radius for radial grids
+   QCUT   =   -4.203; QGAM   =    8.405    optimization parameters
+ 
+   Description
+     l     E      TYP  RCUT    TYP  RCUT
+     0   .000     23  1.900
+     0   .000     23  1.900
+     1   .000     23  1.900
+     1  1.000     23  1.900
+     2   .000      7  1.900
+   Error from kinetic energy argument (eV)
+   NDATA  =      100
+   STEP   =   20.000   1.050
+  2.17      1.95      1.85      1.68      1.61      1.48      1.37      1.32
+  1.24      1.17      1.14      1.08      1.03      .977      .931      .886
+  .843      .801      .758      .695      .653      .611      .549      .509
+  .469      .413      .359      .325      .278      .235      .197      .163
+  .133      .107      .858E-01  .676E-01  .483E-01  .370E-01  .256E-01  .193E-01
+  .132E-01  .922E-02  .676E-02  .535E-02  .461E-02  .426E-02  .410E-02  .397E-02
+  .383E-02  .358E-02  .322E-02  .288E-02  .243E-02  .199E-02  .152E-02  .120E-02
+  .964E-03  .771E-03  .660E-03  .604E-03  .576E-03  .555E-03  .527E-03  .479E-03
+  .425E-03  .355E-03  .288E-03  .231E-03  .185E-03  .161E-03  .147E-03  .140E-03
+  .133E-03  .123E-03  .108E-03  .913E-04  .740E-04  .607E-04  .519E-04  .482E-04
+  .459E-04  .430E-04  .384E-04  .320E-04  .261E-04  .219E-04  .198E-04  .188E-04
+  .176E-04  .155E-04  .128E-04  .107E-04  .933E-05  .881E-05  .825E-05  .723E-05
+  .594E-05  .506E-05  .462E-05  .439E-05
+END of PSCTR-controll parameters
+ local part
+ 98.2657514061040160
+  -.11196040E+01  -.11177563E+01  -.11049391E+01  -.10835857E+01  -.10537102E+01
+  -.10153337E+01  -.96848653E+00  -.91320931E+00  -.84955472E+00  -.77758869E+00
+  -.69739125E+00  -.60905702E+00  -.51269522E+00  -.40842942E+00  -.29639696E+00
+  -.17674840E+00  -.49646910E-01   .84732128E-01   .22620132E+00   .37456122E+00
+   .52960001E+00   .69109312E+00   .85880261E+00   .10324767E+01   .12118494E+01
+   .13966402E+01   .15865537E+01   .17812803E+01   .19804960E+01   .21838631E+01
+   .23910305E+01   .26016344E+01   .28152987E+01   .30316358E+01   .32502469E+01
+   .34707226E+01   .36926434E+01   .39155809E+01   .41390977E+01   .43627492E+01
+   .45860841E+01   .48086459E+01   .50299739E+01   .52496049E+01   .54670742E+01
+   .56819175E+01   .58936719E+01   .61018779E+01   .63060802E+01   .65058297E+01
+   .67006847E+01   .68902126E+01   .70739913E+01   .72516109E+01   .74226751E+01
+   .75868032E+01   .77436311E+01   .78928134E+01   .80340244E+01   .81669598E+01
+   .82913377E+01   .84069000E+01   .85134133E+01   .86106704E+01   .86984902E+01
+   .87767197E+01   .88452338E+01   .89039366E+01   .89527612E+01   .89916710E+01
+   .90206591E+01   .90397490E+01   .90489941E+01   .90484779E+01   .90383136E+01
+   .90186433E+01   .89896376E+01   .89514949E+01   .89044406E+01   .88487257E+01
+   .87846262E+01   .87124416E+01   .86324938E+01   .85451255E+01   .84506988E+01
+   .83495936E+01   .82422058E+01   .81289454E+01   .80102351E+01   .78865077E+01
+   .77582050E+01   .76257751E+01   .74896708E+01   .73503477E+01   .72082620E+01
+   .70638688E+01   .69176200E+01   .67699625E+01   .66213364E+01   .64721729E+01
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+   .31320672E+01   .30842840E+01   .30395585E+01   .29977073E+01   .29585414E+01
+   .29218677E+01   .28874903E+01   .28552118E+01   .28248347E+01   .27961629E+01
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+ gradient corrections used for XC
+ 5
+ core charge-density (partial)
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+  -.74847025E+00  -.61481243E+00  -.46932237E+00  -.31847831E+00  -.16838293E+00
+ Real Space Part
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+ Non local Part
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+ 2.08596921736620722 -0.219845133596054454 -0.219845133596054454 0.318470468308045818E-01
+ Reciprocal Space Part
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+ Real Space Part
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+ Reciprocal Space Part
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+ Real Space Part
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+ PAW radial sets
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+(5E20.12)                                
+ augmentation charges (non sperical)
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+ pseudo wavefunction
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+ ae wavefunction
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+   .155938810029E+00   .148406454816E+00   .140305921417E+00   .131629170872E+00   .122369967322E+00
+   .112524063168E+00   .102089388722E+00   .910662453038E-01   .794575005932E-01   .672687848695E-01
+   .545086865818E-01   .411889454619E-01   .273246411261E-01   .129343748029E-01  -.195955851944E-02
+  -.173310105740E-01  -.331498362275E-01  -.493817691556E-01  -.659883197062E-01  -.829266968104E-01
+  -.100149753968E+00  -.117605956929E+00  -.135239368407E+00  -.152989644229E+00  -.170792036977E+00
+  -.188577408208E+00  -.206272258061E+00  -.223798789436E+00  -.241075029578E+00  -.258015031229E+00
+  -.274529166790E+00  -.290524514526E+00  -.305905322466E+00  -.320573529993E+00  -.334429330413E+00
+  -.347371765868E+00  -.359299352910E+00  -.370110740101E+00  -.379705398299E+00  -.387984341669E+00
+  -.394850874597E+00  -.400211357493E+00  -.403975983236E+00  -.406059555664E+00  -.406382261714E+00
+  -.404870429344E+00  -.401457264083E+00  -.396083557705E+00  -.388698363249E+00  -.379259631204E+00
+  -.367734802263E+00  -.354101352553E+00  -.338347287644E+00  -.320471581939E+00  -.300484560161E+00
+  -.278408217619E+00  -.254276475696E+00  -.228135368564E+00  -.200043156559E+00  -.170070360989E+00
+  -.138299714482E+00  -.104826020564E+00  -.697559161095E-01  -.332075309935E-01   .468995907276E-02
+   .437968875875E-01   .839637569512E-01   .125031994062E+00   .166834787031E+00   .209197983033E+00
+   .251941024863E+00   .294877906607E+00   .337818139334E+00   .380567737962E+00   .422930271764E+00
+   .464708065076E+00   .505703692588E+00   .545721983159E+00   .584572800861E+00   .622074818376E+00
+   .658060116054E+00   .692378435674E+00   .724898373014E+00   .755502088508E+00   .784072893555E+00
+   .810481564956E+00   .834581011566E+00   .856213260446E+00   .875223044045E+00   .891469665881E+00
+   .904833586733E+00   .915218814120E+00   .922553366029E+00
+ pseudo wavefunction
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+   .132147293857E-05   .136444394173E-05   .140881225471E-05   .145462331452E-05   .150192403570E-05
+   .155076285831E-05   .160118979757E-05   .165325649508E-05   .170701627168E-05   .176252418208E-05
+   .181983707122E-05   .187901363250E-05   .194011446790E-05   .200320215000E-05   .206834128610E-05
+   .213559858435E-05   .220504292211E-05   .227674541644E-05   .235077949694E-05   .242722098099E-05
+   .250614815133E-05   .258764183626E-05   .267178549244E-05   .275866529032E-05   .284837020237E-05
+   .294099209426E-05   .303662581889E-05   .313536931352E-05   .323732370010E-05   .334259338882E-05
+   .345128618501E-05   .356351339957E-05   .367938996295E-05   .379903454284E-05   .392256966572E-05
+   .405012184230E-05   .418182169713E-05   .431780410231E-05   .445820831567E-05   .460317812334E-05
+   .475286198700E-05   .490741319595E-05   .506699002406E-05   .523175589187E-05   .540187953394E-05
+   .557753517164E-05   .575890269159E-05   .594616782988E-05   .613952236223E-05   .633916430044E-05
+   .654529809515E-05   .675813484521E-05   .697789251385E-05   .720479615194E-05   .743907812839E-05
+   .768097836817E-05   .793074459799E-05   .818863260000E-05   .845490647371E-05   .872983890646E-05
+   .901371145270E-05   .930681482226E-05   .960944917812E-05   .992192444377E-05   .102445606206E-04
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+   .145668268047E-04   .150405035020E-04   .155295829666E-04   .160345660564E-04   .165559699157E-04
+   .170943285048E-04   .176501931469E-04   .182241330927E-04   .188167361032E-04   .194286090515E-04
+   .200603785446E-04   .207126915648E-04   .213862161322E-04   .220816419889E-04   .227996813051E-04
+   .235410694088E-04   .243065655381E-04   .250969536193E-04   .259130430693E-04   .267556696244E-04
+   .276256961961E-04   .285240137551E-04   .294515422428E-04   .304092315139E-04   .313980623089E-04
+   .324190472581E-04   .334732319187E-04   .345616958451E-04   .356855536944E-04   .368459563677E-04
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+   .446451360499E-04   .460968795866E-04   .475958297065E-04   .491435214001E-04   .507415395670E-04
+   .523915206379E-04   .540951542505E-04   .558541849783E-04   .576704141166E-04   .595457015265E-04
+   .614819675379E-04   .634811949153E-04   .655454308869E-04   .676767892399E-04   .698774524831E-04
+   .721496740809E-04   .744957807587E-04   .769181748838E-04   .794193369231E-04   .820018279810E-04
+   .846682924192E-04   .874214605617E-04   .902641514875E-04   .931992759141E-04   .962298391737E-04
+   .993589442868E-04   .102589795135E-03   .105925699735E-03   .109370073625E-03   .112926443349E-03
+   .116598450065E-03   .120389853267E-03   .124304534623E-03   .128346501942E-03   .132519893268E-03
+   .136828981104E-03   .141278176777E-03   .145872034937E-03   .150615258212E-03   .155512702001E-03
+   .160569379428E-03   .165790466457E-03   .171181307168E-03   .176747419204E-03   .182494499394E-03
+   .188428429555E-03   .194555282482E-03   .200881328130E-03   .207413039993E-03   .214157101689E-03
+   .221120413750E-03   .228310100640E-03   .235733517985E-03   .243398260041E-03   .251312167397E-03
+   .259483334923E-03   .267920119971E-03   .276631150834E-03   .285625335473E-03   .294911870522E-03
+   .304500250573E-03   .314400277753E-03   .324622071607E-03   .335176079278E-03   .346073086018E-03
+   .357324226016E-03   .368940993566E-03   .380935254579E-03   .393319258448E-03   .406105650279E-03
+   .419307483489E-03   .432938232799E-03   .447011807604E-03   .461542565758E-03   .476545327760E-03
+   .492035391373E-03   .508028546662E-03   .524541091479E-03   .541589847398E-03   .559192176104E-03
+   .577365996251E-03   .596129800798E-03   .615502674823E-03   .635504313828E-03   .656155042550E-03
+   .677475834256E-03   .699488330565E-03   .722214861764E-03   .745678467648E-03   .769902918871E-03
+   .794912738803E-03   .820733225907E-03   .847390476612E-03   .874911408686E-03   .903323785092E-03
+   .932656238314E-03   .962938295141E-03   .994200401866E-03   .102647394990E-02   .105979130174E-02
+   .109418581728E-02   .112969188034E-02   .116634492554E-02   .120418146514E-02   .124323911614E-02
+   .128355662722E-02   .132517390562E-02   .136813204376E-02   .141247334546E-02   .145824135158E-02
+   .150548086498E-02   .155423797443E-02   .160456007735E-02   .165649590104E-02   .171009552210E-02
+   .176541038358E-02   .182249330953E-02   .188139851640E-02   .194218162070E-02   .200489964235E-02
+   .206961100281E-02   .213637551739E-02   .220525438041E-02   .227631014244E-02   .234960667806E-02
+   .242520914277E-02   .250318391728E-02   .258359853735E-02   .266652160675E-02   .275202269087E-02
+   .284017218797E-02   .293104117465E-02   .302470122158E-02   .312122417502E-02   .322068189888E-02
+   .332314597122E-02   .342868732849E-02   .353737584931E-02   .364927986874E-02   .376446561243E-02
+   .388299653843E-02   .400493257248E-02   .413032922085E-02   .425923654164E-02   .439169795324E-02
+   .452774885501E-02   .466741503139E-02   .481071080661E-02   .495763691170E-02   .510817802009E-02
+   .526229990132E-02   .541994613458E-02   .558103431548E-02   .574545167907E-02   .591305005102E-02
+   .608364002558E-02   .625698425450E-02   .643278971390E-02   .661069879712E-02   .679027906019E-02
+   .697101142189E-02   .715227659331E-02   .733333948095E-02   .751333127352E-02   .769122888430E-02
+   .786583137942E-02   .803573297624E-02   .819929214612E-02   .835459630174E-02   .849942149162E-02
+   .863118646359E-02   .874690039581E-02   .884310353006E-02   .891579987863E-02   .896038111628E-02
+   .897154071534E-02   .894317733976E-02   .886828648780E-02   .873883937084E-02   .854564804555E-02
+   .827821588990E-02   .792457264284E-02   .747109342965E-02   .690230148784E-02   .620065471569E-02
+   .534631671129E-02   .431691368429E-02   .308727953746E-02   .162919256556E-02  -.888913590440E-04
+  -.210210251381E-02  -.444940929413E-02  -.717384730825E-02  -.103227116583E-01  -.139476952572E-01
+  -.181049524656E-01  -.228550634831E-01  -.282628708988E-01  -.343971557975E-01  -.413301170779E-01
+  -.491366145502E-01  -.578931344278E-01  -.676764356335E-01  -.785618376897E-01  -.906211167620E-01
+  -.103919986731E+00  -.118505750633E+00  -.134448326467E+00
+ ae wavefunction
+  -.152371601917E-04  -.157299019590E-04  -.162385629939E-04  -.167636566274E-04  -.173057126811E-04
+  -.178652779934E-04  -.184429169611E-04  -.190392120983E-04  -.196547646134E-04  -.202901950026E-04
+  -.209461436638E-04  -.216232715277E-04  -.223222607100E-04  -.230438151831E-04  -.237886614686E-04
+  -.245575493518E-04  -.253512526173E-04  -.261705698084E-04  -.270163250094E-04  -.278893686514E-04
+  -.287905783442E-04  -.297208597322E-04  -.306811473778E-04  -.316724056706E-04  -.326956297657E-04
+  -.337518465488E-04  -.348421156325E-04  -.359675303811E-04  -.371292189675E-04  -.383283454616E-04
+  -.395661109510E-04  -.408437546962E-04  -.421625553195E-04  -.435238320298E-04  -.449289458839E-04
+  -.463793010845E-04  -.478763463179E-04  -.494215761292E-04  -.510165323401E-04  -.526628055057E-04
+  -.543620364160E-04  -.561159176396E-04  -.579261951122E-04  -.597946697712E-04  -.617231992366E-04
+  -.637136995408E-04  -.657681469059E-04  -.678885795728E-04  -.700770996803E-04  -.723358751980E-04
+  -.746671419117E-04  -.770732054642E-04  -.795564434521E-04  -.821193075793E-04  -.847643258694E-04
+  -.874941049366E-04  -.903113323184E-04  -.932187788689E-04  -.962193012152E-04  -.993158442777E-04
+  -.102511443856E-03  -.105809229277E-03  -.109212426119E-03  -.112724358991E-03  -.116348454391E-03
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+  -.907124582617E-03  -.934792499471E-03  -.963247033520E-03  -.992506734014E-03  -.102259032150E-02
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+  -.356331741057E-02  -.364438167103E-02  -.372608567133E-02  -.380834476223E-02  -.389106687738E-02
+  -.397415217609E-02  -.405749268150E-02  -.414097191535E-02  -.422446453080E-02  -.430783594500E-02
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+  -.479672757831E-02  -.487463092805E-02  -.495096132197E-02  -.502548551938E-02  -.509795785457E-02
+  -.516812003450E-02  -.523570097357E-02  -.530041667025E-02  -.536197013098E-02  -.542005134663E-02
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+  -.567664410605E-02  -.570067094716E-02  -.571829624860E-02  -.572910352812E-02  -.573266732666E-02
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+  -.444335189958E-02  -.425698021466E-02  -.405600143384E-02  -.384017513006E-02  -.360929946841E-02
+  -.336321479125E-02  -.310180719642E-02  -.282501207578E-02  -.253281757733E-02  -.222526795134E-02
+  -.190246673658E-02  -.156457973854E-02  -.121183774652E-02  -.844538930161E-03  -.463050849624E-03
+  -.678120067335E-04   .340667140122E-03   .761803773724E-03   .119494299313E-02   .163935880230E-02
+   .209425579900E-02   .255877148356E-02   .303197903813E-02   .351289038583E-02   .400045935951E-02
+   .449358491434E-02   .499111449780E-02   .549184789751E-02   .599454203852E-02   .649791720417E-02
+   .700066495056E-02   .750145762264E-02   .799895902097E-02   .849183558674E-02   .897876752013E-02
+   .945845942579E-02   .992965024698E-02   .103911223243E-01   .108417093948E-01   .112803032765E-01
+   .117058588972E-01   .121173972601E-01   .125140058923E-01   .128948362979E-01   .132590979347E-01
+   .136060482342E-01   .139349781989E-01   .142451931268E-01   .145359880292E-01   .148066173351E-01
+   .150562584989E-01   .152839691643E-01   .154886375714E-01   .156689259419E-01   .158232066241E-01
+   .159494908365E-01   .160453499067E-01   .161078289685E-01   .161333531430E-01   .161176262967E-01
+   .160555225330E-01   .159409706311E-01   .157668317025E-01   .155247703815E-01   .152051199191E-01
+   .147967416081E-01   .142868790633E-01   .136610080333E-01   .129026826654E-01   .119933795112E-01
+   .109123410538E-01   .963642112230E-02   .813993513239E-02   .639451848116E-02   .436899635077E-02
+   .202926726703E-02  -.661799589696E-03  -.374445792893E-02  -.726218107493E-02  -.112617840548E-01
+  -.157935974468E-01  -.209116960300E-01  -.266741034650E-01  -.331427650790E-01  -.403830423964E-01
+  -.484627327506E-01  -.574510452014E-01  -.674180448767E-01  -.784346356823E-01  -.905727218722E-01
+  -.103905208579E+00  -.118505750633E+00  -.134448326467E+00
+ pseudo wavefunction
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diff --git a/notebooks/Al-static/vasprun.xml.gz b/notebooks/Al-static/vasprun.xml.gz
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zZqeGnYiwnFrrOaVjGHgWHU7~f;S0;=5$zHPy3#LP_|CRW|13ma2mRTc+|KXxe^>xM
P{=ui*Hf&6xM@9G_$P0Nl

literal 0
HcmV?d00001

diff --git a/notebooks/Al.cif b/notebooks/Al.cif
new file mode 100644
index 0000000..163e0d5
--- /dev/null
+++ b/notebooks/Al.cif
@@ -0,0 +1,27 @@
+# generated using pymatgen
+data_Al
+_symmetry_space_group_name_H-M   'P 1'
+_cell_length_a   2.85749640
+_cell_length_b   2.85749640
+_cell_length_c   2.85749640
+_cell_angle_alpha   60.00000000
+_cell_angle_beta   60.00000000
+_cell_angle_gamma   60.00000000
+_symmetry_Int_Tables_number   1
+_chemical_formula_structural   Al
+_chemical_formula_sum   Al1
+_cell_volume   16.49840943
+_cell_formula_units_Z   1
+loop_
+ _symmetry_equiv_pos_site_id
+ _symmetry_equiv_pos_as_xyz
+  1  'x, y, z'
+loop_
+ _atom_site_type_symbol
+ _atom_site_label
+ _atom_site_symmetry_multiplicity
+ _atom_site_fract_x
+ _atom_site_fract_y
+ _atom_site_fract_z
+ _atom_site_occupancy
+  Al  Al0  1  0.00000000  0.00000000  0.00000000  1
diff --git a/notebooks/Si-relax.cif b/notebooks/Si-relax.cif
new file mode 100644
index 0000000..163e0d5
--- /dev/null
+++ b/notebooks/Si-relax.cif
@@ -0,0 +1,27 @@
+# generated using pymatgen
+data_Al
+_symmetry_space_group_name_H-M   'P 1'
+_cell_length_a   2.85749640
+_cell_length_b   2.85749640
+_cell_length_c   2.85749640
+_cell_angle_alpha   60.00000000
+_cell_angle_beta   60.00000000
+_cell_angle_gamma   60.00000000
+_symmetry_Int_Tables_number   1
+_chemical_formula_structural   Al
+_chemical_formula_sum   Al1
+_cell_volume   16.49840943
+_cell_formula_units_Z   1
+loop_
+ _symmetry_equiv_pos_site_id
+ _symmetry_equiv_pos_as_xyz
+  1  'x, y, z'
+loop_
+ _atom_site_type_symbol
+ _atom_site_label
+ _atom_site_symmetry_multiplicity
+ _atom_site_fract_x
+ _atom_site_fract_y
+ _atom_site_fract_z
+ _atom_site_occupancy
+  Al  Al0  1  0.00000000  0.00000000  0.00000000  1
diff --git a/notebooks/Si-relax/KPOINTS b/notebooks/Si-relax/KPOINTS
deleted file mode 100644
index 7f1ff74..0000000
--- a/notebooks/Si-relax/KPOINTS
+++ /dev/null
@@ -1,4 +0,0 @@
-pymatgen with grid density = 787 / number of atoms
-0
-Gamma
-7 7 7
diff --git a/notebooks/Si-relax/POSCAR b/notebooks/Si-relax/POSCAR
deleted file mode 100644
index bff1a67..0000000
--- a/notebooks/Si-relax/POSCAR
+++ /dev/null
@@ -1,10 +0,0 @@
-Si2
-1.0
-  -2.7218511849999998   -2.7218511849999998    0.0000000000000000
-  -2.7218511849999998    0.0000000000000000   -2.7218511849999998
-   0.0000000000000002   -2.7218511849999998   -2.7218511849999998
-Si
-2
-direct
-   0.0000000000000000    0.0000000000000000    0.0000000000000000 Si
-   0.7500000000000000    0.7500000000000000    0.7500000000000000 Si
diff --git a/notebooks/Si-relax/POTCAR b/notebooks/Si-relax/POTCAR
deleted file mode 100644
index ae2291f..0000000
--- a/notebooks/Si-relax/POTCAR
+++ /dev/null
@@ -1,1768 +0,0 @@
- PAW_PBE Si 05Jan2001
- 4.00000000000000000
- parameters from PSCTR are:
-   VRHFIN =Si: s2p2
-   LEXCH  = PE
-   EATOM  =   103.0669 eV,    7.5752 Ry
-
-   TITEL  = PAW_PBE Si 05Jan2001
-   LULTRA =        F    use ultrasoft PP ?
-   IUNSCR =        1    unscreen: 0-lin 1-nonlin 2-no
-   RPACOR =    1.500    partial core radius
-   POMASS =   28.085; ZVAL   =    4.000    mass and valenz
-   RCORE  =    1.900    outmost cutoff radius
-   RWIGS  =    2.480; RWIGS  =    1.312    wigner-seitz radius (au A)
-   ENMAX  =  245.345; ENMIN  =  184.009 eV
-   ICORE  =        2    local potential
-   LCOR   =        T    correct aug charges
-   LPAW   =        T    paw PP
-   EAUG   =  322.069
-   DEXC   =    -.007
-   RMAX   =    2.944    core radius for proj-oper
-   RAUG   =    1.300    factor for augmentation sphere
-   RDEP   =    1.993    radius for radial grids
-   QCUT   =   -4.246; QGAM   =    8.493    optimization parameters
- 
-   Description
-     l     E      TYP  RCUT    TYP  RCUT
-     0   .000     23  1.900
-     0   .000     23  1.900
-     1   .000     23  1.900
-     1   .000     23  1.900
-     2   .000      7  1.900
-   Error from kinetic energy argument (eV)
-   NDATA  =      100
-   STEP   =   20.000   1.050
-  10.1      9.04      8.56      7.65      7.23      6.44      5.73      5.40
-  4.79      4.25      4.00      3.54      3.13      2.77      2.45      2.16
-  1.91      1.69      1.50      1.24      1.10      .975      .812      .718
-  .636      .529      .440      .388      .322      .266      .219      .180
-  .148      .121      .986E-01  .804E-01  .614E-01  .504E-01  .392E-01  .328E-01
-  .265E-01  .220E-01  .189E-01  .166E-01  .149E-01  .135E-01  .123E-01  .109E-01
-  .977E-02  .840E-02  .707E-02  .605E-02  .488E-02  .387E-02  .290E-02  .229E-02
-  .185E-02  .152E-02  .134E-02  .125E-02  .121E-02  .117E-02  .112E-02  .102E-02
-  .915E-03  .776E-03  .640E-03  .524E-03  .425E-03  .369E-03  .331E-03  .310E-03
-  .294E-03  .273E-03  .242E-03  .210E-03  .175E-03  .146E-03  .124E-03  .113E-03
-  .105E-03  .973E-04  .879E-04  .755E-04  .633E-04  .539E-04  .478E-04  .438E-04
-  .404E-04  .362E-04  .308E-04  .264E-04  .229E-04  .209E-04  .192E-04  .170E-04
-  .145E-04  .126E-04  .112E-04  .103E-04
-END of PSCTR-controll parameters
- local part
- 98.2657514061040160
-   .84157696E+01   .84210616E+01   .84276868E+01   .84387430E+01   .84542501E+01
-   .84742336E+01   .84987229E+01   .85277486E+01   .85613410E+01   .85995276E+01
-   .86423322E+01   .86897735E+01   .87418643E+01   .87986117E+01   .88600162E+01
-   .89260725E+01   .89967686E+01   .90720854E+01   .91519966E+01   .92364669E+01
-   .93254512E+01   .94188926E+01   .95167214E+01   .96188530E+01   .97251866E+01
-   .98356042E+01   .99499691E+01   .10068126E+02   .10189900E+02   .10315095E+02
-   .10443498E+02   .10574872E+02   .10708964E+02   .10845497E+02   .10984178E+02
-   .11124691E+02   .11266702E+02   .11409858E+02   .11553785E+02   .11698096E+02
-   .11842382E+02   .11986223E+02   .12129182E+02   .12270810E+02   .12410650E+02
-   .12548232E+02   .12683081E+02   .12814718E+02   .12942658E+02   .13066416E+02
-   .13185509E+02   .13299456E+02   .13407780E+02   .13510014E+02   .13605699E+02
-   .13694388E+02   .13775652E+02   .13849074E+02   .13914259E+02   .13970835E+02
-   .14018449E+02   .14056778E+02   .14085523E+02   .14104415E+02   .14113216E+02
-   .14111719E+02   .14099752E+02   .14077176E+02   .14043889E+02   .13999825E+02
-   .13944955E+02   .13879288E+02   .13802872E+02   .13715793E+02   .13618173E+02
-   .13510175E+02   .13391996E+02   .13263872E+02   .13126073E+02   .12978903E+02
-   .12822702E+02   .12657838E+02   .12484712E+02   .12303753E+02   .12115415E+02
-   .11920177E+02   .11718543E+02   .11511033E+02   .11298186E+02   .11080557E+02
-   .10858712E+02   .10633228E+02   .10404688E+02   .10173679E+02   .99407918E+01
-   .97066146E+01   .94717325E+01   .92367246E+01   .90021609E+01   .87686001E+01
-   .85365874E+01   .83066514E+01   .80793026E+01   .78550308E+01   .76343035E+01
-   .74175636E+01   .72052280E+01   .69976861E+01   .67952984E+01   .65983952E+01
-   .64072758E+01   .62222076E+01   .60434252E+01   .58711303E+01   .57054911E+01
-   .55466426E+01   .53946862E+01   .52496902E+01   .51116906E+01   .49806911E+01
-   .48566645E+01   .47395534E+01   .46292712E+01   .45257038E+01   .44287105E+01
-   .43381258E+01   .42537607E+01   .41754049E+01   .41028282E+01   .40357822E+01
-   .39740031E+01   .39172124E+01   .38651203E+01   .38174267E+01   .37738238E+01
-   .37339979E+01   .36976315E+01   .36644056E+01   .36340010E+01   .36061008E+01
-   .35803917E+01   .35565663E+01   .35343243E+01   .35133745E+01   .34934357E+01
-   .34742388E+01   .34555274E+01   .34370596E+01   .34186083E+01   .33999627E+01
-   .33809285E+01   .33613290E+01   .33410052E+01   .33198164E+01   .32976401E+01
-   .32743723E+01   .32499276E+01   .32242387E+01   .31972561E+01   .31689481E+01
-   .31393000E+01   .31083133E+01   .30760055E+01   .30424087E+01   .30075693E+01
-   .29715463E+01   .29344112E+01   .28962459E+01   .28571426E+01   .28172018E+01
-   .27765317E+01   .27352466E+01   .26934662E+01   .26513138E+01   .26089155E+01
-   .25663991E+01   .25238927E+01   .24815236E+01   .24394173E+01   .23976966E+01
-   .23564804E+01   .23158831E+01   .22760134E+01   .22369739E+01   .21988600E+01
-   .21617599E+01   .21257533E+01   .20909116E+01   .20572974E+01   .20249638E+01
-   .19939548E+01   .19643045E+01   .19360379E+01   .19091701E+01   .18837069E+01
-   .18596450E+01   .18369720E+01   .18156670E+01   .17957010E+01   .17770368E+01
-   .17596305E+01   .17434311E+01   .17283816E+01   .17144193E+01   .17014768E+01
-   .16894823E+01   .16783607E+01   .16680338E+01   .16584212E+01   .16494415E+01
-   .16410120E+01   .16330504E+01   .16254746E+01   .16182040E+01   .16111597E+01
-   .16042653E+01   .15974473E+01   .15906355E+01   .15837638E+01   .15767703E+01
-   .15695978E+01   .15621941E+01   .15545123E+01   .15465111E+01   .15381544E+01
-   .15294125E+01   .15202610E+01   .15106817E+01   .15006619E+01   .14901947E+01
-   .14792788E+01   .14679182E+01   .14561221E+01   .14439046E+01   .14312844E+01
-   .14182846E+01   .14049321E+01   .13912574E+01   .13772942E+01   .13630791E+01
-   .13486509E+01   .13340503E+01   .13193195E+01   .13045019E+01   .12896412E+01
-   .12747815E+01   .12599666E+01   .12452397E+01   .12306428E+01   .12162167E+01
-   .12020006E+01   .11880314E+01   .11743437E+01   .11609697E+01   .11479386E+01
-   .11352766E+01   .11230067E+01   .11111486E+01   .10997186E+01   .10887293E+01
-   .10781902E+01   .10681067E+01   .10584813E+01   .10493127E+01   .10405964E+01
-   .10323246E+01   .10244865E+01   .10170685E+01   .10100542E+01   .10034245E+01
-   .99715846E+00   .99123280E+00   .98562260E+00   .98030145E+00   .97524173E+00
-   .97041488E+00   .96579171E+00   .96134265E+00   .95703806E+00   .95284844E+00
-   .94874473E+00   .94469858E+00   .94068254E+00   .93667031E+00   .93263696E+00
-   .92855909E+00   .92441506E+00   .92018509E+00   .91585142E+00   .91139842E+00
-   .90681263E+00   .90208291E+00   .89720039E+00   .89215854E+00   .88695315E+00
-   .88158229E+00   .87604630E+00   .87034770E+00   .86449110E+00   .85848313E+00
-   .85233229E+00   .84604884E+00   .83964465E+00   .83313300E+00   .82652847E+00
-   .81984671E+00   .81310428E+00   .80631845E+00   .79950703E+00   .79268813E+00
-   .78588003E+00   .77910097E+00   .77236895E+00   .76570159E+00   .75911593E+00
-   .75262828E+00   .74625407E+00   .74000773E+00   .73390251E+00   .72795041E+00
-   .72216209E+00   .71654675E+00   .71111209E+00   .70586428E+00   .70080787E+00
-   .69594584E+00   .69127954E+00   .68680877E+00   .68253173E+00   .67844513E+00
-   .67454418E+00   .67082274E+00   .66727331E+00   .66388721E+00   .66065462E+00
-   .65756473E+00   .65460586E+00   .65176555E+00   .64903076E+00   .64638795E+00
-   .64382325E+00   .64132257E+00   .63887178E+00   .63645678E+00   .63406371E+00
-   .63167900E+00   .62928956E+00   .62688288E+00   .62444710E+00   .62197118E+00
-   .61944494E+00   .61685919E+00   .61420575E+00   .61147755E+00   .60866866E+00
-   .60577434E+00   .60279104E+00   .59971643E+00   .59654939E+00   .59329003E+00
-   .58993961E+00   .58650056E+00   .58297643E+00   .57937181E+00   .57569230E+00
-   .57194440E+00   .56813547E+00   .56427363E+00   .56036764E+00   .55642683E+00
-   .55246099E+00   .54848026E+00   .54449503E+00   .54051583E+00   .53655322E+00
-   .53261771E+00   .52871961E+00   .52486898E+00   .52107551E+00   .51734843E+00
-   .51369641E+00   .51012750E+00   .50664907E+00   .50326768E+00   .49998911E+00
-   .49681824E+00   .49375908E+00   .49081468E+00   .48798715E+00   .48527763E+00
-   .48268632E+00   .48021244E+00   .47785431E+00   .47560930E+00   .47347392E+00
-   .47144387E+00   .46951402E+00   .46767855E+00   .46593095E+00   .46426412E+00
-   .46267047E+00   .46114194E+00   .45967012E+00   .45824632E+00   .45686169E+00
-   .45550723E+00   .45417395E+00   .45285292E+00   .45153535E+00   .45021267E+00
-   .44887661E+00   .44751931E+00   .44613331E+00   .44471171E+00   .44324816E+00
-   .44173692E+00   .44017295E+00   .43855190E+00   .43687017E+00   .43512491E+00
-   .43331405E+00   .43143631E+00   .42949120E+00   .42747899E+00   .42540073E+00
-   .42325823E+00   .42105400E+00   .41879126E+00   .41647384E+00   .41410622E+00
-   .41169341E+00   .40924089E+00   .40675462E+00   .40424088E+00   .40170629E+00
-   .39915769E+00   .39660209E+00   .39404660E+00   .39149835E+00   .38896445E+00
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-   .36383915E+00   .36193261E+00   .36010239E+00   .35834945E+00   .35667414E+00
-   .35507613E+00   .35355450E+00   .35210772E+00   .35073362E+00   .34942953E+00
-   .34819219E+00   .34701788E+00   .34590241E+00   .34484117E+00   .34382921E+00
-   .34286125E+00   .34193178E+00   .34103506E+00   .34016522E+00   .33931629E+00
-   .33848229E+00   .33765725E+00   .33683525E+00   .33601054E+00   .33517754E+00
-   .33433091E+00   .33346559E+00   .33257683E+00   .33166028E+00   .33071198E+00
-   .32972841E+00   .32870651E+00   .32764370E+00   .32653791E+00   .32538758E+00
-   .32419168E+00   .32294968E+00   .32166161E+00   .32032797E+00   .31894980E+00
-   .31752862E+00   .31606640E+00   .31456556E+00   .31302895E+00   .31145977E+00
-   .30986158E+00   .30823823E+00   .30659385E+00   .30493275E+00   .30325946E+00
-   .30157859E+00   .29989486E+00   .29821301E+00   .29653778E+00   .29487386E+00
-   .29322581E+00   .29159807E+00   .28999490E+00   .28842031E+00   .28687807E+00
-   .28537164E+00   .28390415E+00   .28247839E+00   .28109677E+00   .27976132E+00
-   .27847363E+00   .27723491E+00   .27604592E+00   .27490700E+00   .27381809E+00
-   .27277867E+00   .27178784E+00   .27084428E+00   .26994630E+00   .26909186E+00
-   .26827855E+00   .26750369E+00   .26676430E+00   .26605715E+00   .26537882E+00
-   .26472568E+00   .26409398E+00   .26347988E+00   .26287945E+00   .26228874E+00
-   .26170381E+00   .26112076E+00   .26053579E+00   .25994520E+00   .25934545E+00
-   .25873320E+00   .25810531E+00   .25745888E+00   .25679129E+00   .25610022E+00
-   .25538363E+00   .25463983E+00   .25386744E+00   .25306545E+00   .25223318E+00
-   .25137030E+00   .25047684E+00   .24955316E+00   .24859996E+00   .24761829E+00
-   .24660949E+00   .24557519E+00   .24451731E+00   .24343801E+00   .24233971E+00
-   .24122498E+00   .24009659E+00   .23895746E+00   .23781060E+00   .23665912E+00
-   .23550617E+00   .23435492E+00   .23320855E+00   .23207016E+00   .23094281E+00
-   .22982945E+00   .22873289E+00   .22765579E+00   .22660063E+00   .22556967E+00
-   .22456498E+00   .22358834E+00   .22264131E+00   .22172517E+00   .22084092E+00
-   .21998928E+00   .21917068E+00   .21838526E+00   .21763287E+00   .21691308E+00
-   .21622517E+00   .21556818E+00   .21494086E+00   .21434175E+00   .21376913E+00
-   .21322111E+00   .21269560E+00   .21219035E+00   .21170297E+00   .21123098E+00
-   .21077179E+00   .21032276E+00   .20988120E+00   .20944443E+00   .20900979E+00
-   .20857462E+00   .20813639E+00   .20769262E+00   .20724095E+00   .20677916E+00
-   .20630522E+00   .20581722E+00   .20531350E+00   .20479256E+00   .20425315E+00
-   .20369424E+00   .20311502E+00   .20251496E+00   .20189372E+00   .20125124E+00
-   .20058769E+00   .19990349E+00   .19919926E+00   .19847589E+00   .19773443E+00
-   .19697618E+00   .19620258E+00   .19541527E+00   .19461602E+00   .19380673E+00
-   .19298941E+00   .19216618E+00   .19133918E+00   .19051063E+00   .18968276E+00
-   .18885780E+00   .18803797E+00   .18722542E+00   .18642227E+00   .18563052E+00
-   .18485209E+00   .18408877E+00   .18334220E+00   .18261388E+00   .18190512E+00
-   .18121707E+00   .18055068E+00   .17990670E+00   .17928569E+00   .17868800E+00
-   .17811376E+00   .17756291E+00   .17703518E+00   .17653009E+00   .17604697E+00
-   .17558497E+00   .17514306E+00   .17472002E+00   .17431452E+00   .17392507E+00
-   .17355005E+00   .17318776E+00   .17283640E+00   .17249410E+00   .17215895E+00
-   .17182901E+00   .17150232E+00   .17117693E+00   .17085094E+00   .17052245E+00
-   .17018966E+00   .16985084E+00   .16950435E+00   .16914867E+00   .16878242E+00
-   .16840433E+00   .16801331E+00   .16760841E+00   .16718886E+00   .16675406E+00
-   .16630358E+00   .16583717E+00   .16535477E+00   .16485650E+00   .16434264E+00
-   .16381366E+00   .16327018E+00   .16271301E+00   .16214308E+00   .16156147E+00
-   .16096939E+00   .16036817E+00   .15975923E+00   .15914407E+00   .15852427E+00
-   .15790145E+00   .15727728E+00   .15665345E+00   .15603163E+00   .15541350E+00
-   .15480071E+00   .15419486E+00   .15359747E+00   .15301002E+00   .15243388E+00
-   .15187030E+00   .15132044E+00   .15078533E+00   .15026585E+00   .14976275E+00
-   .14927662E+00   .14880791E+00   .14835691E+00   .14792374E+00   .14750838E+00
-   .14711065E+00   .14673019E+00   .14636653E+00   .14601903E+00   .14568691E+00
-   .14536927E+00   .14506509E+00   .14477325E+00   .14449251E+00   .14422157E+00
-   .14395905E+00   .14370352E+00   .14345350E+00   .14320750E+00   .14296399E+00
-   .14272149E+00   .14247848E+00   .14223350E+00   .14198515E+00   .14173206E+00
-   .14147294E+00   .14120659E+00   .14093190E+00   .14064788E+00   .14035363E+00
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-   .12924998E+00   .12879027E+00   .12833900E+00   .12789721E+00   .12746584E+00
-   .12704575E+00   .12663767E+00   .12624224E+00   .12585999E+00   .12549130E+00
-   .12513646E+00   .12479563E+00   .12446883E+00   .12415596E+00   .12385682E+00
-   .12357106E+00   .12329824E+00   .12303778E+00   .12278902E+00   .12255119E+00
-   .12232344E+00   .12210482E+00   .12189434E+00   .12169092E+00   .12149346E+00
-   .12130080E+00   .12111176E+00   .12092515E+00   .12073978E+00   .12055446E+00
-   .12036801E+00   .12017930E+00   .11998723E+00   .11979076E+00   .11958890E+00
-   .11938073E+00   .11916544E+00   .11894226E+00   .11871055E+00   .11846975E+00
-   .11821943E+00   .11795923E+00   .11768892E+00   .11740838E+00   .11711760E+00
-   .11681667E+00   .11650581E+00   .11618532E+00   .11585561E+00   .11551720E+00
-   .11517070E+00   .11481679E+00   .11445623E+00   .11408986E+00   .11371858E+00
-   .11334333E+00   .11296511E+00   .11258491E+00   .11220379E+00   .11182279E+00
-   .11144296E+00   .11106534E+00   .11069096E+00   .11032079E+00   .10995580E+00
-   .10959689E+00   .10924491E+00   .10890064E+00   .10856478E+00   .10823798E+00
-   .10792077E+00   .10761362E+00   .10731688E+00   .10703084E+00   .10675565E+00
-   .10649140E+00   .10623807E+00   .10599552E+00   .10576356E+00   .10554186E+00
-   .10533004E+00   .10512760E+00   .10493399E+00   .10474857E+00   .10457063E+00
-   .10439942E+00   .10423412E+00   .10407387E+00   .10391779E+00   .10376497E+00
-   .10361446E+00   .10346535E+00   .10331669E+00   .10316756E+00   .10301705E+00
-   .10286430E+00   .10270846E+00   .10254874E+00   .10238439E+00   .10221475E+00
-   .10203918E+00   .10185715E+00   .10166820E+00   .10147193E+00   .10126804E+00
-   .10105631E+00   .10083661E+00   .10060889E+00   .10037320E+00   .10012965E+00
-   .99878467E-01   .99619932E-01   .99354416E-01   .99082363E-01   .98804288E-01
-   .98520765E-01   .98232428E-01   .97939960E-01   .97644087E-01   .97345569E-01
-   .97045195E-01   .96743772E-01   .96442116E-01   .96141050E-01   .95841391E-01
-   .95543942E-01   .95249488E-01   .94958785E-01   .94672554E-01   .94391474E-01
-   .94116174E-01   .93847229E-01   .93585152E-01   .93330392E-01   .93083329E-01
-   .92844268E-01   .92613442E-01   .92391008E-01   .92177045E-01   .91971556E-01
-   .91774467E-01   .91585628E-01   .91404815E-01   .91231735E-01   .91066024E-01
-   .90907255E-01   .90754941E-01   .90608543E-01   .90467470E-01   .90331093E-01
-   .90198744E-01   .90069732E-01   .89943339E-01   .89818838E-01   .89695492E-01
-   .89572566E-01   .89449332E-01   .89325075E-01   .89199102E-01   .89070749E-01
-   .88939383E-01   .88804416E-01   .88665301E-01   .88521548E-01   .88372720E-01
-   .88218440E-01   .88058396E-01   .87892342E-01   .87720097E-01   .87541550E-01
-   .87356660E-01   .87165453E-01   .86968025E-01   .86764537E-01   .86555218E-01
-   .86340357E-01   .86120303E-01   .85895462E-01   .85666290E-01   .85433289E-01
-   .85197004E-01   .84958012E-01   .84716921E-01   .84474359E-01   .84230970E-01
-   .83987410E-01   .83744335E-01   .83502399E-01   .83262247E-01   .83024506E-01
-   .82789784E-01   .82558658E-01   .82331673E-01   .82109336E-01   .81892108E-01
-   .81680401E-01   .81474576E-01   .81274938E-01   .81081732E-01   .80895145E-01
-   .80715299E-01   .80542258E-01   .80376020E-01   .80216523E-01   .80063643E-01
-   .79917196E-01   .79776941E-01   .79642582E-01   .79513768E-01   .79390103E-01
-   .79271145E-01   .79156412E-01   .79045389E-01   .78937532E-01   .78832272E-01
-   .78729025E-01   .78627196E-01   .78526182E-01   .78425382E-01   .78324201E-01
-   .78222055E-01   .78118379E-01   .78012628E-01   .77904287E-01   .77792874E-01
-   .77677943E-01   .77559095E-01   .77435971E-01   .77308267E-01   .77175728E-01
-   .77038154E-01   .76895403E-01   .76747386E-01   .76594073E-01   .76435492E-01
-   .76271726E-01   .76102913E-01   .75929245E-01   .75750968E-01   .75568374E-01
- gradient corrections used for XC
- 5
- core charge-density (partial)
-   .13681950E+01   .13676960E+01   .13662001E+01   .13637105E+01   .13602325E+01
-   .13557734E+01   .13503429E+01   .13439524E+01   .13366153E+01   .13283473E+01
-   .13191655E+01   .13090892E+01   .12981393E+01   .12863384E+01   .12737107E+01
-   .12602820E+01   .12460794E+01   .12311314E+01   .12154677E+01   .11991194E+01
-   .11821181E+01   .11644970E+01   .11462895E+01   .11275301E+01   .11082538E+01
-   .10884962E+01   .10682931E+01   .10476808E+01   .10266957E+01   .10053741E+01
-   .98375267E+00   .96186759E+00   .93975503E+00   .91745077E+00   .89499021E+00
-   .87240826E+00   .84973926E+00   .82701690E+00   .80427415E+00   .78154320E+00
-   .75885536E+00   .73624104E+00   .71372967E+00   .69134969E+00   .66912843E+00
-   .64709213E+00   .62526592E+00   .60367371E+00   .58233824E+00   .56128104E+00
-   .54052238E+00   .52008130E+00   .49997559E+00   .48022178E+00   .46083513E+00
-   .44182968E+00   .42321820E+00   .40501225E+00   .38722216E+00   .36985707E+00
-   .35292495E+00   .33643262E+00   .32038578E+00   .30478902E+00   .28964588E+00
-   .27495886E+00   .26072949E+00   .24695832E+00   .23364498E+00   .22078822E+00
-   .20838596E+00   .19643530E+00   .18493258E+00   .17387344E+00   .16325283E+00
-   .15306507E+00   .14330386E+00   .13396240E+00   .12503332E+00   .11650883E+00
-   .10838067E+00   .10064023E+00   .93278522E-01   .86286250E-01   .79653846E-01
-   .73371505E-01   .67429216E-01   .61816797E-01   .56523934E-01   .51540202E-01
-   .46855108E-01   .42458109E-01   .38338647E-01   .34486174E-01   .30890174E-01
-   .27540191E-01   .24425850E-01   .21536879E-01   .18863125E-01   .16394577E-01
-   .14121382E-01   .12033860E-01   .10122516E-01   .83780589E-02   .67914092E-02
-   .53537108E-02   .40563408E-02   .28909177E-02   .18493086E-02   .92363545E-03
-   .10628041E-03  -.61011044E-03  -.12326237E-02  -.17680763E-02  -.22230146E-02
-  -.26037134E-02  -.29161762E-02  -.31661368E-02  -.33590603E-02  -.35001462E-02
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-  -.28633344E-02  -.26967780E-02  -.25238182E-02  -.23464568E-02  -.21665171E-02
-  -.19856525E-02  -.18053531E-02  -.16269545E-02  -.14516446E-02  -.12804716E-02
-  -.11143516E-02  -.95407590E-03  -.80031868E-03  -.65364406E-03  -.51451335E-03
-  -.38329201E-03  -.26025656E-03  -.14560117E-03  -.39444206E-04   .58165516E-04
-   .14724263E-03   .22785937E-03   .30013989E-03   .36425487E-03   .42041630E-03
-   .46887251E-03   .50990347E-03   .54381628E-03   .57094091E-03   .59162620E-03
-   .60623608E-03   .61514601E-03   .61873968E-03   .61740593E-03   .61153588E-03
-   .60152031E-03   .58774722E-03   .57059965E-03   .55045362E-03   .52767640E-03
-   .50262485E-03   .47564400E-03   .44706580E-03   .41720805E-03   .38637350E-03
-   .35484906E-03   .32290522E-03   .29079555E-03   .25875641E-03   .22700669E-03
-   .19574775E-03   .16516340E-03   .13542004E-03   .10666685E-03   .79036088E-04
-   .52643451E-04   .27588517E-04   .39552464E-05  -.18187465E-04  -.38785178E-04
-  -.57797264E-04  -.75196221E-04  -.90966959E-04  -.10510606E-03  -.11762104E-03
-  -.12852953E-03  -.13785858E-03  -.14564378E-03  -.15192858E-03  -.15676343E-03
-  -.16020507E-03  -.16231575E-03  -.16316249E-03  -.16281641E-03  -.16135195E-03
-  -.15884628E-03  -.15537859E-03  -.15102952E-03  -.14588056E-03  -.14001345E-03
-  -.13350974E-03  -.12645021E-03  -.11891448E-03  -.11098056E-03  -.10272445E-03
-  -.94219808E-04  -.85537643E-04  -.76746000E-04  -.67909727E-04  -.59090263E-04
-  -.50345446E-04  -.41729367E-04  -.33292247E-04  -.25080349E-04  -.17135911E-04
-  -.94971159E-05  -.21980781E-05   .47311376E-05   .11264479E-04   .17379846E-04
-   .23059012E-04   .28287521E-04   .33054577E-04   .37352910E-04   .41178632E-04
-   .44531079E-04   .47412645E-04   .49828605E-04   .51786930E-04   .53298094E-04
-   .54374884E-04   .55032195E-04   .55286832E-04   .55157309E-04   .54663646E-04
-   .53827166E-04   .52670302E-04   .51216402E-04   .49489534E-04   .47514310E-04
-   .45315700E-04   .42918863E-04   .40348986E-04   .37631124E-04   .34790051E-04
-   .31850126E-04   .28835162E-04   .25768303E-04   .22671916E-04   .19567494E-04
-   .16475560E-04   .13415592E-04   .10405948E-04   .74638126E-05   .46051404E-05
-   .18446197E-05  -.80436009E-06  -.33297302E-05  -.57207550E-05  -.79680369E-05
-  -.10063512E-04  -.12000439E-04  -.13773381E-04  -.15378177E-04  -.16811912E-04
-  -.18072880E-04  -.19160536E-04  -.20075451E-04  -.20819258E-04  -.21394593E-04
-  -.21805038E-04  -.22055054E-04  -.22149917E-04  -.22095649E-04  -.21898951E-04
-  -.21567128E-04  -.21108022E-04  -.20529940E-04  -.19841582E-04  -.19051971E-04
-  -.18170387E-04  -.17206293E-04  -.16169276E-04  -.15068980E-04  -.13915042E-04
-  -.12717039E-04  -.11484427E-04  -.10226489E-04  -.89522887E-05  -.76706186E-05
-  -.63899617E-05  -.51184500E-05  -.38638299E-05  -.26334298E-05  -.14341327E-05
-  -.27235171E-06   .84599016E-06   .19154768E-05   .29312118E-05   .38888277E-05
-   .47844919E-05   .56149089E-05   .63773192E-05   .70694955E-05   .76897350E-05
-   .82368500E-05   .87101545E-05   .91094496E-05   .94350052E-05   .96875413E-05
-   .98682052E-05   .99785491E-05   .10020505E-04   .99963570E-05   .99087173E-05
-   .97604944E-05   .95548661E-05   .92952495E-05   .89852710E-05   .86287366E-05
-   .82296019E-05   .77919423E-05   .73199237E-05   .68177739E-05   .62897539E-05
-   .57401315E-05   .51731543E-05   .45930247E-05   .40038758E-05   .34097487E-05
-   .28145712E-05   .22221377E-05   .16360907E-05   .10599042E-05   .49686829E-06
-  -.49924253E-07  -.57759018E-06  -.10834658E-05  -.15651156E-05  -.20203391E-05
-  -.24471763E-05  -.28439110E-05  -.32090729E-05  -.35414382E-05  -.38400286E-05
-  -.41041086E-05  -.43331819E-05  -.45269862E-05  -.46854867E-05  -.48088688E-05
-  -.48975294E-05  -.49520671E-05  -.49732722E-05  -.49621152E-05  -.49197348E-05
-  -.48474253E-05  -.47466238E-05  -.46188963E-05  -.44659241E-05  -.42894897E-05
-  -.40914626E-05  -.38737848E-05  -.36384571E-05  -.33875243E-05  -.31230618E-05
-  -.28471617E-05  -.25619196E-05  -.22694215E-05  -.19717316E-05  -.16708804E-05
-  -.13688530E-05  -.10675792E-05  -.76892250E-06  -.47467171E-06  -.18653188E-06
-   .93883276E-07   .36505838E-06   .62558254E-06   .87415472E-06   .11095882E-05
-   .13308143E-05   .15368851E-05   .17269757E-05   .19003854E-05   .20565379E-05
-   .21949813E-05   .23153868E-05   .24175471E-05   .25013741E-05   .25668952E-05
-   .26142503E-05   .26436874E-05   .26555573E-05   .26503093E-05   .26284844E-05
-   .25907101E-05   .25376938E-05   .24702158E-05   .23891225E-05   .22953197E-05
-   .21897645E-05   .20734587E-05   .19474411E-05   .18127798E-05   .16705653E-05
-   .15219029E-05   .13679056E-05   .12096872E-05   .10483551E-05   .88500422E-06
-   .72071043E-06   .55652452E-06   .39346658E-06   .23252066E-06   .74629737E-07
-  -.79308789E-07  -.22844732E-06  -.37199180E-06  -.50920504E-06  -.63940961E-06
-  -.76199029E-06  -.87639606E-06  -.98214167E-06  -.10788088E-05  -.11660466E-05
-  -.12435721E-05  -.13111700E-05  -.13686922E-05  -.14160567E-05  -.14532461E-05
-  -.14803064E-05  -.14973448E-05  -.15045271E-05  -.15020754E-05  -.14902650E-05
-  -.14694216E-05  -.14399174E-05  -.14021681E-05  -.13566289E-05  -.13037909E-05
-  -.12441768E-05  -.11783371E-05  -.11068459E-05  -.10302970E-05  -.94929926E-06
-  -.86447308E-06  -.77644588E-06  -.68584828E-06  -.59331011E-06  -.49945662E-06
-  -.40490476E-06  -.31025967E-06  -.21611128E-06  -.12303110E-06  -.31569232E-07
-   .57748417E-07   .14442274E-06   .22798375E-06   .30799272E-06   .38404404E-06
-   .45576684E-06   .52282633E-06   .58492498E-06   .64180332E-06   .69324058E-06
-   .73905504E-06   .77910418E-06   .81328449E-06   .84153118E-06   .86381756E-06
-   .88015426E-06   .89058820E-06   .89520145E-06   .89410978E-06   .88746118E-06
-   .87543410E-06   .85823565E-06   .83609958E-06   .80928424E-06   .77807038E-06
-   .74275888E-06   .70366841E-06   .66113309E-06   .61550004E-06   .56712696E-06
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-   .26383351E+01   .24485880E+01   .21944773E+01   .18917574E+01   .15560536E+01
-   .12024051E+01   .84486462E+00   .49616263E+00   .16743966E+00  -.13195032E+00
-  -.39456569E+00  -.61493394E+00  -.78954326E+00  -.91677435E+00  -.99677914E+00
-  -.10313144E+01  -.10235387E+01  -.97778206E+00  -.89929746E+00  -.79400304E+00
-  -.66822444E+00  -.52844495E+00  -.38107084E+00  -.23221848E+00  -.87528095E-01
- Real Space Part
-   .47043595E+03   .47061811E+03   .47114518E+03   .47195957E+03   .47296738E+03
-   .47404142E+03   .47502541E+03   .47573899E+03   .47598368E+03   .47554935E+03
-   .47422109E+03   .47178640E+03   .46804221E+03   .46280172E+03   .45590085E+03
-   .44720395E+03   .43660875E+03   .42405037E+03   .40950423E+03   .39298784E+03
-   .37456135E+03   .35432699E+03   .33242725E+03   .30904200E+03   .28438464E+03
-   .25869730E+03   .23224536E+03   .20531141E+03   .17818879E+03   .15117498E+03
-   .12456500E+03   .98644898E+02   .73685748E+02   .49938027E+02   .27626718E+02
-   .69471588E+01  -.11938243E+02  -.28902388E+02  -.43854906E+02  -.56742633E+02
-  -.67549163E+02  -.76293525E+02  -.83028062E+02  -.87835614E+02  -.90826098E+02
-  -.92132623E+02  -.91907271E+02  -.90316654E+02  -.87537414E+02  -.83751758E+02
-  -.79143172E+02  -.73892400E+02  -.68173791E+02  -.62152082E+02  -.55979677E+02
-  -.49794451E+02  -.43718116E+02  -.37855127E+02  -.32292132E+02  -.27097928E+02
-  -.22323878E+02  -.18004740E+02  -.14159842E+02  -.10794541E+02  -.79018948E+01
-  -.54644709E+01  -.34562340E+01  -.18444414E+01  -.59149265E+00   .34331959E+00
-   .10021984E+01   .14274044E+01   .16600147E+01   .17388937E+01   .16998820E+01
-   .15752010E+01   .13930648E+01   .11774834E+01   .94823819E+00   .72100557E+00
-   .50760296E+00   .31633056E+00   .15238184E+00   .18296902E-01  -.85564833E-01
-  -.16055420E+00  -.20928196E+00  -.23520343E+00  -.24224903E+00  -.23450846E+00
-  -.21597247E+00  -.19033347E+00  -.16084311E+00  -.13022316E+00  -.10062372E+00
-  -.73622006E-01  -.50254001E-01  -.31070866E-01  -.16212387E-01  -.54900275E-02
- Non local Part
- 1 2 1.55770284366884382
- 2.65859659160385764 -0.504801881867953453E-01 -0.504801881867953453E-01 0.892956271679604986E-02
- Reciprocal Space Part
-   .00000000E+00   .55360975E+00   .11020032E+01   .16400357E+01   .21627048E+01
-   .26652186E+01   .31430596E+01   .35920450E+01   .40083810E+01   .43887098E+01
-   .47301505E+01   .50303314E+01   .52874138E+01   .55001078E+01   .56676786E+01
-   .57899444E+01   .58672657E+01   .59005262E+01   .58911063E+01   .58408488E+01
-   .57520191E+01   .56272596E+01   .54695387E+01   .52820975E+01   .50683934E+01
-   .48320418E+01   .45767578E+01   .43062991E+01   .40244089E+01   .37347632E+01
-   .34409202E+01   .31462743E+01   .28540152E+01   .25670915E+01   .22881811E+01
-   .20196669E+01   .17636193E+01   .15217840E+01   .12955770E+01   .10860853E+01
-   .89407229E+00   .71998985E+00   .56399389E+00   .42596477E+00   .30553088E+00
-   .20209532E+00   .11486458E+00   .42878783E-01  -.14957234E-01  -.59842780E-01
-  -.93050595E-01  -.11589722E+00  -.12971495E+00  -.13582584E+00  -.13551809E+00
-  -.13002523E+00  -.12050824E+00  -.10804072E+00  -.93597327E-01  -.78045331E-01
-  -.62139262E-01  -.46518532E-01  -.31707803E-01  -.18119864E-01  -.60607310E-02
-   .42633380E-02   .12737265E-01   .19327344E-01   .24070560E-01   .27063374E-01
-   .28450306E-01   .28412605E-01   .27157313E-01   .24906934E-01   .21889935E-01
-   .18332245E-01   .14449871E-01   .10442718E-01   .64896733E-02   .27449375E-02
-  -.66440255E-03  -.36396321E-02  -.61105795E-02  -.80348118E-02  -.93959825E-02
-  -.10201473E-01  -.10479476E-01  -.10275671E-01  -.96496464E-02  -.86712031E-02
-  -.74166865E-02  -.59654538E-02  -.43965915E-02  -.27859668E-02  -.12036827E-02
-   .28801366E-03   .16363396E-02   .27990903E-02   .37452630E-02   .44552150E-02
- Real Space Part
-   .00000000E+00   .64359942E+00   .12860893E+01   .19263130E+01   .25630221E+01
-   .31948350E+01   .38202017E+01   .44373750E+01   .50443910E+01   .56390587E+01
-   .62189597E+01   .67814592E+01   .73237268E+01   .78427678E+01   .83354645E+01
-   .87986250E+01   .92290406E+01   .96235469E+01   .99790905E+01   .10292796E+02
-   .10562036E+02   .10784491E+02   .10958218E+02   .11081699E+02   .11153897E+02
-   .11174283E+02   .11142876E+02   .11060254E+02   .10927558E+02   .10746490E+02
-   .10519290E+02   .10248709E+02   .99379673E+01   .95907014E+01   .92109083E+01
-   .88028781E+01   .83711229E+01   .79203026E+01   .74551481E+01   .69803858E+01
-   .65006629E+01   .60204776E+01   .55441132E+01   .50755794E+01   .46185613E+01
-   .41763765E+01   .37519415E+01   .33477477E+01   .29658468E+01   .26078460E+01
-   .22749116E+01   .19677819E+01   .16867871E+01   .14318761E+01   .12026495E+01
-   .99839626E+00   .81813432E+00   .66065330E+00   .52455802E+00   .40831211E+00
-   .31028032E+00   .22876897E+00   .16206345E+00   .10846228E+00   .66307278E-01
-   .34009364E-01   .10069850E-01  -.69027801E-02  -.18180606E-01  -.24908286E-01
-  -.28099078E-01  -.28634490E-01  -.27267117E-01  -.24626205E-01  -.21225416E-01
-  -.17472311E-01  -.13679034E-01  -.10073742E-01  -.68123372E-02  -.39901212E-02
-  -.16530358E-02   .19178102E-03   .15663369E-02   .25131785E-02   .30879320E-02
-   .33530317E-02   .33726336E-02   .32086679E-02   .29179506E-02   .25502513E-02
-   .21471944E-02   .17418610E-02   .13589554E-02   .10154019E-02   .72124547E-03
-   .48074009E-03   .29352474E-03   .15580136E-03   .61447592E-04   .30138377E-05
- Reciprocal Space Part
-   .00000000E+00  -.26932227E+01  -.52971472E+01  -.77244363E+01  -.98916316E+01
-  -.11720983E+02  -.13142152E+02  -.14093748E+02  -.14524661E+02  -.14395175E+02
-  -.13677819E+02  -.12357950E+02  -.10434056E+02  -.79177661E+01  -.48335806E+01
-  -.12183197E+01   .28796906E+01   .74016747E+01   .12279682E+02   .17438045E+02
-   .22794994E+02   .28264383E+02   .33757491E+02   .39184855E+02   .44458102E+02
-   .49491724E+02   .54204777E+02   .58522445E+02   .62377462E+02   .65711339E+02
-   .68475389E+02   .70631527E+02   .72152827E+02   .73023834E+02   .73240630E+02
-   .72810652E+02   .71752282E+02   .70094218E+02   .67874635E+02   .65140188E+02
-   .61944855E+02   .58348663E+02   .54416332E+02   .50215862E+02   .45817101E+02
-   .41290320E+02   .36704841E+02   .32127729E+02   .27622587E+02   .23248472E+02
-   .19058953E+02   .15101330E+02   .11416015E+02   .80360965E+01   .49870782E+01
-   .22867940E+01  -.54504994E-01  -.20339040E+01  -.36554301E+01  -.49295269E+01
-  -.58724172E+01  -.65053728E+01  -.68539157E+01  -.69469702E+01  -.68159914E+01
-  -.64940905E+01  -.60151778E+01  -.54131449E+01  -.47211011E+01  -.39706812E+01
-  -.31914370E+01  -.24103219E+01  -.16512754E+01  -.93491359E+00  -.27832313E+00
-   .30503924E+00   .80534852E+00   .12163201E+01   .15350341E+01   .17616860E+01
-   .18992752E+01   .19532440E+01   .19310803E+01   .18418981E+01   .16960073E+01
-   .15044873E+01   .12787746E+01   .10302757E+01   .77001425E+00   .50831954E+00
-   .25456290E+00   .16945576E-01  -.19765940E+00  -.38381089E+00  -.53754978E+00
-  -.65639825E+00  -.73931205E+00  -.78659086E+00  -.79975259E+00  -.78137851E+00
- Real Space Part
-   .00000000E+00   .32174412E+02   .64081200E+02   .95454901E+02   .12603438E+03
-   .15556504E+03   .18380101E+03   .21050740E+03   .23546257E+03   .25846040E+03
-   .27931254E+03   .29785062E+03   .31392841E+03   .32742382E+03   .33824076E+03
-   .34631080E+03   .35159451E+03   .35408254E+03   .35379625E+03   .35078802E+03
-   .34514103E+03   .33696853E+03   .32641275E+03   .31364309E+03   .29885400E+03
-   .28226227E+03   .26410388E+03   .24463049E+03   .22410561E+03   .20280043E+03
-   .18098955E+03   .15894661E+03   .13693992E+03   .11522816E+03   .94056367E+02
-   .73652166E+02   .54222369E+02   .35950069E+02   .18992243E+02   .34779240E+01
-  -.10493014E+02  -.22850445E+02  -.33553946E+02  -.42592145E+02  -.49981475E+02
-  -.55764394E+02  -.60007127E+02  -.62796996E+02  -.64239417E+02  -.64454665E+02
-  -.63574472E+02  -.61738574E+02  -.59091275E+02  -.55778129E+02  -.51942809E+02
-  -.47724232E+02  -.43254004E+02  -.38654223E+02  -.34035686E+02  -.29496509E+02
-  -.25121167E+02  -.20979967E+02  -.17128906E+02  -.13609921E+02  -.10451462E+02
-  -.76693710E+01  -.52679941E+01  -.32414933E+01  -.15752887E+01  -.24758462E+00
-   .76907715E+00   .15062828E+01   .19982770E+01   .22805946E+01   .23888267E+01
-   .23575419E+01   .22193827E+01   .20043426E+01   .17392288E+01   .14473034E+01
-   .11480951E+01   .85736431E+00   .58720519E+00   .34626103E+00   .14003133E+00
-  -.28753785E-01  -.15971487E+00  -.25438251E+00  -.31575466E+00  -.34786993E+00
-  -.35541133E+00  -.34335220E+00  -.31665261E+00  -.28001124E+00  -.23767485E+00
-  -.19330460E+00  -.14989599E+00  -.10974754E+00  -.74471444E-01  -.45038872E-01
- PAW radial sets
- 323 0.989218471734281124
-(5E20.12)                                
- augmentation charges (non sperical)
-  -.118612867153E+00  -.756362247412E-03  -.532145531503E-01  -.130926919871E-02  -.756362247412E-03
-  -.210856503823E-04  -.122603249007E-03   .363423839020E-05  -.532145531503E-01  -.122603249007E-03
-  -.179689875812E-01  -.555432069872E-03  -.130926919871E-02   .363423839020E-05  -.555432069872E-03
-   .498671741032E-04
- uccopancies in atom
-   .200000000162E+01   .000000000000E+00   .000000000000E+00   .000000000000E+00   .000000000000E+00
-   .000000000000E+00   .000000000000E+00   .000000000000E+00   .000000000000E+00   .000000000000E+00
-   .666666667141E+00   .000000000000E+00   .000000000000E+00   .000000000000E+00   .000000000000E+00
-   .000000000000E+00
- grid
-   .353278105438E-04   .364765828105E-04   .376627102856E-04   .388874076671E-04   .401519291522E-04
-   .414575697215E-04   .428056664648E-04   .441975999512E-04   .456347956421E-04   .471187253514E-04
-   .486509087530E-04   .502329149365E-04   .518663640144E-04   .535529287814E-04   .552943364272E-04
-   .570923703053E-04   .589488717596E-04   .608657420098E-04   .628449440985E-04   .648885049016E-04
-   .669985172040E-04   .691771418426E-04   .714266099194E-04   .737492250864E-04   .761473659044E-04
-   .786234882792E-04   .811801279764E-04   .838199032186E-04   .865455173661E-04   .893597616862E-04
-   .922655182109E-04   .952657626888E-04   .983635676325E-04   .101562105465E-03   .104864651768E-03
-   .108274588638E-03   .111795408149E-03   .115430715926E-03   .119184234844E-03   .123059808833E-03
-   .127061406819E-03   .131193126789E-03   .135459199986E-03   .139863995240E-03   .144412023447E-03
-   .149107942186E-03   .153956560487E-03   .158962843759E-03   .164131918874E-03   .169469079417E-03
-   .174979791106E-03   .180669697392E-03   .186544625235E-03   .192610591076E-03   .198873806993E-03
-   .205340687067E-03   .212017853948E-03   .218912145639E-03   .226030622496E-03   .233380574462E-03
-   .240969528530E-03   .248805256452E-03   .256895782699E-03   .265249392676E-03   .273874641209E-03
-   .282780361308E-03   .291975673207E-03   .301469993709E-03   .311273045829E-03   .321394868748E-03
-   .331845828098E-03   .342636626573E-03   .353778314896E-03   .365282303127E-03   .377160372357E-03
-   .389424686766E-03   .402087806084E-03   .415162698451E-03   .428662753701E-03   .442601797068E-03
-   .456994103352E-03   .471854411533E-03   .487197939863E-03   .503040401457E-03   .519398020380E-03
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-   .738536472381E-03   .762551836040E-03   .787348119413E-03   .812950716063E-03   .839385845286E-03
-   .866680578963E-03   .894862869287E-03   .923961577387E-03   .954006502881E-03   .985028414399E-03
-   .101705908109E-02   .105013130516E-02   .108427895544E-02   .111953700213E-02   .115594155253E-02
-   .119352988810E-02   .123234050257E-02   .127241314140E-02   .131378884247E-02   .135650997813E-02
-   .140062029854E-02   .144616497653E-02   .149319065382E-02   .154174548883E-02   .159187920594E-02
-   .164364314647E-02   .169709032120E-02   .175227546473E-02   .180925509145E-02   .186808755348E-02
-   .192883310041E-02   .199155394099E-02   .205631430683E-02   .212318051821E-02   .219222105197E-02
-   .226350661166E-02   .233711019991E-02   .241310719324E-02   .249157541920E-02   .257259523611E-02
-   .265624961535E-02   .274262422631E-02   .283180752413E-02   .292389084032E-02   .301896847624E-02
-   .311713779968E-02   .321849934462E-02   .332315691413E-02   .343121768671E-02   .354279232604E-02
-   .365799509430E-02   .377694396919E-02   .389976076474E-02   .402657125610E-02   .415750530828E-02
-   .429269700920E-02   .443228480697E-02   .457641165169E-02   .472522514185E-02   .487887767547E-02
-   .503752660617E-02   .520133440431E-02   .537046882339E-02   .554510307185E-02   .572541599040E-02
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-   .170189957261E+00   .175724110099E+00   .181438219781E+00   .187338138056E+00   .193429906954E+00
-   .199719764979E+00   .206214153496E+00   .212919723327E+00   .219843341560E+00   .226992098585E+00
-   .234373315355E+00   .241994550880E+00   .249863609972E+00   .257988551235E+00   .266377695319E+00
-   .275039633439E+00   .283983236179E+00   .293217662568E+00   .302752369466E+00   .312597121246E+00
-   .322761999795E+00   .333257414835E+00   .344094114590E+00   .355283196787E+00   .366836120023E+00
-   .378764715502E+00   .391081199148E+00   .403798184116E+00   .416928693710E+00   .430486174720E+00
-   .444484511190E+00   .458938038641E+00   .473861558747E+00   .489270354497E+00   .505180205845E+00
-   .521607405869E+00   .538568777456E+00   .556081690535E+00   .574164079857E+00   .592834463369E+00
-   .612111961177E+00   .632016315122E+00   .652567909002E+00   .673787789445E+00   .695697687463E+00
-   .718320040705E+00   .741678016440E+00   .765795535274E+00   .790697295655E+00   .816408799161E+00
-   .842956376619E+00   .870367215068E+00   .898669385601E+00   .927891872115E+00   .958064600989E+00
-   .989218471734E+00   .102138538864E+01   .105459829343E+01
- aepotential
-   .249296618412E+05   .247076583257E+05   .244443255599E+05   .241414371172E+05   .238011681064E+05
-   .234259054160E+05   .230182276498E+05   .225808680933E+05   .221166790321E+05   .216285959644E+05
-   .211196020425E+05   .205926935296E+05   .200508469868E+05   .194969885786E+05   .189339660140E+05
-   .183645234482E+05   .177912796436E+05   .172167095020E+05   .166431291099E+05   .160726841798E+05
-   .155073419145E+05   .149488860093E+05   .143989147023E+05   .138588415092E+05   .133298984061E+05
-   .128131411287E+05   .123094562646E+05   .118195698156E+05   .113440569063E+05   .108833523432E+05
-   .104377617399E+05   .100074729506E+05   .959256758265E+04   .919303239296E+04   .880877039590E+04
-   .843961154725E+04   .808532289425E+04   .774561810756E+04   .742016634235E+04   .710860038888E+04
-   .681052409519E+04   .652551907131E+04   .625315067621E+04   .599297332353E+04   .574453513086E+04
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-   .744246633582E+02   .705324162159E+02   .666918555610E+02   .629102856287E+02   .591944669183E+02
-   .555502477826E+02   .519821532120E+02   .484929672536E+02   .450833747318E+02   .417517679306E+02
-   .384943726247E+02   .353058986338E+02   .321809414460E+02   .291163276325E+02   .261144334538E+02
-   .231871492547E+02   .203596538297E+02   .176726025177E+02   .151810751243E+02   .129490421749E+02
-   .110393419236E+02   .950085943829E+01   .835601596774E+01   .759220035195E+01   .716026979128E+01
-   .698171586735E+01   .696337537316E+01   .701521042419E+01   .706481632887E+01   .706399956522E+01
-   .698712622280E+01   .682461424434E+01   .657568967629E+01   .624298209986E+01   .582958804938E+01
-   .533805380599E+01   .477041519949E+01   .412860165824E+01   .341481131402E+01   .263171136544E+01
-   .178246368857E+01   .870634878579E+00  -.999438728779E-01  -.112531868169E+01  -.220152969452E+01
-  -.332469269108E+01  -.449104609659E+01  -.569696875391E+01  -.693897492955E+01  -.821369210611E+01
-  -.951782536530E+01  -.108481102767E+02  -.122012545007E+02  -.135738669876E+02  -.149623728146E+02
-  -.163629115444E+02  -.177712178383E+02  -.191824854283E+02  -.205912200739E+02  -.219910944781E+02
-  -.233748284178E+02  -.247341312735E+02  -.260597521130E+02  -.273417019240E+02  -.285696929862E+02
-  -.297338408481E+02  -.308256300402E+02  -.318391145291E+02  -.327722934381E+02  -.336286096960E+02
-  -.344184453032E+02  -.351602594335E+02  -.358801411316E+02  -.366068307978E+02  -.373574862777E+02
-  -.381118849160E+02  -.387867273418E+02  -.392441857634E+02  -.393634904186E+02  -.391349287009E+02
-  -.386756216504E+02  -.381417407639E+02  -.376357898778E+02  -.371876084285E+02  -.367857308718E+02
-  -.364089017521E+02  -.360404072746E+02  -.356705440643E+02  -.352947736909E+02  -.349113812250E+02
-  -.345198086599E+02  -.341197549222E+02  -.337108274651E+02
- core charge-density
-   .566100405752E-04   .603274790726E-04   .642889041986E-04   .685103164325E-04   .730087642691E-04
-   .778024127357E-04   .829106163764E-04   .883539969928E-04   .941545264508E-04   .100335614880E-03
-   .106922204616E-03   .113940870262E-03   .121419925256E-03   .129389535376E-03   .137881839620E-03
-   .146931078955E-03   .156573733420E-03   .166848668143E-03   .177797288839E-03   .189463707397E-03
-   .201894918215E-03   .215140985966E-03   .229255245539E-03   .244294514933E-03   .260319321939E-03
-   .277394145493E-03   .295587672651E-03   .314973072166E-03   .335628285763E-03   .357636338214E-03
-   .381085667437E-03   .406070475885E-03   .432691104597E-03   .461054431344E-03   .491274294413E-03
-   .523471943665E-03   .557776520581E-03   .594325569167E-03   .633265579655E-03   .674752567074E-03
-   .718952686923E-03   .766042890258E-03   .816211620710E-03   .869659556058E-03   .926600397160E-03
-   .987261707239E-03   .105188580466E-02   .112073071253E-02   .119407116880E-02   .127219970037E-02
-   .135542776555E-02   .144408696885E-02   .153853035261E-02   .163913377046E-02   .174629734739E-02
-   .186044703187E-02   .198203624583E-02   .211154763822E-02   .224949494879E-02   .239642498860E-02
-   .255291974450E-02   .271959861504E-02   .289712078585E-02   .308618775280E-02   .328754600198E-02
-   .350198985578E-02   .373036449505E-02   .397356916791E-02   .423256059621E-02   .450835659128E-02
-   .480203989148E-02   .511476223442E-02   .544774867755E-02   .580230218169E-02   .617980847259E-02
-   .658174119662E-02   .700966738736E-02   .746525326090E-02   .795027035842E-02   .846660205552E-02
-   .901625045908E-02   .960134371288E-02   .102241437348E-01   .108870544090E-01   .115926302582E-01
-   .123435856218E-01   .131428043661E-01   .139933501568E-01   .148984773211E-01   .158616423311E-01
-   .168865159410E-01   .179769960102E-01   .191372210475E-01   .203715845116E-01   .216847499059E-01
-   .230816667048E-01   .245675871519E-01   .261480839698E-01   .278290690246E-01   .296168129868E-01
-   .315179660337E-01   .335395796374E-01   .356891294839E-01   .379745395704E-01   .404042075275E-01
-   .429870312127E-01   .457324366235E-01   .486504071769E-01   .517515144015E-01   .550469500898E-01
-   .585485599535E-01   .622688788272E-01   .662211674610E-01   .704194509412E-01   .748785587749E-01
-   .796141666712E-01   .846428400460E-01   .899820792747E-01   .956503667062E-01   .101667215451E+00
-   .108053219945E+00   .114830108271E+00   .122020796239E+00   .129649443177E+00   .137741509388E+00
-   .146323815234E+00   .155424601742E+00   .165073592657E+00   .175302057823E+00   .186142877738E+00
-   .197630609132E+00   .209801551371E+00   .222693813452E+00   .236347381338E+00   .250804185329E+00
-   .266108167138E+00   .282305346272E+00   .299443885308E+00   .317574153560E+00   .336748788604E+00
-   .357022755061E+00   .378453399961E+00   .401100503966E+00   .425026327615E+00   .450295651730E+00
-   .476975810973E+00   .505136719518E+00   .534850887654E+00   .566193428081E+00   .599242050517E+00
-   .634077043169E+00   .670781239474E+00   .709439968420E+00   .750140986642E+00   .792974390370E+00
-   .838032505174E+00   .885409751349E+00   .935202482669E+00   .987508796104E+00   .104242831002E+01
-   .110006190827E+01   .116051144745E+01   .122387942461E+01   .129026860260E+01   .135978159017E+01
-   .143252037390E+01   .150858579919E+01   .158807699749E+01   .167109075688E+01   .175772083353E+01
-   .184805720162E+01   .194218523933E+01   .204018484914E+01   .214212951079E+01   .224808526583E+01
-   .235810963304E+01   .247225045485E+01   .259054467535E+01   .271301705146E+01   .283967879975E+01
-   .297052618226E+01   .310553903613E+01   .324467925296E+01   .338788921520E+01   .353509019870E+01
-   .368618075190E+01   .384103506433E+01   .399950133877E+01   .416140018359E+01   .432652304404E+01
-   .449463069343E+01   .466545180749E+01   .483868164752E+01   .501398088047E+01   .519097456619E+01
-   .536925134438E+01   .554836285615E+01   .572782343649E+01   .590711011606E+01   .608566297177E+01
-   .626288586635E+01   .643814761788E+01   .661078363938E+01   .678009808823E+01   .694536656274E+01
-   .710583938103E+01   .726074547323E+01   .740929691345E+01   .755069411170E+01   .768413167876E+01
-   .780880496809E+01   .792391728912E+01   .802868777438E+01   .812235987040E+01   .820421040778E+01
-   .827355919064E+01   .832977902881E+01   .837230611874E+01   .840065066096E+01   .841440758325E+01
-   .841326722016E+01   .839702578152E+01   .836559542526E+01   .831901373419E+01   .825745238298E+01
-   .818122477058E+01   .809079238605E+01   .798676967249E+01   .786992715557E+01   .774119261011E+01
-   .760165005169E+01   .745253636003E+01   .729523536819E+01   .713126928576E+01   .696228736593E+01
-   .679005177517E+01   .661642067944E+01   .644332862203E+01   .627276433335E+01   .610674618159E+01
-   .594729554133E+01   .579640842184E+01   .565602576681E+01   .552800287068E+01   .541407839925E+01
-   .531584353892E+01   .523471177953E+01   .517188984282E+01   .512835026211E+01   .510480613184E+01
-   .510168858572E+01   .511912762968E+01   .515693703459E+01   .521460405617E+01   .529128475754E+01
-   .538580562001E+01   .549667189770E+01   .562208280769E+01   .575995323743E+01   .590794134470E+01
-   .606348131935E+01   .622382063669E+01   .638606123530E+01   .654720408632E+01   .670419655739E+01
-   .685398184633E+01   .699354961718E+01   .711998685544E+01   .723052788809E+01   .732260249172E+01
-   .739388103439E+01   .744231565540E+01   .746617657427E+01   .746408272963E+01   .743502607482E+01
-   .737838899666E+01   .729395447390E+01   .718190874815E+01   .704283644131E+01   .687770821462E+01
-   .668786122365E+01   .647497277612E+01   .624102774402E+01   .598828041327E+01   .571921157222E+01
-   .543648174187E+01   .514288153425E+01   .484128019032E+01   .453457339482E+01   .422563149315E+01
-   .391724924503E+01   .361209824281E+01   .331268309860E+01   .302130245731E+01   .274001582420E+01
-   .247061708263E+01   .221461541805E+01   .197322413413E+01   .174735759662E+01   .153763606876E+01
-   .134439807766E+01   .116771931577E+01   .100743688382E+01   .863177180939E+00   .734385201328E+00
-   .620352489207E+00   .520241312105E+00   .433105012361E+00   .357908953755E+00   .293558971531E+00
-   .238939332961E+00   .192952602310E+00   .154550561105E+00   .122752025089E+00   .966509456742E-01
-   .754197389551E-01   .583105713293E-01   .446553155083E-01   .338641489723E-01   .254227504169E-01
-   .188882123217E-01   .138839144900E-01   .100936595806E-01
- kinetic energy-density
-   .667223264162E+01   .673711797765E+01   .680446051695E+01   .687434851945E+01   .694687595542E+01
-   .702214224715E+01   .710025264340E+01   .718131851959E+01   .726545770326E+01   .735279480889E+01
-   .744346157547E+01   .753759722098E+01   .763534880551E+01   .773687160651E+01   .784232950769E+01
-   .795189540556E+01   .806575163262E+01   .818409040251E+01   .830711427710E+01   .843503666033E+01
-   .856808232008E+01   .870648794174E+01   .885050271727E+01   .900038897044E+01   .915642282528E+01
-   .931889491632E+01   .948811114834E+01   .966439350589E+01   .984808091773E+01   .100395301784E+02
-   .102391169326E+02   .104472367229E+02   .106643061077E+02   .108907638526E+02   .111270721976E+02
-   .113737182071E+02   .116312152061E+02   .119001043069E+02   .121809560330E+02   .124743720445E+02
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- core charge-density (pseudized)
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-   .170299369380E-03   .181554049396E-03   .193552467086E-03   .206343762684E-03   .219980322147E-03
-   .234517991391E-03   .250016304646E-03   .266538727861E-03   .284152918146E-03   .302931000300E-03
-   .322949861560E-03   .344291465748E-03   .367043188107E-03   .391298172159E-03   .417155710061E-03
-   .444721647953E-03   .474108817981E-03   .505437498701E-03   .538835905735E-03   .574440714657E-03
-   .612397618202E-03   .652861920041E-03   .695999167499E-03   .741985825749E-03   .791009996188E-03
-   .843272181843E-03   .898986102869E-03   .958379565380E-03   .102169538706E-02   .108919238320E-02
-   .116114641712E-02   .123785151900E-02   .131962107766E-02   .140678910979E-02   .149971161181E-02
-   .159876799938E-02   .170436264031E-02   .181692648675E-02   .193691881296E-02   .206482906523E-02
-   .220117883122E-02   .234652393586E-02   .250145667215E-02   .266660817484E-02   .284265094610E-02
-   .303030154244E-02   .323032343282E-02   .344353003832E-02   .367078796445E-02   .391302043770E-02
-   .417121095843E-02   .444640718317E-02   .473972504961E-02   .505235315859E-02   .538555742793E-02
-   .574068603353E-02   .611917465425E-02   .652255203717E-02   .695244590122E-02   .741058919732E-02
-   .789882674413E-02   .841912225897E-02   .897356580441E-02   .956438167099E-02   .101939367177E-01
-   .108647491919E-01   .115794980501E-01   .123410328028E-01   .131523839044E-01   .140167737110E-01
-   .149376280269E-01   .159185882611E-01   .169635242136E-01   .180765475092E-01   .192620256957E-01
-   .205245970213E-01   .218691859007E-01   .233010190786E-01   .248256424935E-01   .264489388384E-01
-   .281771458098E-01   .300168750282E-01   .319751316050E-01   .340593343169E-01   .362773363404E-01
-   .386374464823E-01   .411484508237E-01   .438196346781E-01   .466608047400E-01   .496823112734E-01
-   .528950701615E-01   .563105846042E-01   .599409662088E-01   .637989551781E-01   .678979392487E-01
-   .722519709725E-01   .768757828747E-01   .817847999463E-01   .869951488479E-01   .925236631107E-01
-   .983878835213E-01   .104606052760E+00   .111197103239E+00   .118180636950E+00   .125576895976E+00
-   .133406722150E+00   .141691504177E+00   .150453110317E+00   .159713804529E+00   .169496143740E+00
-   .179822853659E+00   .190716680317E+00   .202200214208E+00   .214295683694E+00   .227024713996E+00
-   .240408047883E+00   .254465223863E+00   .269214207487E+00   .284670971153E+00   .300849017672E+00
-   .317758842779E+00   .335407331821E+00   .353797086014E+00   .372925673998E+00   .392784804976E+00
-   .413359420546E+00   .434626703479E+00   .456555003242E+00   .479102680107E+00   .502216872244E+00
-   .525832193516E+00   .549869373680E+00   .574233857642E+00   .598814386387E+00   .623481589187E+00
-   .648086625061E+00   .672459920978E+00   .696410065316E+00   .719722927378E+00   .742161087375E+00
-   .763463676005E+00   .783346738217E+00   .801504251502E+00   .817609944243E+00   .831320073323E+00
-   .842277330789E+00   .850116055018E+00   .854468920152E+00   .854975265373E+00   .851291199249E+00
-   .843101569433E+00   .830133819226E+00   .812173654295E+00   .789082308931E+00   .760815025548E+00
-   .727440137991E+00   .689157874534E+00   .646317668655E+00   .599432387566E+00   .549187469489E+00
-   .496442519212E+00   .442222478719E+00   .387695112852E+00   .334131296257E+00   .282844548501E+00
-   .235106556397E+00   .192036190812E+00   .154460937507E+00   .122751901168E+00   .966509456742E-01
-   .754197389551E-01   .583105713293E-01   .446553155083E-01   .338641489723E-01   .254227504169E-01
-   .188882123217E-01   .138839144900E-01   .100936595806E-01
- pseudo wavefunction
-   .575355356415E-04   .594064477253E-04   .613381972024E-04   .633327623533E-04   .653921857868E-04
-   .675185765325E-04   .697141122004E-04   .719810412106E-04   .743216850967E-04   .767384408824E-04
-   .792337835369E-04   .818102685089E-04   .844705343442E-04   .872173053874E-04   .900533945721E-04
-   .929817063013E-04   .960052394220E-04   .991270902962E-04   .102350455972E-03   .105678637457E-03
-   .109115043101E-03   .112663192082E-03   .116326718016E-03   .120109372672E-03   .124015029819E-03
-   .128047689192E-03   .132211480586E-03   .136510668086E-03   .140949654437E-03   .145532985548E-03
-   .150265355149E-03   .155151609602E-03   .160196752857E-03   .165405951581E-03   .170784540448E-03
-   .176338027603E-03   .182072100302E-03   .187992630735E-03   .194105682043E-03   .200417514522E-03
-   .206934592042E-03   .213663588656E-03   .220611395446E-03   .227785127571E-03   .235192131559E-03
-   .242839992828E-03   .250736543454E-03   .258889870194E-03   .267308322765E-03   .276000522397E-03
-   .284975370659E-03   .294242058578E-03   .303810076049E-03   .313689221556E-03   .323889612204E-03
-   .334421694082E-03   .345296252956E-03   .356524425323E-03   .368117709807E-03   .380087978939E-03
-   .392447491317E-03   .405208904153E-03   .418385286245E-03   .431990131351E-03   .446037372013E-03
-   .460541393824E-03   .475517050162E-03   .490979677395E-03   .506945110594E-03   .523429699744E-03
-   .540450326492E-03   .558024421429E-03   .576169981949E-03   .594905590672E-03   .614250434477E-03
-   .634224324152E-03   .654847714681E-03   .676141726189E-03   .698128165574E-03   .720829548839E-03
-   .744269124145E-03   .768470895626E-03   .793459647966E-03   .819260971781E-03   .845901289826E-03
-   .873407884057E-03   .901808923562E-03   .931133493415E-03   .961411624459E-03   .992674324057E-03
-   .102495360785E-02   .105828253254E-02   .109269522973E-02   .112822694092E-02   .116491405352E-02
-   .120279413821E-02   .124190598731E-02   .128228965460E-02   .132398649626E-02   .136703921328E-02
-   .141149189515E-02   .145739006503E-02   .150478072633E-02   .155371241090E-02   .160423522870E-02
-   .165640091909E-02   .171026290385E-02   .176587634186E-02   .182329818560E-02   .188258723945E-02
-   .194380421993E-02   .200701181784E-02   .207227476250E-02   .213965988796E-02   .220923620153E-02
-   .228107495436E-02   .235524971443E-02   .243183644189E-02   .251091356682E-02   .259256206952E-02
-   .267686556349E-02   .276391038097E-02   .285378566135E-02   .294658344250E-02   .304239875489E-02
-   .314132971901E-02   .324347764574E-02   .334894714010E-02   .345784620834E-02   .357028636854E-02
-   .368638276474E-02   .380625428484E-02   .393002368229E-02   .405781770175E-02   .418976720886E-02
-   .432600732415E-02   .446667756139E-02   .461192197039E-02   .476188928438E-02   .491673307231E-02
-   .507661189599E-02   .524168947234E-02   .541213484098E-02   .558812253715E-02   .576983277035E-02
-   .595745160873E-02   .615117116944E-02   .635118981518E-02   .655771235717E-02   .677095026461E-02
-   .699112188101E-02   .721845264752E-02   .745317533347E-02   .769553027439E-02   .794576561781E-02
-   .820413757691E-02   .847091069247E-02   .874635810329E-02   .903076182533E-02   .932441303995E-02
-   .962761239135E-02   .994067029381E-02   .102639072487E-01   .105976541719E-01   .109422527315E-01
-   .112980556968E-01   .116654272983E-01   .120447435995E-01   .124363928804E-01   .128407760336E-01
-   .132583069731E-01   .136894130563E-01   .141345355194E-01   .145941299272E-01   .150686666365E-01
-   .155586312758E-01   .160645252384E-01   .165868661936E-01   .171261886122E-01   .176830443099E-01
-   .182580030081E-01   .188516529119E-01   .194646013071E-01   .200974751761E-01   .207509218330E-01
-   .214256095793E-01   .221222283799E-01   .228414905610E-01   .235841315294E-01   .243509105150E-01
-   .251426113360E-01   .259600431889E-01   .268040414619E-01   .276754685752E-01   .285752148462E-01
-   .295041993818E-01   .304633709985E-01   .314537091706E-01   .324762250072E-01   .335319622594E-01
-   .346219983579E-01   .357474454814E-01   .369094516585E-01   .381092019006E-01   .393479193701E-01
-   .406268665822E-01   .419473466418E-01   .433107045170E-01   .447183283484E-01   .461716507967E-01
-   .476721504277E-01   .492213531363E-01   .508208336098E-01   .524722168313E-01   .541771796234E-01
-   .559374522328E-01   .577548199563E-01   .596311248087E-01   .615682672319E-01   .635682078464E-01
-   .656329692451E-01   .677646378278E-01   .699653656785E-01   .722373724825E-01   .745829474842E-01
-   .770044514849E-01   .795043188773E-01   .820850597180E-01   .847492618341E-01   .874995929625E-01
-   .903388029198E-01   .932697257982E-01   .962952821862E-01   .994184814074E-01   .102642423774E+00
-   .105970302852E+00   .109405407722E+00   .112951125248E+00   .116610942317E+00   .120388448077E+00
-   .124287336121E+00   .128311406648E+00   .132464568547E+00   .136750841429E+00   .141174357551E+00
-   .145739363643E+00   .150450222608E+00   .155311415056E+00   .160327540676E+00   .165503319382E+00
-   .170843592230E+00   .176353322051E+00   .182037593757E+00   .187901614291E+00   .193950712150E+00
-   .200190336440E+00   .206626055381E+00   .213263554212E+00   .220108632399E+00   .227167200068E+00
-   .234445273557E+00   .241948969987E+00   .249684500724E+00   .257658163593E+00   .265876333703E+00
-   .274345452710E+00   .283072016330E+00   .292062559898E+00   .301323641738E+00   .310861824101E+00
-   .320683651362E+00   .330795625188E+00   .341204176307E+00   .351915632491E+00   .362936182330E+00
-   .374271834305E+00   .385928370642E+00   .397911295339E+00   .410225775742E+00   .422876576925E+00
-   .435867988095E+00   .449203740138E+00   .462886913351E+00   .476919834292E+00   .491303960597E+00
-   .506039752485E+00   .521126529587E+00   .536562311577E+00   .552343640997E+00   .568465386534E+00
-   .584920524858E+00   .601699899070E+00   .618791951638E+00   .636182429658E+00   .653854060191E+00
-   .671786193400E+00   .689954411226E+00   .708330099434E+00   .726879981021E+00   .745565609229E+00
-   .764342818847E+00   .783161135014E+00   .801963139531E+00   .820683795679E+00   .839249733873E+00
-   .857578502086E+00   .875577787069E+00   .893144614848E+00   .910164542018E+00   .926510852941E+00
-   .942043782108E+00   .956609785792E+00   .970040892551E+00   .982154168203E+00   .992751337468E+00
-   .100161861137E+01   .100852677652E+01   .101323160906E+01   .101547468225E+01   .101498464091E+01
-   .101147901878E+01   .100466111560E+01   .994375951175E+00
- ae wavefunction
-   .723210491674E-03   .746578583504E-03   .770700951777E-03   .795601892046E-03   .821306479222E-03
-   .847840592364E-03   .875230940233E-03   .903505087646E-03   .932691482648E-03   .962819484530E-03
-   .993919392710E-03   .102602247652E-02   .105916100589E-02   .109336828301E-02   .112867867496E-02
-   .116512764731E-02   .120275179882E-02   .124158889712E-02   .128167791559E-02   .132305907123E-02
-   .136577386383E-02   .140986511623E-02   .145537701585E-02   .150235515746E-02   .155084658728E-02
-   .160089984836E-02   .165256502735E-02   .170589380272E-02   .176093949434E-02   .181775711461E-02
-   .187640342107E-02   .193693697064E-02   .199941817539E-02   .206390935997E-02   .213047482081E-02
-   .219918088694E-02   .227009598271E-02   .234329069219E-02   .241883782559E-02   .249681248751E-02
-   .257729214718E-02   .266035671067E-02   .274608859525E-02   .283457280576E-02   .292589701322E-02
-   .302015163557E-02   .311742992074E-02   .321782803195E-02   .332144513543E-02   .342838349055E-02
-   .353874854230E-02   .365264901643E-02   .377019701702E-02   .389150812670E-02   .401670150953E-02
-   .414590001658E-02   .427923029422E-02   .441682289522E-02   .455881239271E-02   .470533749697E-02
-   .485654117518E-02   .501257077409E-02   .517357814572E-02   .533971977604E-02   .551115691676E-02
-   .568805572017E-02   .587058737709E-02   .605892825797E-02   .625326005711E-02   .645376994004E-02
-   .666065069409E-02   .687410088207E-02   .709432499912E-02   .732153363272E-02   .755594362580E-02
-   .779777824289E-02   .804726733939E-02   .830464753379E-02   .857016238277E-02   .884406255928E-02
-   .912660603329E-02   .941805825521E-02   .971869234197E-02   .100287892654E-01   .103486380429E-01
-   .106785359304E-01   .110187886169E-01   .113697104211E-01   .117316244893E-01   .121048629944E-01
-   .124897673360E-01   .128866883414E-01   .132959864662E-01   .137180319953E-01   .141532052432E-01
-   .146018967537E-01   .150645074973E-01   .155414490675E-01   .160331438739E-01   .165400253324E-01
-   .170625380517E-01   .176011380142E-01   .181562927528E-01   .187284815203E-01   .193181954522E-01
-   .199259377210E-01   .205522236809E-01   .211975810029E-01   .218625497970E-01   .225476827224E-01
-   .232535450820E-01   .239807149024E-01   .247297829946E-01   .255013529962E-01   .262960413920E-01
-   .271144775113E-01   .279573034995E-01   .288251742619E-01   .297187573775E-01   .306387329797E-01
-   .315857936016E-01   .325606439823E-01   .335640008323E-01   .345965925527E-01   .356591589072E-01
-   .367524506409E-01   .378772290432E-01   .390342654498E-01   .402243406813E-01   .414482444099E-01
-   .427067744540E-01   .440007359916E-01   .453309406888E-01   .466982057375E-01   .481033527959E-01
-   .495472068255E-01   .510305948176E-01   .525543444026E-01   .541192823346E-01   .557262328435E-01
-   .573760158460E-01   .590694450081E-01   .608073256492E-01   .625904524789E-01   .644196071575E-01
-   .662955556690E-01   .682190454976E-01   .701908025956E-01   .722115281337E-01   .742818950192E-01
-   .764025441734E-01   .785740805545E-01   .807970689137E-01   .830720292724E-01   .853994321068E-01
-   .877796932277E-01   .902131683422E-01   .927001472824E-01   .952408478902E-01   .978354095427E-01
-   .100483886305E+00   .103186239701E+00   .105942331082E+00   .108751913586E+00   .111614623678E+00
-   .114529972255E+00   .117497335304E+00   .120515944107E+00   .123584874990E+00   .126703038594E+00
-   .129869168677E+00   .133081810436E+00   .136339308348E+00   .139639793532E+00   .142981170636E+00
-   .146361104253E+00   .149777004875E+00   .153226014404E+00   .156704991228E+00   .160210494897E+00
-   .163738770409E+00   .167285732154E+00   .170846947546E+00   .174417620387E+00   .177992574025E+00
-   .181566234348E+00   .185132612703E+00   .188685288794E+00   .192217393669E+00   .195721592871E+00
-   .199190069873E+00   .202614509914E+00   .205986084362E+00   .209295435754E+00   .212532663666E+00
-   .215687311579E+00   .218748354949E+00   .221704190648E+00   .224542628026E+00   .227250881804E+00
-   .229815567059E+00   .232222696565E+00   .234457680772E+00   .236505330719E+00   .238349864209E+00
-   .239974915563E+00   .241363549317E+00   .242498278209E+00   .243361085852E+00   .243933454457E+00
-   .244196398032E+00   .244130501447E+00   .243715965781E+00   .242932660377E+00   .241760182005E+00
-   .240177921559E+00   .238165138679E+00   .235701044686E+00   .232764894196E+00   .229336085751E+00
-   .225394271769E+00   .220919478069E+00   .215892233186E+00   .210293707615E+00   .204105863065E+00
-   .197311611722E+00   .189894985412E+00   .181841314484E+00   .173137416083E+00   .163771791405E+00
-   .153734831344E+00   .143019029848E+00   .131619204110E+00   .119532720583E+00   .106759725623E+00
-   .933033793783E-01   .791700913290E-01   .643697556467E-01   .489159842705E-01   .328263352823E-01
-   .161225338086E-01  -.116931769311E-02  -.190185432589E-01  -.373897150652E-01  -.562424965567E-01
-  -.755315101746E-01  -.952062316141E-01  -.115210910670E+00  -.135484516518E+00  -.155960703517E+00
-  -.176567793429E+00  -.197228772403E+00  -.217861306439E+00  -.238377786432E+00  -.258685421094E+00
-  -.278686400098E+00  -.298278147634E+00  -.317353677390E+00  -.335802046575E+00  -.353508895291E+00
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-  -.437506929404E+00  -.446674028239E+00  -.454144807390E+00  -.459807173979E+00  -.463553709570E+00
-  -.465282646961E+00  -.464898846615E+00  -.462314763759E+00  -.457451397642E+00  -.450239215005E+00
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-  -.355155021405E+00  -.330524779042E+00  -.303426907952E+00  -.273910868147E+00  -.242041851308E+00
-  -.207900949827E+00  -.171585207413E+00  -.133207540559E+00  -.928965205479E-01  -.507960069887E-01
-  -.706462660247E-02   .381249046254E-01   .845866118155E-01   .132122232827E+00   .180522312943E+00
-   .229567399836E+00   .279029316983E+00   .328672503777E+00   .378255433412E+00   .427532158406E+00
-   .476254091096E+00   .524172202057E+00   .571039898221E+00   .616616860053E+00   .660673895312E+00
-   .702998092998E+00   .743396069181E+00   .781691750831E+00   .817716502043E+00   .851295258407E+00
-   .882238299672E+00   .910345743397E+00   .935421491735E+00   .957287299205E+00   .975791213531E+00
-   .990810701652E+00   .100225314042E+01   .101005569012E+01   .101418535258E+01   .101463927777E+01
-   .101144510801E+01   .100466111560E+01   .994375951175E+00
- pseudo wavefunction
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-   .162939810629E-05   .168238206754E-05   .173708893499E-05   .179357473326E-05   .185189730873E-05
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-   .224388936550E-05   .231685504901E-05   .239219339443E-05   .246998155480E-05   .255029919199E-05
-   .263322855826E-05   .271885458052E-05   .280726494727E-05   .289855019843E-05   .299280381807E-05
-   .309012233011E-05   .319060539717E-05   .329435592268E-05   .340148015621E-05   .351208780231E-05
-   .362629213282E-05   .374421010294E-05   .386596247091E-05   .399167392177E-05   .412147319496E-05
-   .425549321623E-05   .439387123372E-05   .453674895855E-05   .468427270993E-05   .483659356497E-05
-   .499386751345E-05   .515625561753E-05   .532392417672E-05   .549704489814E-05   .567579507240E-05
-   .586035775516E-05   .605092195456E-05   .624768282482E-05   .645084186605E-05   .666060713066E-05
-   .687719343636E-05   .710082258618E-05   .733172359563E-05   .757013292719E-05   .781629473250E-05
-   .807046110236E-05   .833289232491E-05   .860385715220E-05   .888363307535E-05   .917250660878E-05
-   .947077358361E-05   .977873945059E-05   .100967195929E-04   .104250396492E-04   .107640358469E-04
-   .111140553467E-04   .114754565982E-04   .118486097064E-04   .122338968115E-04   .126317124796E-04
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-   .889613540173E-04   .918541028731E-04   .948409114207E-04   .979248377142E-04   .101109039194E-03
-   .104396775914E-03   .107791413872E-03   .111296428448E-03   .114915407952E-03   .118652057294E-03
-   .122510201760E-03   .126493790920E-03   .130606902659E-03   .134853747338E-03   .139238672088E-03
-   .143766165242E-03   .148440860915E-03   .153267543723E-03   .158251153660E-03   .163396791131E-03
-   .168709722144E-03   .174195383669E-03   .179859389171E-03   .185707534319E-03   .191745802874E-03
-   .197980372773E-03   .204417622402E-03   .211064137063E-03   .217926715664E-03   .225012377598E-03
-   .232328369866E-03   .239882174401E-03   .247681515644E-03   .255734368344E-03   .264048965612E-03
-   .272633807228E-03   .281497668203E-03   .290649607612E-03   .300098977705E-03   .309855433294E-03
-   .319928941443E-03   .330329791440E-03   .341068605095E-03   .352156347338E-03   .363604337150E-03
-   .375424258823E-03   .387628173562E-03   .400228531432E-03   .413238183671E-03   .426670395356E-03
-   .440538858462E-03   .454857705282E-03   .469641522262E-03   .484905364210E-03   .500664768938E-03
-   .516935772296E-03   .533734923645E-03   .551079301749E-03   .568986531105E-03   .587474798722E-03
-   .606562871331E-03   .626270113061E-03   .646616503561E-03   .667622656585E-03   .689309839028E-03
-   .711699990427E-03   .734815742920E-03   .758680441650E-03   .783318165627E-03   .808753749025E-03
-   .835012802915E-03   .862121737409E-03   .890107784211E-03   .918999019551E-03   .948824387471E-03
-   .979613723446E-03   .101139777830E-02   .104420824237E-02   .107807776989E-02   .111304000356E-02
-   .114912959911E-02   .118638225005E-02   .122483471218E-02   .126452482815E-02   .130549155155E-02
-   .134777497086E-02   .139141633267E-02   .143645806444E-02   .148294379626E-02   .153091838171E-02
-   .158042791736E-02   .163151976091E-02   .168424254740E-02   .173864620342E-02   .179478195889E-02
-   .185270235589E-02   .191246125433E-02   .197411383369E-02   .203771659049E-02   .210332733071E-02
-   .217100515649E-02   .224081044631E-02   .231280482772E-02   .238705114166E-02   .246361339709E-02
-   .254255671485E-02   .262394725904E-02   .270785215452E-02   .279433938855E-02   .288347769449E-02
-   .297533641527E-02   .306998534399E-02   .316749453861E-02   .326793410732E-02   .337137396094E-02
-   .347788352781E-02   .358753142647E-02   .370038509052E-02   .381651033932E-02   .393597088755E-02
-   .405882778553E-02   .418513878099E-02   .431495759219E-02   .444833308019E-02   .458530830718E-02
-   .472591946529E-02   .487019465868E-02   .501815251889E-02   .516980063105E-02   .532513374505E-02
-   .548413174236E-02   .564675732521E-02   .581295338964E-02   .598264003926E-02   .615571118988E-02
-   .633203070846E-02   .651142802188E-02   .669369312193E-02   .687857088273E-02   .706575459498E-02
-   .725487860842E-02   .744550995872E-02   .763713883827E-02   .782916775105E-02   .802089917058E-02
-   .821152149574E-02   .840009307223E-02   .858552401783E-02   .876655555604E-02   .894173652625E-02
-   .910939669822E-02   .926761647490E-02   .941419252015E-02   .954659879722E-02   .966194244997E-02
-   .975691390319E-02   .982773050077E-02   .987007294359E-02   .987901373415E-02   .984893678510E-02
-   .977344730712E-02   .964527106365E-02   .945614207061E-02   .919667783672E-02   .885624129362E-02
-   .842278866608E-02   .788270269565E-02   .722061087326E-02   .641918867735E-02   .545894827979E-02
-   .431801379800E-02   .297188497289E-02   .139319217287E-02  -.448553094467E-03  -.258720639694E-02
-  -.506022962024E-02  -.790891121518E-02  -.111785546697E-01  -.149186192039E-01  -.191827929812E-01
-  -.240289749478E-01  -.295191367867E-01  -.357190314954E-01  -.426977099021E-01  -.505268012579E-01
-  -.592795092078E-01  -.690292703957E-01  -.798480203107E-01  -.918040104754E-01  -.104959123678E+00
-  -.119365640755E+00  -.135052537078E+00  -.152079847668E+00
- ae wavefunction
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-  -.629463877488E-05  -.649799364359E-05  -.670791014832E-05  -.692459949849E-05  -.714827966909E-05
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-  -.101399473930E-04  -.104672958085E-04  -.108051916432E-04  -.111539734135E-04  -.115139904123E-04
-  -.118856030458E-04  -.122691831813E-04  -.126651145043E-04  -.130737928877E-04  -.134956267708E-04
-  -.139310375502E-04  -.143804599824E-04  -.148443425977E-04  -.153231481275E-04  -.158173539430E-04
-  -.163274525071E-04  -.168539518402E-04  -.173973759985E-04  -.179582655672E-04  -.185371781670E-04
-  -.191346889761E-04  -.197513912662E-04  -.203878969549E-04  -.210448371726E-04  -.217228628465E-04
-  -.224226453000E-04  -.231448768698E-04  -.238902715395E-04  -.246595655907E-04  -.254535182727E-04
-  -.262729124892E-04  -.271185555052E-04  -.279912796712E-04  -.288919431682E-04  -.298214307715E-04
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-  -.851716921913E-03  -.873877109413E-03  -.896429619485E-03  -.919368663237E-03  -.942687315069E-03
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-  -.102754275349E-02  -.939611039582E-03  -.846818745856E-03  -.749140153709E-03  -.646557849671E-03
-  -.539062263517E-03  -.426651020394E-03  -.309328089220E-03  -.187102709897E-03  -.599880838515E-04
-   .720001825600E-04   .208845882540E-03   .350534246572E-03   .497054178393E-03   .648400632914E-03
-   .804577064382E-03   .965597871782E-03   .113149078626E-02   .130229918063E-02   .147808432308E-02
-   .165892762793E-02   .184493295336E-02   .203622894624E-02   .223297134696E-02   .243534507736E-02
-   .264356588222E-02   .285788129106E-02   .307857069465E-02   .330594435780E-02   .354034119917E-02
-   .378212515797E-02   .403167994363E-02   .428940193867E-02   .455569100166E-02   .483093890027E-02
-   .511551509457E-02   .540974958539E-02   .571391254373E-02   .602819044082E-02   .635265840777E-02
-   .668724856637E-02   .703171409088E-02   .738558878481E-02   .774814198662E-02   .811832865644E-02
-   .849473454000E-02   .887551635833E-02   .925833702998E-02   .964029599629E-02   .100178547868E-01
-   .103867580288E-01   .107419501671E-01   .110774882165E-01   .113864509092E-01   .116608446298E-01
-   .118915065430E-01   .120680053329E-01   .121785399967E-01   .122098372057E-01   .121470479066E-01
-   .119736441032E-01   .116713171792E-01   .112198796429E-01   .105971727185E-01   .977898257453E-02
-   .873896786599E-02   .744860013681E-02   .587711563848E-02   .399147119709E-02   .175628797936E-02
-  -.866239019038E-03  -.391647408054E-02  -.743746940754E-02  -.114749637066E-01  -.160771276901E-01
-  -.212941062664E-01  -.271776042085E-01  -.337807161610E-01  -.411579574899E-01  -.493653243621E-01
-  -.584602786172E-01  -.685016626504E-01  -.795495976261E-01  -.916654172796E-01  -.104911674326E+00
-  -.119352243438E+00  -.135052537078E+00  -.152079847668E+00
- pseudo wavefunction
-   .291401328267E-08   .310660741021E-08   .331193054558E-08   .353082397944E-08   .376418460535E-08
-   .401296859474E-08   .427819531469E-08   .456095150469E-08   .486239572944E-08   .518376312600E-08
-   .552637046455E-08   .589162154379E-08   .628101294285E-08   .669614015334E-08   .713870411675E-08
-   .761051819386E-08   .811351559483E-08   .864975730028E-08   .922144050602E-08   .983090762574E-08
-   .104806558889E-07   .111733475729E-07   .119118209112E-07   .126991017233E-07   .135384158119E-07
-   .144332021812E-07   .153871271269E-07   .164040992594E-07   .174882855184E-07   .186441282465E-07
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-   .273722917656E-07   .291813921584E-07   .311100603318E-07   .331661988066E-07   .353582324001E-07
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- ae wavefunction
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- pseudo wavefunction
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-   .106426813207E-05   .113460647955E-05   .120959342687E-05   .128953617969E-05   .137476224337E-05
-   .146562076397E-05   .156248395791E-05   .166574863599E-05   .177583782802E-05   .189320251473E-05
-   .201832347399E-05   .215171324889E-05   .229391824580E-05   .244552097081E-05   .260714241377E-05
-   .277944458969E-05   .296313324782E-05   .315896075937E-05   .336772919581E-05   .359029361017E-05
-   .382756553466E-05   .408051670906E-05   .435018305473E-05   .463766891071E-05   .494415154892E-05
-   .527088598687E-05   .561921011746E-05   .599055017661E-05   .638642657091E-05   .680846008894E-05
-   .725837852142E-05   .773802371682E-05   .824935910117E-05   .879447769232E-05   .937561064095E-05
-   .999513633285E-05   .106555900890E-04   .113596745027E-04   .121102704547E-04   .129104488515E-04
-   .137634831326E-04   .146728625977E-04   .156423066068E-04   .166757797093E-04   .177775077628E-04
-   .189519951060E-04   .202040428520E-04   .215387683771E-04   .229616260786E-04   .244784294863E-04
-   .260953748122E-04   .278190660317E-04   .296565415935E-04   .316153028623E-04   .337033444036E-04
-   .359291862279E-04   .383019081186E-04   .408311861731E-04   .435273316971E-04   .464013325996E-04
-   .494648974426E-04   .527305023115E-04   .562114406801E-04   .599218764523E-04   .638769003772E-04
-   .680925900398E-04   .725860736440E-04   .773755978153E-04   .824805996618E-04   .879217833433E-04
-   .937212014151E-04   .999023412187E-04   .106490216612E-03   .113511465340E-03   .120994452360E-03
-   .128969379448E-03   .137468401441E-03   .146525749442E-03   .156177861381E-03   .166463520291E-03
-   .177424000698E-03   .189103223502E-03   .201547919779E-03   .214807803882E-03   .228935756279E-03
-   .243988016516E-03   .260024386720E-03   .277108446041E-03   .295307776404E-03   .314694199941E-03
-   .335344028437E-03   .357338325072E-03   .380763178723E-03   .405709990999E-03   .432275776138E-03
-   .460563473773E-03   .490682274495E-03   .522747957989E-03   .556883243367E-03   .593218151151E-03
-   .631890376108E-03   .673045669922E-03   .716838232348E-03   .763431109165E-03   .812996594826E-03
-   .865716637226E-03   .921783241464E-03   .981398868826E-03   .104477682649E-02   .111214164262E-02
-   .118372942048E-02   .125978816423E-02   .134057806758E-02   .142637175521E-02   .151745446512E-02
-   .161412415806E-02   .171669153832E-02   .182547996737E-02   .194082524924E-02   .206307526326E-02
-   .219258941639E-02   .232973788293E-02   .247490059520E-02   .262846594337E-02   .279082913687E-02
-   .296239017320E-02   .314355135267E-02   .333471426917E-02   .353627619812E-02   .374862579194E-02
-   .397213798232E-02   .420716797543E-02   .445404421192E-02   .471306014793E-02   .498446469549E-02
-   .526845114184E-02   .556514434534E-02   .587458598281E-02   .619671759756E-02   .653136116924E-02
-   .687819689722E-02   .723673785601E-02   .760630114682E-02   .798597513191E-02   .837458229890E-02
-   .877063726069E-02   .917229935323E-02   .957731924895E-02   .998297895804E-02   .103860245445E-01
-   .107825908400E-01   .111681173956E-01   .115372548753E-01   .118837610617E-01   .122003856210E-01
-   .124787427655E-01   .127091709518E-01   .128805787801E-01   .129802763102E-01   .129937910905E-01
-   .129046683256E-01   .126942547801E-01   .123414662634E-01   .118225388591E-01   .111107644916E-01
-   .101762119689E-01   .898543534943E-02   .750117238625E-02   .568203694441E-02   .348221074715E-02
-   .851141640091E-03  -.226674211916E-02  -.593228912367E-02  -.102118375499E-01  -.151773626963E-01
-  -.209065329490E-01  -.274826407059E-01  -.349943660481E-01  -.435353202661E-01  -.532033034353E-01
-  -.640991948492E-01  -.763253771158E-01  -.899835741667E-01  -.105171960694E+00  -.121981376528E+00
-  -.140490455867E+00  -.160752140242E+00  -.182838197398E+00
- ae wavefunction
-   .329908017899E-08   .350070879538E-08   .371353032623E-08   .393823260492E-08   .417554304096E-08
-   .442623111551E-08   .469111103129E-08   .497104452448E-08   .526694384922E-08   .557977494597E-08
-   .591056080576E-08   .626038504303E-08   .663039569071E-08   .702180923184E-08   .743591488320E-08
-   .787407914718E-08   .833775064943E-08   .882846528060E-08   .934785166202E-08   .989763695626E-08
-   .104796530450E-07   .110958430977E-07   .117482685572E-07   .124391165681E-07   .131707078780E-07
-   .139455052412E-07   .147661223583E-07   .156353333861E-07   .165560830548E-07   .175314974331E-07
-   .185648953814E-07   .196598007399E-07   .208199552982E-07   .220493325979E-07   .233521526224E-07
-   .247328974311E-07   .261963278005E-07   .277475009372E-07   .293917893326E-07   .311349008342E-07
-   .329829000119E-07   .349422309040E-07   .370197412336E-07   .392227081895E-07   .415588658745E-07
-   .440364345292E-07   .466641516475E-07   .494513051048E-07   .524077684326E-07   .555440383768E-07
-   .588712748880E-07   .624013437039E-07   .661468616893E-07   .701212451142E-07   .743387610605E-07
-   .788145821596E-07   .835648448764E-07   .886067115712E-07   .939584365812E-07   .996394365846E-07
-   .105670365522E-06   .112073194371E-06   .118871296086E-06   .126089536039E-06   .133754368318E-06
-   .141893938246E-06   .150538191549E-06   .159718990577E-06   .169470238034E-06   .179828008724E-06
-   .190830689788E-06   .202519130018E-06   .214936798801E-06   .228129955327E-06   .242147828705E-06
-   .257042809702E-06   .272870654832E-06   .289690703594E-06   .307566109690E-06   .326564087128E-06
-   .346756172139E-06   .368218501929E-06   .391032111332E-06   .415283248495E-06   .441063710808E-06
-   .468471202359E-06   .497609714270E-06   .528589929370E-06   .561529652727E-06   .596554269675E-06
-   .633797233063E-06   .673400581564E-06   .715515490979E-06   .760302860615E-06   .807933936922E-06
-   .858590976703E-06   .912467952376E-06   .969771301889E-06   .103072072606E-05   .109555003626E-05
-   .116450805559E-05   .123785957678E-05   .131588638035E-05   .139888831671E-05   .148718445608E-05
-   .158111431043E-05   .168103913172E-05   .178734329115E-05   .190043574433E-05   .202075158739E-05
-   .214875370975E-05   .228493454907E-05   .242981795469E-05   .258396116581E-05   .274795691142E-05
-   .292243563898E-05   .310806787948E-05   .330556675685E-05   .351569065019E-05   .373924601751E-05
-   .397709039049E-05   .423013554987E-05   .449935089198E-05   .478576699710E-05   .509047941113E-05
-   .541465265242E-05   .575952445644E-05   .612641027142E-05   .651670801861E-05   .693190313178E-05
-   .737357389105E-05   .784339706665E-05   .834315388946E-05   .887473636521E-05   .944015395058E-05
-   .100415406097E-04   .106811622710E-04   .113614247036E-04   .120848818358E-04   .128542445362E-04
-   .136723898809E-04   .145423709291E-04   .154674270325E-04   .164509947032E-04   .174967190638E-04
-   .186084659092E-04   .197903344043E-04   .210466704466E-04   .223820807216E-04   .238014474792E-04
-   .253099440608E-04   .269130512058E-04   .286165741680E-04   .304266606703E-04   .323498197291E-04
-   .343929413762E-04   .365633173085E-04   .388686624936E-04   .413171377592E-04   .439173733939E-04
-   .466784937828E-04   .496101431055E-04   .527225121145E-04   .560263660175E-04   .595330734786E-04
-   .632546367534E-04   .672037229692E-04   .713936965562E-04   .758386528320E-04   .805534527382E-04
-   .855537587174E-04   .908560717189E-04   .964777693090E-04   .102437144857E-03   .108753447759E-03
-   .115446924650E-03   .122538861549E-03   .130051626865E-03   .138008715186E-03   .146434791756E-03
-   .155355737528E-03   .164798694679E-03   .174792112435E-03   .185365793069E-03   .196550937879E-03
-   .208380192963E-03   .220887694586E-03   .234109113894E-03   .248081700728E-03   .262844326268E-03
-   .278437524200E-03   .294903530092E-03   .312286318645E-03   .330631638438E-03   .349987043795E-03
-   .370401923370E-03   .391927525004E-03   .414616976437E-03   .438525301396E-03   .463709430588E-03
-   .490228207127E-03   .518142385893E-03   .547514626344E-03   .578409478292E-03   .610893360173E-03
-   .645034529359E-03   .680903044093E-03   .718570716657E-03   .758111057440E-03   .799599209646E-03
-   .843111874437E-03   .888727226421E-03   .936524819495E-03   .986585483195E-03   .103899120984E-02
-   .109382503292E-02   .115117089748E-02   .121111352320E-02   .127373826159E-02   .133913094834E-02
-   .140737775294E-02   .147856502718E-02   .155277915525E-02   .163010640797E-02   .171063280434E-02
-   .179444398399E-02   .188162509437E-02   .197226069717E-02   .206643469870E-02   .216423030948E-02
-   .226573003870E-02   .237101572979E-02   .248016864360E-02   .259326959640E-02   .271039916068E-02
-   .283163793710E-02   .295706690745E-02   .308676787920E-02   .322082403378E-02   .335932059220E-02
-   .350234561239E-02   .364999093291E-02   .380235327479E-02   .395953550720E-02   .412164806889E-02
-   .428881051644E-02   .446115314045E-02   .463881855679E-02   .482196315214E-02   .501075825528E-02
-   .520539093344E-02   .540606438254E-02   .561299798267E-02   .582642719909E-02   .604660358714E-02
-   .627379516452E-02   .650828731395E-02   .675038417942E-02   .700041028844E-02   .725871197647E-02
-   .752565817955E-02   .780164027316E-02   .808707077981E-02   .838238086423E-02   .868801655628E-02
-   .900443360736E-02   .933209082854E-02   .967144170169E-02   .100229240120E-01   .103869472209E-01
-   .107638772809E-01   .111540185848E-01   .115575927342E-01   .119747138083E-01   .124053598104E-01
-   .128493399678E-01   .133062575600E-01   .137754679559E-01   .142560315452E-01   .147466612667E-01
-   .152456644480E-01   .157508787005E-01   .162596016357E-01   .167685142012E-01   .172735974648E-01
-   .177700427009E-01   .182521546525E-01   .187132478523E-01   .191455358726E-01   .195400133505E-01
-   .198863305955E-01   .201726605474E-01   .203855578566E-01   .205098099183E-01   .205282799298E-01
-   .204217424344E-01   .201687124905E-01   .197452704861E-01   .191248856466E-01   .182782422416E-01
-   .171730730409E-01   .157740040676E-01   .140424119477E-01   .119362882257E-01   .941009223694E-02
-   .641455956391E-02   .289643672970E-02  -.120182972349E-02  -.594230845433E-02  -.113915061558E-01
-  -.176199584845E-01  -.247017208792E-01  -.327140327375E-01  -.417371826148E-01  -.518544026197E-01
-  -.631516436073E-01  -.757171941354E-01  -.896411710603E-01  -.105014918512E+00  -.121930338317E+00
-  -.140479159189E+00  -.160752140242E+00  -.182838197398E+00
- End of Dataset
diff --git a/notebooks/Si-static/INCAR b/notebooks/Si-static/INCAR
new file mode 100644
index 0000000..41617cb
--- /dev/null
+++ b/notebooks/Si-static/INCAR
@@ -0,0 +1,23 @@
+ALGO = All
+EDIFF = 1e-05
+ENAUG = 1360.0
+ENCUT = 680.0
+ICHARG = 1
+ISMEAR = -5
+ISPIN = 2
+KPOINT_BSE = -1 0 0 0
+LAECHG = True
+LASPH = True
+LCHARG = True
+LELF = True
+LMIXTAU = -1
+LORBIT = 11
+LREAL = False
+LVTOT = True
+LWAVE = False
+MAGMOM = 1*0.6
+METAGGA = R2scan
+NELM = 60
+NSW = 0
+PREC = Accurate
+SIGMA = 0.5
diff --git a/notebooks/Si-static/KPOINTS b/notebooks/Si-static/KPOINTS
new file mode 100644
index 0000000..0594750
--- /dev/null
+++ b/notebooks/Si-static/KPOINTS
@@ -0,0 +1,4 @@
+pymatgen with grid density = 1503 / number of atoms
+0
+Gamma
+11 11 11
diff --git a/notebooks/Si-static/POSCAR b/notebooks/Si-static/POSCAR
new file mode 100644
index 0000000..8e43408
--- /dev/null
+++ b/notebooks/Si-static/POSCAR
@@ -0,0 +1,9 @@
+Al1
+1.0
+  -0.0000000000000001    2.0205550799999998    2.0205550799999998
+   2.0205550799999998    0.0000000000000000    2.0205550799999998
+   2.0205550799999998    2.0205550799999998    0.0000000000000002
+Al
+1
+direct
+   0.0000000000000000    0.0000000000000000    0.0000000000000000 Al
diff --git a/notebooks/Si-static/POTCAR b/notebooks/Si-static/POTCAR
new file mode 100644
index 0000000..c8d9ecb
--- /dev/null
+++ b/notebooks/Si-static/POTCAR
@@ -0,0 +1,1768 @@
+ PAW_PBE Al 04Jan2001
+ 3.00000000000000000
+ parameters from PSCTR are:
+   VRHFIN =Al: s2p1
+   LEXCH  = PE
+   EATOM  =    53.5387 eV,    3.9350 Ry
+
+   TITEL  = PAW_PBE Al 04Jan2001
+   LULTRA =        F    use ultrasoft PP ?
+   IUNSCR =        1    unscreen: 0-lin 1-nonlin 2-no
+   RPACOR =    1.500    partial core radius
+   POMASS =   26.982; ZVAL   =    3.000    mass and valenz
+   RCORE  =    1.900    outmost cutoff radius
+   RWIGS  =    2.650; RWIGS  =    1.402    wigner-seitz radius (au A)
+   ENMAX  =  240.300; ENMIN  =  180.225 eV
+   ICORE  =        2    local potential
+   LCOR   =        T    correct aug charges
+   LPAW   =        T    paw PP
+   EAUG   =  291.052
+   DEXC   =    -.041
+   RMAX   =    2.974    core radius for proj-oper
+   RAUG   =    1.300    factor for augmentation sphere
+   RDEP   =    1.966    radius for radial grids
+   QCUT   =   -4.203; QGAM   =    8.405    optimization parameters
+ 
+   Description
+     l     E      TYP  RCUT    TYP  RCUT
+     0   .000     23  1.900
+     0   .000     23  1.900
+     1   .000     23  1.900
+     1  1.000     23  1.900
+     2   .000      7  1.900
+   Error from kinetic energy argument (eV)
+   NDATA  =      100
+   STEP   =   20.000   1.050
+  2.17      1.95      1.85      1.68      1.61      1.48      1.37      1.32
+  1.24      1.17      1.14      1.08      1.03      .977      .931      .886
+  .843      .801      .758      .695      .653      .611      .549      .509
+  .469      .413      .359      .325      .278      .235      .197      .163
+  .133      .107      .858E-01  .676E-01  .483E-01  .370E-01  .256E-01  .193E-01
+  .132E-01  .922E-02  .676E-02  .535E-02  .461E-02  .426E-02  .410E-02  .397E-02
+  .383E-02  .358E-02  .322E-02  .288E-02  .243E-02  .199E-02  .152E-02  .120E-02
+  .964E-03  .771E-03  .660E-03  .604E-03  .576E-03  .555E-03  .527E-03  .479E-03
+  .425E-03  .355E-03  .288E-03  .231E-03  .185E-03  .161E-03  .147E-03  .140E-03
+  .133E-03  .123E-03  .108E-03  .913E-04  .740E-04  .607E-04  .519E-04  .482E-04
+  .459E-04  .430E-04  .384E-04  .320E-04  .261E-04  .219E-04  .198E-04  .188E-04
+  .176E-04  .155E-04  .128E-04  .107E-04  .933E-05  .881E-05  .825E-05  .723E-05
+  .594E-05  .506E-05  .462E-05  .439E-05
+END of PSCTR-controll parameters
+ local part
+ 98.2657514061040160
+  -.11196040E+01  -.11177563E+01  -.11049391E+01  -.10835857E+01  -.10537102E+01
+  -.10153337E+01  -.96848653E+00  -.91320931E+00  -.84955472E+00  -.77758869E+00
+  -.69739125E+00  -.60905702E+00  -.51269522E+00  -.40842942E+00  -.29639696E+00
+  -.17674840E+00  -.49646910E-01   .84732128E-01   .22620132E+00   .37456122E+00
+   .52960001E+00   .69109312E+00   .85880261E+00   .10324767E+01   .12118494E+01
+   .13966402E+01   .15865537E+01   .17812803E+01   .19804960E+01   .21838631E+01
+   .23910305E+01   .26016344E+01   .28152987E+01   .30316358E+01   .32502469E+01
+   .34707226E+01   .36926434E+01   .39155809E+01   .41390977E+01   .43627492E+01
+   .45860841E+01   .48086459E+01   .50299739E+01   .52496049E+01   .54670742E+01
+   .56819175E+01   .58936719E+01   .61018779E+01   .63060802E+01   .65058297E+01
+   .67006847E+01   .68902126E+01   .70739913E+01   .72516109E+01   .74226751E+01
+   .75868032E+01   .77436311E+01   .78928134E+01   .80340244E+01   .81669598E+01
+   .82913377E+01   .84069000E+01   .85134133E+01   .86106704E+01   .86984902E+01
+   .87767197E+01   .88452338E+01   .89039366E+01   .89527612E+01   .89916710E+01
+   .90206591E+01   .90397490E+01   .90489941E+01   .90484779E+01   .90383136E+01
+   .90186433E+01   .89896376E+01   .89514949E+01   .89044406E+01   .88487257E+01
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+ 5
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+  -.34034825E-08  -.38981382E-08  -.43496976E-08  -.47543168E-08  -.51086485E-08
+ 19.8421228800786942 T
+ Non local Part
+ 0 2 1.57396957515338021
+ 5.95455379507119975 -0.947622792329037567E-01 -0.947622792329037567E-01 0.296195088768378464E-02
+ Reciprocal Space Part
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+   .12732216E+02   .12443151E+02   .12108486E+02   .11731521E+02   .11315936E+02
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+   .55798975E-02   .52324585E-02   .46964705E-02   .40095377E-02   .32119402E-02
+ Real Space Part
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+  -.33035122E-04  -.16552831E-03  -.23464831E-03  -.25366604E-03  -.23619783E-03
+ Reciprocal Space Part
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+  -.74847025E+00  -.61481243E+00  -.46932237E+00  -.31847831E+00  -.16838293E+00
+ Real Space Part
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+   .67765642E+03   .67653890E+03   .67472952E+03   .67201476E+03   .66817044E+03
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+  -.51387033E-01  -.29662701E-01  -.13337670E-01  -.20265672E-02   .49177022E-02
+ Non local Part
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+ 2.08596921736620722 -0.219845133596054454 -0.219845133596054454 0.318470468308045818E-01
+ Reciprocal Space Part
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+ Real Space Part
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+   .79260455E-03   .47461243E-03   .24398580E-03   .88606522E-04  -.54803893E-05
+ Reciprocal Space Part
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+(5E20.12)                                
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+ core charge-density (pseudized)
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+ pseudo wavefunction
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+ ae wavefunction
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+ pseudo wavefunction
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+ ae wavefunction
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+ pseudo wavefunction
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+ ae wavefunction
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+ pseudo wavefunction
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+   .341870011358E-01   .315333857728E-01   .284339121815E-01   .248303777137E-01   .206585994077E-01
+   .158481387571E-01   .103220726566E-01   .399681145283E-02  -.321804879480E-02  -.114198726910E-01
+  -.207131766228E-01  -.312098754437E-01  -.430294443432E-01  -.562985886144E-01  -.711498810414E-01
+  -.877192443605E-01  -.106142997440E+00  -.126555453149E+00  -.149087269809E+00  -.173863896068E+00
+  -.201003403349E+00  -.230613449456E+00  -.262787450420E+00
+ End of Dataset
diff --git a/notebooks/Si.cif b/notebooks/Si.cif
deleted file mode 100644
index 11da42a..0000000
--- a/notebooks/Si.cif
+++ /dev/null
@@ -1,218 +0,0 @@
-# generated using pymatgen
-data_Si
-_symmetry_space_group_name_H-M   Fd-3m
-_cell_length_a   5.44370237
-_cell_length_b   5.44370237
-_cell_length_c   5.44370237
-_cell_angle_alpha   90.00000000
-_cell_angle_beta   90.00000000
-_cell_angle_gamma   90.00000000
-_symmetry_Int_Tables_number   227
-_chemical_formula_structural   Si
-_chemical_formula_sum   Si8
-_cell_volume   161.31810739
-_cell_formula_units_Z   8
-loop_
- _symmetry_equiv_pos_site_id
- _symmetry_equiv_pos_as_xyz
-  1  'x, y, z'
-  2  '-y+1/4, x+1/4, z+1/4'
-  3  '-x, -y+1/2, z+1/2'
-  4  'y+3/4, -x+1/4, z+3/4'
-  5  'x, -y, -z'
-  6  '-y+1/4, -x+3/4, -z+3/4'
-  7  '-x, y+1/2, -z+1/2'
-  8  'y+3/4, x+3/4, -z+1/4'
-  9  'z, x, y'
-  10  'z+1/4, -y+1/4, x+1/4'
-  11  'z+1/2, -x, -y+1/2'
-  12  'z+3/4, y+3/4, -x+1/4'
-  13  '-z, x, -y'
-  14  '-z+3/4, -y+1/4, -x+3/4'
-  15  '-z+1/2, -x, y+1/2'
-  16  '-z+1/4, y+3/4, x+3/4'
-  17  'y, z, x'
-  18  'x+1/4, z+1/4, -y+1/4'
-  19  '-y+1/2, z+1/2, -x'
-  20  '-x+1/4, z+3/4, y+3/4'
-  21  '-y, -z, x'
-  22  '-x+3/4, -z+3/4, -y+1/4'
-  23  'y+1/2, -z+1/2, -x'
-  24  'x+3/4, -z+1/4, y+3/4'
-  25  '-x+1/4, -y+1/4, -z+1/4'
-  26  'y, -x, -z'
-  27  'x+1/4, y+3/4, -z+3/4'
-  28  '-y+1/2, x, -z+1/2'
-  29  '-x+1/4, y+1/4, z+1/4'
-  30  'y, x+1/2, z+1/2'
-  31  'x+1/4, -y+3/4, z+3/4'
-  32  '-y+1/2, -x+1/2, z'
-  33  '-z+1/4, -x+1/4, -y+1/4'
-  34  '-z, y, -x'
-  35  '-z+3/4, x+1/4, y+3/4'
-  36  '-z+1/2, -y+1/2, x'
-  37  'z+1/4, -x+1/4, y+1/4'
-  38  'z+1/2, y, x+1/2'
-  39  'z+3/4, x+1/4, -y+3/4'
-  40  'z, -y+1/2, -x+1/2'
-  41  '-y+1/4, -z+1/4, -x+1/4'
-  42  '-x, -z, y'
-  43  'y+3/4, -z+3/4, x+1/4'
-  44  'x, -z+1/2, -y+1/2'
-  45  'y+1/4, z+1/4, -x+1/4'
-  46  'x+1/2, z+1/2, y'
-  47  '-y+3/4, z+3/4, x+1/4'
-  48  '-x+1/2, z, -y+1/2'
-  49  'x+1/2, y+1/2, z'
-  50  '-y+3/4, x+3/4, z+1/4'
-  51  '-x+1/2, -y, z+1/2'
-  52  'y+1/4, -x+3/4, z+3/4'
-  53  'x+1/2, -y+1/2, -z'
-  54  '-y+3/4, -x+1/4, -z+3/4'
-  55  '-x+1/2, y, -z+1/2'
-  56  'y+1/4, x+1/4, -z+1/4'
-  57  'z+1/2, x+1/2, y'
-  58  'z+3/4, -y+3/4, x+1/4'
-  59  'z, -x+1/2, -y+1/2'
-  60  'z+1/4, y+1/4, -x+1/4'
-  61  '-z+1/2, x+1/2, -y'
-  62  '-z+1/4, -y+3/4, -x+3/4'
-  63  '-z, -x+1/2, y+1/2'
-  64  '-z+3/4, y+1/4, x+3/4'
-  65  'y+1/2, z+1/2, x'
-  66  'x+3/4, z+3/4, -y+1/4'
-  67  '-y, z, -x'
-  68  '-x+3/4, z+1/4, y+3/4'
-  69  '-y+1/2, -z+1/2, x'
-  70  '-x+1/4, -z+1/4, -y+1/4'
-  71  'y, -z, -x'
-  72  'x+1/4, -z+3/4, y+3/4'
-  73  '-x+3/4, -y+3/4, -z+1/4'
-  74  'y+1/2, -x+1/2, -z'
-  75  'x+3/4, y+1/4, -z+3/4'
-  76  '-y, x+1/2, -z+1/2'
-  77  '-x+3/4, y+3/4, z+1/4'
-  78  'y+1/2, x, z+1/2'
-  79  'x+3/4, -y+1/4, z+3/4'
-  80  '-y, -x, z'
-  81  '-z+3/4, -x+3/4, -y+1/4'
-  82  '-z+1/2, y+1/2, -x'
-  83  '-z+1/4, x+3/4, y+3/4'
-  84  '-z, -y, x'
-  85  'z+3/4, -x+3/4, y+1/4'
-  86  'z, y+1/2, x+1/2'
-  87  'z+1/4, x+3/4, -y+3/4'
-  88  'z+1/2, -y, -x+1/2'
-  89  '-y+3/4, -z+3/4, -x+1/4'
-  90  '-x+1/2, -z+1/2, y'
-  91  'y+1/4, -z+1/4, x+1/4'
-  92  'x+1/2, -z, -y+1/2'
-  93  'y+3/4, z+3/4, -x+1/4'
-  94  'x, z, y'
-  95  '-y+1/4, z+1/4, x+1/4'
-  96  '-x, z+1/2, -y+1/2'
-  97  'x+1/2, y, z+1/2'
-  98  '-y+3/4, x+1/4, z+3/4'
-  99  '-x+1/2, -y+1/2, z'
-  100  'y+1/4, -x+1/4, z+1/4'
-  101  'x+1/2, -y, -z+1/2'
-  102  '-y+3/4, -x+3/4, -z+1/4'
-  103  '-x+1/2, y+1/2, -z'
-  104  'y+1/4, x+3/4, -z+3/4'
-  105  'z+1/2, x, y+1/2'
-  106  'z+3/4, -y+1/4, x+3/4'
-  107  'z, -x, -y'
-  108  'z+1/4, y+3/4, -x+3/4'
-  109  '-z+1/2, x, -y+1/2'
-  110  '-z+1/4, -y+1/4, -x+1/4'
-  111  '-z, -x, y'
-  112  '-z+3/4, y+3/4, x+1/4'
-  113  'y+1/2, z, x+1/2'
-  114  'x+3/4, z+1/4, -y+3/4'
-  115  '-y, z+1/2, -x+1/2'
-  116  '-x+3/4, z+3/4, y+1/4'
-  117  '-y+1/2, -z, x+1/2'
-  118  '-x+1/4, -z+3/4, -y+3/4'
-  119  'y, -z+1/2, -x+1/2'
-  120  'x+1/4, -z+1/4, y+1/4'
-  121  '-x+3/4, -y+1/4, -z+3/4'
-  122  'y+1/2, -x, -z+1/2'
-  123  'x+3/4, y+3/4, -z+1/4'
-  124  '-y, x, -z'
-  125  '-x+3/4, y+1/4, z+3/4'
-  126  'y+1/2, x+1/2, z'
-  127  'x+3/4, -y+3/4, z+1/4'
-  128  '-y, -x+1/2, z+1/2'
-  129  '-z+3/4, -x+1/4, -y+3/4'
-  130  '-z+1/2, y, -x+1/2'
-  131  '-z+1/4, x+1/4, y+1/4'
-  132  '-z, -y+1/2, x+1/2'
-  133  'z+3/4, -x+1/4, y+3/4'
-  134  'z, y, x'
-  135  'z+1/4, x+1/4, -y+1/4'
-  136  'z+1/2, -y+1/2, -x'
-  137  '-y+3/4, -z+1/4, -x+3/4'
-  138  '-x+1/2, -z, y+1/2'
-  139  'y+1/4, -z+3/4, x+3/4'
-  140  'x+1/2, -z+1/2, -y'
-  141  'y+3/4, z+1/4, -x+3/4'
-  142  'x, z+1/2, y+1/2'
-  143  '-y+1/4, z+3/4, x+3/4'
-  144  '-x, z, -y'
-  145  'x, y+1/2, z+1/2'
-  146  '-y+1/4, x+3/4, z+3/4'
-  147  '-x, -y, z'
-  148  'y+3/4, -x+3/4, z+1/4'
-  149  'x, -y+1/2, -z+1/2'
-  150  '-y+1/4, -x+1/4, -z+1/4'
-  151  '-x, y, -z'
-  152  'y+3/4, x+1/4, -z+3/4'
-  153  'z, x+1/2, y+1/2'
-  154  'z+1/4, -y+3/4, x+3/4'
-  155  'z+1/2, -x+1/2, -y'
-  156  'z+3/4, y+1/4, -x+3/4'
-  157  '-z, x+1/2, -y+1/2'
-  158  '-z+3/4, -y+3/4, -x+1/4'
-  159  '-z+1/2, -x+1/2, y'
-  160  '-z+1/4, y+1/4, x+1/4'
-  161  'y, z+1/2, x+1/2'
-  162  'x+1/4, z+3/4, -y+3/4'
-  163  '-y+1/2, z, -x+1/2'
-  164  '-x+1/4, z+1/4, y+1/4'
-  165  '-y, -z+1/2, x+1/2'
-  166  '-x+3/4, -z+1/4, -y+3/4'
-  167  'y+1/2, -z, -x+1/2'
-  168  'x+3/4, -z+3/4, y+1/4'
-  169  '-x+1/4, -y+3/4, -z+3/4'
-  170  'y, -x+1/2, -z+1/2'
-  171  'x+1/4, y+1/4, -z+1/4'
-  172  '-y+1/2, x+1/2, -z'
-  173  '-x+1/4, y+3/4, z+3/4'
-  174  'y, x, z'
-  175  'x+1/4, -y+1/4, z+1/4'
-  176  '-y+1/2, -x, z+1/2'
-  177  '-z+1/4, -x+3/4, -y+3/4'
-  178  '-z, y+1/2, -x+1/2'
-  179  '-z+3/4, x+3/4, y+1/4'
-  180  '-z+1/2, -y, x+1/2'
-  181  'z+1/4, -x+3/4, y+3/4'
-  182  'z+1/2, y+1/2, x'
-  183  'z+3/4, x+3/4, -y+1/4'
-  184  'z, -y, -x'
-  185  '-y+1/4, -z+3/4, -x+3/4'
-  186  '-x, -z+1/2, y+1/2'
-  187  'y+3/4, -z+1/4, x+3/4'
-  188  'x, -z, -y'
-  189  'y+1/4, z+3/4, -x+3/4'
-  190  'x+1/2, z, y+1/2'
-  191  '-y+3/4, z+1/4, x+3/4'
-  192  '-x+1/2, z+1/2, -y'
-loop_
- _atom_site_type_symbol
- _atom_site_label
- _atom_site_symmetry_multiplicity
- _atom_site_fract_x
- _atom_site_fract_y
- _atom_site_fract_z
- _atom_site_occupancy
-  Si  Si0  8  0.00000000  0.00000000  0.00000000  1
diff --git a/notebooks/vasprun.Al.xml.gz b/notebooks/vasprun.Al.xml.gz
new file mode 100644
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diff --git a/psp/POT_GGA_PAW_PBE/POTCAR.Al.gz b/psp/POT_GGA_PAW_PBE/POTCAR.Al.gz
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