diff --git a/docs/tutorials/thermal_conductivity.ipynb b/docs/tutorials/thermal_conductivity.ipynb
index a352562..2a59af6 100644
--- a/docs/tutorials/thermal_conductivity.ipynb
+++ b/docs/tutorials/thermal_conductivity.ipynb
@@ -102,7 +102,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from polykin.properties.thermal_conductivity import KVPC_stiel_thodos"
+    "from polykin.properties.thermal_conductivity import KVPC_stiel_thodos\n",
+    "from polykin.properties.eos import PengRobinson\n",
+    "import numpy as np"
    ]
   },
   {
@@ -120,7 +122,7 @@
     {
      "data": {
       "text/plain": [
-       "0.016923428850625477"
+       "array([0.00018441])"
       ]
      },
      "execution_count": 5,
@@ -129,9 +131,31 @@
     }
    ],
    "source": [
-    "v = 184e-6 # m³/mol, with Peng-Robinson\n",
-    "\n",
-    "KVPC_stiel_thodos(v=v, M=28.05e-3, Tc=282.4, Pc=50.4e5, Zc=0.280)"
+    "Tc = 282.4   # K\n",
+    "Pc = 50.4e5  # Pa\n",
+    "eos = PengRobinson(Tc, Pc, w=0.089)\n",
+    "v = eos.v(350., 100e5, np.array([1.])) # m³/mol\n",
+    "v"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.016870676177529628"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "KVPC_stiel_thodos(v=v[0], M=28.05e-3, Tc=Tc, Pc=Pc, Zc=0.280)"
    ]
   },
   {
@@ -154,7 +178,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -170,15 +194,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
     "import numpy as np\n",
     "\n",
-    "T = 350. # temperature, K\n",
-    "\n",
-    "y = np.array([0.5, 0.5]) # mole fractions, mol/mol\n",
+    "T = 350.                           # temperature, K\n",
+    "y = np.array([0.5, 0.5])           # mole fractions, mol/mol\n",
     "M = np.array([28.05e-3, 42.08e-3]) # molar masses, kg/mol\n",
     "\n",
     "k = np.array([kv_ethylene(T), kv_propylene(T)]) # pure kv, W/(m.K)"
@@ -186,7 +209,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
@@ -195,7 +218,7 @@
        "0.02593529043825696"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -215,7 +238,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -231,32 +254,33 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "0.03818087671826145"
+       "0.03832154985250473"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "v = 112e-6  # m³/mol, with Peng-Robinson\n",
-    "\n",
     "y = np.array([0.5, 0.5])           # molmol\n",
     "M = np.array([28.05e-3, 42.08e-3]) # kg/mol\n",
     "\n",
-    "Zc = np.array([0.280, 0.274])\n",
-    "Pc = np.array([50.4e5, 46.0e5])    # Pa\n",
     "Tc = np.array([282.4, 364.9])      # K\n",
+    "Pc = np.array([50.4e5, 46.0e5])    # Pa\n",
+    "Zc = np.array([0.280, 0.274])\n",
     "w = np.array([0.089, 0.144])       # kg/kg \n",
     "\n",
-    "KVMXPC_stiel_thodos(v, y, M, Tc, Pc, Zc, w)"
+    "eos = PengRobinson(Tc, Pc, w)\n",
+    "v = eos.v(T=350., P=100e5, y=y)    # m³/mol\n",
+    "\n",
+    "KVMXPC_stiel_thodos(v[0], y, M, Tc, Pc, Zc, w)"
    ]
   },
   {
@@ -274,7 +298,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -290,7 +314,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -303,7 +327,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
@@ -336,12 +360,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [],
    "source": [
-    "from polykin.properties.thermal_conductivity import KLMX2_li\n",
-    "from polykin.properties.equations import DIPPR105"
+    "from polykin.properties.equations import DIPPR105\n",
+    "from polykin.properties.thermal_conductivity import KLMX2_li"
    ]
   },
   {
@@ -353,7 +377,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -366,19 +390,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [],
    "source": [
-    "w = np.array([0.5, 0.5]) # mass fractions\n",
-    "T = 350. # temperature, K\n",
+    "w = np.array([0.5, 0.5])                       # mass fractions\n",
+    "T = 350.                                       # temperature, K\n",
     "k = np.array([kl_styrene(T), kl_butadiene(T)]) # pure kl\n",
     "rho = np.array([dl_styrene(T)*104.152, dl_butadiene(T)*54.092]) # pure rhol"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
@@ -387,7 +411,7 @@
        "0.10808664126899356"
       ]
      },
-     "execution_count": 17,
+     "execution_count": 18,
      "metadata": {},
      "output_type": "execute_result"
     }