diff --git a/README.md b/README.md
index 9962ee54..de415f81 100644
--- a/README.md
+++ b/README.md
@@ -243,6 +243,7 @@ These are currently used to compute properties of a minimum energy conformation
 |`OpenFF NAGL2 ESP Timing Benchmark v1.0` | [2024-09-06-OpenFF-NAGL2-ESP-Timing-Benchmark-v1.0](https://github.com/openforcefield/qca-dataset-submission/tree/master/submissions/2024-09-06-OpenFF-NAGL2-ESP-Timing-Benchmark-v1.0) | Single point ESP calculations for timing/memory benchmarking | 'P', 'S', 'N', 'C', 'Cl', 'F', 'Br', 'O', 'H', 'I' | |
 |`OpenFF NAGL2 ESP Timing Benchmark v1.1` | [2024-09-18-OpenFF-NAGL2-ESP-Timing-Benchmark-v1.1](https://github.com/openforcefield/qca-dataset-submission/tree/master/submissions/2024-09-18-OpenFF-NAGL2-ESP-Timing-Benchmark-v1.1) | Single point ESP calculations for timing/memory benchmarking | 'P', 'S', 'N', 'C', 'Cl', 'F', 'Br', 'O', 'H', 'I' | |
 |`OpenFF Sulfur Hessian Training Coverage Supplement v1.0` | [2024-09-18-OpenFF-Sulfur-Hessian-Training-Coverage-Supplement-v1.0](https://github.com/openforcefield/qca-dataset-submission/tree/master/submissions/2024-09-18-OpenFF-Sulfur-Hessian-Training-Coverage-Supplement-v1.0) | Additional Hessian training data for Sage sulfur and phosphorus parameters (from ['OpenFF Sulfur Optimization Training Coverage Supplement v1.0'](https://github.com/openforcefield/qca-dataset-submission/tree/master/submissions/2024-09-11-OpenFF-Sulfur-Optimization-Training-Coverage-Supplement-v1.0)) | O, S, C, Cl, P, N, F, Br, H | |
+|`OpenFF Sulfur Hessian Training Coverage Supplement v1.1` | [2024-11-08-OpenFF-Sulfur-Hessian-Training-Coverage-Supplement-v1.1](https://github.com/openforcefield/qca-dataset-submission/tree/master/submissions/2024-11-08-OpenFF-Sulfur-Hessian-Training-Coverage-Supplement-v1.1) | Additional Hessian training data for Sage sulfur and phosphorus parameters (from ['OpenFF Sulfur Optimization Training Coverage Supplement v1.0'](https://github.com/openforcefield/qca-dataset-submission/tree/master/submissions/2024-09-11-OpenFF-Sulfur-Optimization-Training-Coverage-Supplement-v1.0)) | O, S, C, Cl, P, N, F, Br, H | |
 | `OpenFF Aniline Para Hessian v1.0` | [2024-10-07-OpenFF-Aniline-Para-Hessian-v1.0](https://github.com/openforcefield/qca-dataset-submission/tree/master/submissions/2024-10-07-OpenFF-Aniline-Para-Hessian-v1.0) | Hessian single points for the final molecules in the `OpenFF Aniline Para Opt v1.0` [dataset](https://github.com/openforcefield/qca-dataset-submission/tree/master/submissions/2021-04-02-OpenFF-Aniline-Para-Opt-v1.0) | 'O', 'Cl', 'S', 'Br', 'H', 'F', 'N', 'C' ||
 |`OpenFF Gen2 Hessian Dataset Protomers v1.0` | [2024-10-07-OpenFF-Gen2-Hessian-Dataset-Protomers-v1.0](https://github.com/openforcefield/qca-dataset-submission/tree/master/submissions/2024-10-07-OpenFF-Gen2-Hessian-Dataset-Protomers-v1.0/) | Hessian single points for the final molecules in the `OpenFF Gen2 Optimization Dataset Protomers v1.0` [dataset](https://github.com/openforcefield/qca-dataset-submission/tree/master/submissions/2021-12-21-OpenFF-Gen2-Optimization-Set-Protomers) | 'H', 'C', 'Cl', 'P', 'F', 'Br', 'O', 'N', 'S'||
 | `MLPepper-RECAP-Optimized-Fragments-Add-Iodines-v1.0` | [2024-10-11-MLPepper-RECAP-Optimized-Fragments-Add-Iodines-v1.0](https://github.com/openforcefield/qca-dataset-submission/tree/master/submissions/2024-10-11-MLPepper-RECAP-Optimized-Fragments-Add-Iodines-v1.0)  | Set of diverse iodine containing molecules with a number of calculated electrostatic properties.   | Br, Cl, S, B, O, Si, C, N, I, P, H, F|   |
diff --git a/submissions/2024-11-08-Sulfur-Hessian-Training-Coverage-Supplement-v1.1/README.md b/submissions/2024-11-08-Sulfur-Hessian-Training-Coverage-Supplement-v1.1/README.md
new file mode 100644
index 00000000..7a3edb45
--- /dev/null
+++ b/submissions/2024-11-08-Sulfur-Hessian-Training-Coverage-Supplement-v1.1/README.md
@@ -0,0 +1,68 @@
+# OpenFF Sulfur Hessian Training Coverage Supplement v1.1
+
+## Description
+
+A basic data set created to improve the training coverage of sulfonic and
+phosphonic acids, sulfone, sulfonate, sulfinyl, sulfoximine, sulfonamides,
+thioether, and 1,3-thiazole groups. The structures in this data set are the
+optimized geometries from `OpenFF Sulfur Optimization Training Coverage
+Supplement v1.0`.
+
+## General Information
+
+* Date: 2024-11-08
+* Class: OpenFF Optimization Dataset
+* Purpose: Improve coverage in Sage
+* Name: OpenFF Sulfur Hessian Training Coverage Supplement v1.1
+* Number of unique molecules: 129
+* Number of filtered molecules: 0
+* Number of conformers: 899
+* Number of conformers per molecule (min, mean, max): 1, 6.97, 10
+* Mean molecular weight: 218.80
+* Max molecular weight: 493.37
+* Charges: [-2.0, -1.0, 0.0]
+* Dataset submitter: Brent Westbrook
+* Dataset generator: Brent Westbrook
+
+## QCSubmit Generation Pipeline
+
+* `generate.py`: This script shows how the dataset was prepared.
+
+
+## QCSubmit Manifest
+
+* `generate.py`: Script describing dataset generation and submission
+* `input-environment.yaml`: Environment file used to create the Python environment for the script
+* `full-environment.yaml`: Fully-resolved environment used to execute the script
+* `opt.toml`: Experimental [qcaide](https://github.com/ntBre/qcaide) input file for defining
+variables used throughout the QCA submission process
+* `dataset.json.bz2`: Compressed dataset ready for submission
+* `dataset.pdf`: Visualization of dataset molecules
+* `dataset.smi`: SMILES strings for dataset molecules
+
+## Metadata
+
+* Elements: {O, S, C, Cl, P, N, F, Br, H}
+* Spec: default
+	* basis: DZVP
+	* implicit_solvent: None
+	* keywords: {}
+	* maxiter: 200
+	* method: B3LYP-D3BJ
+	* program: psi4
+	* SCF properties:
+		* dipole
+		* quadrupole
+		* wiberg_lowdin_indices
+		* mayer_indices
+
+## Changelog
+v1.0 included a manual implementation of
+`OptimizationResultCollection.create_basic_dataset` that failed to preserve
+QCArchive molecule IDs between the optimization and single-point datasets.
+Unfortunately, this issue would not have been avoided by that version of
+`create_basic_dataset` either. The issue has been fixed in openff-qcsubmit
+[version
+0.54](https://github.com/openforcefield/openff-qcsubmit/releases/tag/0.54.0), so
+the environment has been updated to use this release, and the `generate.py`
+script has been updated to use `create_basic_dataset`.
diff --git a/submissions/2024-11-08-Sulfur-Hessian-Training-Coverage-Supplement-v1.1/dataset.json.bz2 b/submissions/2024-11-08-Sulfur-Hessian-Training-Coverage-Supplement-v1.1/dataset.json.bz2
new file mode 100644
index 00000000..4f18b10a
--- /dev/null
+++ b/submissions/2024-11-08-Sulfur-Hessian-Training-Coverage-Supplement-v1.1/dataset.json.bz2
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1f81fab3d7782cc1b2e7088de4919fdad9314e2daf5b53d6444190c3f7d50a6b
+size 650626
diff --git a/submissions/2024-11-08-Sulfur-Hessian-Training-Coverage-Supplement-v1.1/dataset.pdf b/submissions/2024-11-08-Sulfur-Hessian-Training-Coverage-Supplement-v1.1/dataset.pdf
new file mode 100644
index 00000000..47af601c
Binary files /dev/null and b/submissions/2024-11-08-Sulfur-Hessian-Training-Coverage-Supplement-v1.1/dataset.pdf differ
diff --git a/submissions/2024-11-08-Sulfur-Hessian-Training-Coverage-Supplement-v1.1/full-environment.yaml b/submissions/2024-11-08-Sulfur-Hessian-Training-Coverage-Supplement-v1.1/full-environment.yaml
new file mode 100644
index 00000000..821f9714
--- /dev/null
+++ b/submissions/2024-11-08-Sulfur-Hessian-Training-Coverage-Supplement-v1.1/full-environment.yaml
@@ -0,0 +1,309 @@
+name: qcarchive-user-submit
+channels:
+  - openeye
+  - conda-forge
+dependencies:
+  - _libgcc_mutex=0.1=conda_forge
+  - _openmp_mutex=4.5=2_gnu
+  - ambertools=23.6=cuda_None_nompi_py311h4a53416_105
+  - annotated-types=0.7.0=pyhd8ed1ab_0
+  - anyio=4.6.2.post1=pyhd8ed1ab_0
+  - apsw=3.46.1.0=py311h333efcf_1
+  - argcomplete=3.5.1=pyhd8ed1ab_0
+  - argon2-cffi=23.1.0=pyhd8ed1ab_0
+  - argon2-cffi-bindings=21.2.0=py311h9ecbd09_5
+  - arpack=3.9.1=nompi_h77f6705_101
+  - arrow=1.3.0=pyhd8ed1ab_0
+  - asttokens=2.4.1=pyhd8ed1ab_0
+  - async-lru=2.0.4=pyhd8ed1ab_0
+  - attrs=24.2.0=pyh71513ae_0
+  - babel=2.16.0=pyhd8ed1ab_0
+  - basis_set_exchange=0.10=pyhd8ed1ab_1
+  - beautifulsoup4=4.12.3=pyha770c72_0
+  - bleach=6.2.0=pyhd8ed1ab_0
+  - blosc=1.21.6=hef167b5_0
+  - brotli=1.1.0=hb9d3cd8_2
+  - brotli-bin=1.1.0=hb9d3cd8_2
+  - brotli-python=1.1.0=py311hfdbb021_2
+  - bson=0.5.9=py_0
+  - bzip2=1.0.8=h4bc722e_7
+  - c-ares=1.34.2=heb4867d_0
+  - c-blosc2=2.15.1=hc57e6cf_0
+  - ca-certificates=2024.8.30=hbcca054_0
+  - cached-property=1.5.2=hd8ed1ab_1
+  - cached_property=1.5.2=pyha770c72_1
+  - cachetools=5.5.0=pyhd8ed1ab_0
+  - cairo=1.18.0=hebfffa5_3
+  - certifi=2024.8.30=pyhd8ed1ab_0
+  - cffi=1.17.1=py311hf29c0ef_0
+  - chardet=5.2.0=py311h38be061_2
+  - charset-normalizer=3.4.0=pyhd8ed1ab_0
+  - colorama=0.4.6=pyhd8ed1ab_0
+  - comm=0.2.2=pyhd8ed1ab_0
+  - contourpy=1.3.0=py311hd18a35c_2
+  - cudatoolkit=11.8.0=h4ba93d1_13
+  - cycler=0.12.1=pyhd8ed1ab_0
+  - debugpy=1.8.8=py311hfdbb021_0
+  - decorator=5.1.1=pyhd8ed1ab_0
+  - defusedxml=0.7.1=pyhd8ed1ab_0
+  - entrypoints=0.4=pyhd8ed1ab_0
+  - exceptiongroup=1.2.2=pyhd8ed1ab_0
+  - executing=2.1.0=pyhd8ed1ab_0
+  - fftw=3.3.10=nompi_hf1063bd_110
+  - font-ttf-dejavu-sans-mono=2.37=hab24e00_0
+  - font-ttf-inconsolata=3.000=h77eed37_0
+  - font-ttf-source-code-pro=2.038=h77eed37_0
+  - font-ttf-ubuntu=0.83=h77eed37_3
+  - fontconfig=2.15.0=h7e30c49_1
+  - fonts-conda-ecosystem=1=0
+  - fonts-conda-forge=1=0
+  - fonttools=4.54.1=py311h2dc5d0c_1
+  - fqdn=1.5.1=pyhd8ed1ab_0
+  - freetype=2.12.1=h267a509_2
+  - freetype-py=2.3.0=pyhd8ed1ab_0
+  - greenlet=3.1.1=py311hfdbb021_0
+  - h11=0.14.0=pyhd8ed1ab_0
+  - h2=4.1.0=pyhd8ed1ab_0
+  - hdf4=4.2.15=h2a13503_7
+  - hdf5=1.14.4=nompi_h2d575fe_103
+  - hpack=4.0.0=pyh9f0ad1d_0
+  - httpcore=1.0.6=pyhd8ed1ab_0
+  - httpx=0.27.2=pyhd8ed1ab_0
+  - hyperframe=6.0.1=pyhd8ed1ab_0
+  - icu=75.1=he02047a_0
+  - idna=3.10=pyhd8ed1ab_0
+  - importlib-metadata=8.5.0=pyha770c72_0
+  - importlib_metadata=8.5.0=hd8ed1ab_0
+  - importlib_resources=6.4.5=pyhd8ed1ab_0
+  - iniconfig=2.0.0=pyhd8ed1ab_0
+  - ipykernel=6.29.5=pyh3099207_0
+  - ipython=8.29.0=pyh707e725_0
+  - ipywidgets=8.1.5=pyhd8ed1ab_0
+  - isoduration=20.11.0=pyhd8ed1ab_0
+  - jedi=0.19.1=pyhd8ed1ab_0
+  - jinja2=3.1.4=pyhd8ed1ab_0
+  - joblib=1.4.2=pyhd8ed1ab_0
+  - json5=0.9.25=pyhd8ed1ab_0
+  - jsonpointer=3.0.0=py311h38be061_1
+  - jsonschema=4.23.0=pyhd8ed1ab_0
+  - jsonschema-specifications=2024.10.1=pyhd8ed1ab_0
+  - jsonschema-with-format-nongpl=4.23.0=hd8ed1ab_0
+  - jupyter-lsp=2.2.5=pyhd8ed1ab_0
+  - jupyter_client=8.6.3=pyhd8ed1ab_0
+  - jupyter_core=5.7.2=pyh31011fe_1
+  - jupyter_events=0.10.0=pyhd8ed1ab_0
+  - jupyter_server=2.14.2=pyhd8ed1ab_0
+  - jupyter_server_terminals=0.5.3=pyhd8ed1ab_0
+  - jupyterlab=4.2.5=pyhd8ed1ab_0
+  - jupyterlab_pygments=0.3.0=pyhd8ed1ab_1
+  - jupyterlab_server=2.27.3=pyhd8ed1ab_0
+  - jupyterlab_widgets=3.0.13=pyhd8ed1ab_0
+  - keyutils=1.6.1=h166bdaf_0
+  - kiwisolver=1.4.7=py311hd18a35c_0
+  - krb5=1.21.3=h659f571_0
+  - lcms2=2.16=hb7c19ff_0
+  - ld_impl_linux-64=2.43=h712a8e2_2
+  - lerc=4.0.0=h27087fc_0
+  - libaec=1.1.3=h59595ed_0
+  - libblas=3.9.0=25_linux64_openblas
+  - libboost=1.84.0=hb8260a3_6
+  - libboost-python=1.84.0=py311h5b7b71f_6
+  - libbrotlicommon=1.1.0=hb9d3cd8_2
+  - libbrotlidec=1.1.0=hb9d3cd8_2
+  - libbrotlienc=1.1.0=hb9d3cd8_2
+  - libcblas=3.9.0=25_linux64_openblas
+  - libcurl=8.10.1=hbbe4b11_0
+  - libdeflate=1.22=hb9d3cd8_0
+  - libedit=3.1.20191231=he28a2e2_2
+  - libev=4.33=hd590300_2
+  - libexpat=2.6.4=h5888daf_0
+  - libffi=3.4.2=h7f98852_5
+  - libgcc=14.2.0=h77fa898_1
+  - libgcc-ng=14.2.0=h69a702a_1
+  - libgfortran=14.2.0=h69a702a_1
+  - libgfortran-ng=14.2.0=h69a702a_1
+  - libgfortran5=14.2.0=hd5240d6_1
+  - libglib=2.82.2=h2ff4ddf_0
+  - libgomp=14.2.0=h77fa898_1
+  - libiconv=1.17=hd590300_2
+  - libjpeg-turbo=3.0.0=hd590300_1
+  - liblapack=3.9.0=25_linux64_openblas
+  - libnetcdf=4.9.2=nompi_h2564987_115
+  - libnghttp2=1.64.0=h161d5f1_0
+  - libnsl=2.0.1=hd590300_0
+  - libopenblas=0.3.28=pthreads_h94d23a6_1
+  - libpng=1.6.44=hadc24fc_0
+  - libpq=16.4=h2d7952a_3
+  - librdkit=2024.03.5=h79cfef2_3
+  - libsodium=1.0.20=h4ab18f5_0
+  - libsqlite=3.46.1=hadc24fc_0
+  - libssh2=1.11.0=h0841786_0
+  - libstdcxx=14.2.0=hc0a3c3a_1
+  - libstdcxx-ng=14.2.0=h4852527_1
+  - libtiff=4.7.0=he137b08_1
+  - libuuid=2.38.1=h0b41bf4_0
+  - libwebp-base=1.4.0=hd590300_0
+  - libxcb=1.17.0=h8a09558_0
+  - libxcrypt=4.4.36=hd590300_1
+  - libxml2=2.13.4=hb346dea_2
+  - libzip=1.11.2=h6991a6a_0
+  - libzlib=1.3.1=hb9d3cd8_2
+  - lz4-c=1.9.4=hcb278e6_0
+  - markupsafe=3.0.2=py311h2dc5d0c_0
+  - matplotlib-base=3.9.2=py311h2b939e6_2
+  - matplotlib-inline=0.1.7=pyhd8ed1ab_0
+  - mda-xdrlib=0.2.0=pyhd8ed1ab_0
+  - mdtraj=1.10.1=py311h4734c11_0
+  - mistune=3.0.2=pyhd8ed1ab_0
+  - msgpack-python=1.1.0=py311hd18a35c_0
+  - munkres=1.1.4=pyh9f0ad1d_0
+  - nbclient=0.10.0=pyhd8ed1ab_0
+  - nbconvert-core=7.16.4=pyhd8ed1ab_1
+  - nbformat=5.10.4=pyhd8ed1ab_0
+  - ncurses=6.5=he02047a_1
+  - nest-asyncio=1.6.0=pyhd8ed1ab_0
+  - netcdf-fortran=4.6.1=nompi_ha5d1325_107
+  - networkx=3.4.2=pyhd8ed1ab_1
+  - nomkl=1.0=h5ca1d4c_0
+  - notebook=7.2.2=pyhd8ed1ab_0
+  - notebook-shim=0.2.4=pyhd8ed1ab_0
+  - numexpr=2.10.1=py311h38b10cd_103
+  - numpy=1.26.4=py311h64a7726_0
+  - ocl-icd=2.3.2=hd590300_1
+  - ocl-icd-system=1.0.0=1
+  - openeye-toolkits=2024.1.3=py311_0
+  - openff-amber-ff-ports=0.0.4=pyhca7485f_0
+  - openff-forcefields=2024.09.0=pyhff2d567_0
+  - openff-interchange=0.4.0=pyhd8ed1ab_0
+  - openff-interchange-base=0.4.0=pyhd8ed1ab_0
+  - openff-qcsubmit=0.54.0=pyhd8ed1ab_0
+  - openff-toolkit=0.16.5=pyhd8ed1ab_0
+  - openff-toolkit-base=0.16.5=pyhd8ed1ab_0
+  - openff-units=0.2.2=pyhca7485f_0
+  - openff-utilities=0.1.12=pyhd8ed1ab_0
+  - openjpeg=2.5.2=h488ebb8_0
+  - openmm=8.1.2=py311he040c58_2
+  - openssl=3.3.2=hb9d3cd8_0
+  - overrides=7.7.0=pyhd8ed1ab_0
+  - packaging=24.1=pyhd8ed1ab_0
+  - pandas=2.2.3=py311h7db5c69_1
+  - pandocfilters=1.5.0=pyhd8ed1ab_0
+  - panedr=0.8.0=pyhd8ed1ab_0
+  - parmed=4.3.0=py311h8cc7b42_0
+  - parso=0.8.4=pyhd8ed1ab_0
+  - pcre2=10.44=hba22ea6_2
+  - perl=5.32.1=7_hd590300_perl5
+  - pexpect=4.9.0=pyhd8ed1ab_0
+  - pickleshare=0.7.5=py_1003
+  - pillow=11.0.0=py311h49e9ac3_0
+  - pint=0.23=pyhd8ed1ab_1
+  - pip=24.3.1=pyh8b19718_0
+  - pixman=0.43.2=h59595ed_0
+  - pkgutil-resolve-name=1.3.10=pyhd8ed1ab_1
+  - platformdirs=4.3.6=pyhd8ed1ab_0
+  - pluggy=1.5.0=pyhd8ed1ab_0
+  - prometheus_client=0.21.0=pyhd8ed1ab_0
+  - prompt-toolkit=3.0.48=pyha770c72_0
+  - psutil=6.1.0=py311h9ecbd09_0
+  - pthread-stubs=0.4=hb9d3cd8_1002
+  - ptyprocess=0.7.0=pyhd3deb0d_0
+  - pure_eval=0.2.3=pyhd8ed1ab_0
+  - py-cpuinfo=9.0.0=pyhd8ed1ab_0
+  - pycairo=1.27.0=py311h124c5f0_0
+  - pycalverter=1.6.1=pyhd8ed1ab_1
+  - pycparser=2.22=pyhd8ed1ab_0
+  - pydantic=2.9.2=pyhd8ed1ab_0
+  - pydantic-core=2.23.4=py311h9e33e62_0
+  - pyedr=0.8.0=pyhd8ed1ab_0
+  - pygments=2.18.0=pyhd8ed1ab_0
+  - pyjwt=2.9.0=pyhd8ed1ab_1
+  - pyparsing=3.2.0=pyhd8ed1ab_1
+  - pysocks=1.7.1=pyha2e5f31_6
+  - pytables=3.10.1=py311h3ebe2b2_3
+  - pytest=8.3.3=pyhd8ed1ab_0
+  - python=3.11.10=hc5c86c4_3_cpython
+  - python-constraint=1.4.0=py_0
+  - python-dateutil=2.9.0=pyhd8ed1ab_0
+  - python-fastjsonschema=2.20.0=pyhd8ed1ab_0
+  - python-json-logger=2.0.7=pyhd8ed1ab_0
+  - python-tzdata=2024.2=pyhd8ed1ab_0
+  - python_abi=3.11=5_cp311
+  - pytz=2024.1=pyhd8ed1ab_0
+  - pyyaml=6.0.2=py311h9ecbd09_1
+  - pyzmq=26.2.0=py311h7deb3e3_3
+  - qcelemental=0.28.0=pyhd8ed1ab_1
+  - qcportal=0.56=pyhd8ed1ab_1
+  - qhull=2020.2=h434a139_5
+  - rdkit=2024.03.5=py311h845bd92_3
+  - readline=8.2=h8228510_1
+  - referencing=0.35.1=pyhd8ed1ab_0
+  - regex=2024.11.6=py311h9ecbd09_0
+  - reportlab=4.2.5=py311h9ecbd09_0
+  - requests=2.32.3=pyhd8ed1ab_0
+  - rfc3339-validator=0.1.4=pyhd8ed1ab_0
+  - rfc3986-validator=0.1.1=pyh9f0ad1d_0
+  - rlpycairo=0.2.0=pyhd8ed1ab_0
+  - rpds-py=0.21.0=py311h9e33e62_0
+  - scipy=1.14.1=py311he9a78e4_1
+  - send2trash=1.8.3=pyh0d859eb_0
+  - setuptools=75.3.0=pyhd8ed1ab_0
+  - six=1.16.0=pyh6c4a22f_0
+  - smirnoff99frosst=1.1.0=pyh44b312d_0
+  - snappy=1.2.1=ha2e4443_0
+  - sniffio=1.3.1=pyhd8ed1ab_0
+  - soupsieve=2.5=pyhd8ed1ab_1
+  - sqlalchemy=2.0.36=py311h9ecbd09_0
+  - sqlite=3.46.1=h9eae976_0
+  - stack_data=0.6.2=pyhd8ed1ab_0
+  - tabulate=0.9.0=pyhd8ed1ab_1
+  - terminado=0.18.1=pyh0d859eb_0
+  - tinycss2=1.4.0=pyhd8ed1ab_0
+  - tk=8.6.13=noxft_h4845f30_101
+  - tomli=2.0.2=pyhd8ed1ab_0
+  - tornado=6.4.1=py311h9ecbd09_1
+  - tqdm=4.67.0=pyhd8ed1ab_0
+  - traitlets=5.14.3=pyhd8ed1ab_0
+  - types-python-dateutil=2.9.0.20241003=pyhff2d567_0
+  - typing-extensions=4.12.2=hd8ed1ab_0
+  - typing_extensions=4.12.2=pyha770c72_0
+  - typing_utils=0.1.0=pyhd8ed1ab_0
+  - tzdata=2024b=hc8b5060_0
+  - unicodedata2=15.1.0=py311h9ecbd09_1
+  - unidecode=1.3.8=pyhd8ed1ab_0
+  - uri-template=1.3.0=pyhd8ed1ab_0
+  - urllib3=2.2.3=pyhd8ed1ab_0
+  - wcwidth=0.2.13=pyhd8ed1ab_0
+  - webcolors=24.8.0=pyhd8ed1ab_0
+  - webencodings=0.5.1=pyhd8ed1ab_2
+  - websocket-client=1.8.0=pyhd8ed1ab_0
+  - wheel=0.44.0=pyhd8ed1ab_0
+  - widgetsnbextension=4.0.13=pyhd8ed1ab_0
+  - xmltodict=0.14.2=pyhd8ed1ab_0
+  - xorg-libice=1.1.1=hb9d3cd8_1
+  - xorg-libsm=1.2.4=he73a12e_1
+  - xorg-libx11=1.8.10=h4f16b4b_0
+  - xorg-libxau=1.0.11=hb9d3cd8_1
+  - xorg-libxdmcp=1.1.5=hb9d3cd8_0
+  - xorg-libxext=1.3.6=hb9d3cd8_0
+  - xorg-libxrender=0.9.11=hb9d3cd8_1
+  - xorg-libxt=1.3.0=hb9d3cd8_2
+  - xorg-xorgproto=2024.1=hb9d3cd8_1
+  - xz=5.2.6=h166bdaf_0
+  - yaml=0.2.5=h7f98852_2
+  - zeromq=4.3.5=h3b0a872_6
+  - zipp=3.20.2=pyhd8ed1ab_0
+  - zlib=1.3.1=hb9d3cd8_2
+  - zlib-ng=2.2.2=h5888daf_0
+  - zstandard=0.23.0=py311hbc35293_1
+  - zstd=1.5.6=ha6fb4c9_0
+  - pip:
+      - amberutils==21.0
+      - edgembar==0.2
+      - mmpbsa-py==16.0
+      - packmol-memgen==2024.2.9
+      - pdb4amber==22.0
+      - pymsmt==22.0
+      - pytraj==2.0.6
+      - qcaide==0.0.0
+      - sander==22.0
+prefix: /home/brent/mambaforge/envs/qcarchive-user-submit
diff --git a/submissions/2024-11-08-Sulfur-Hessian-Training-Coverage-Supplement-v1.1/generate.py b/submissions/2024-11-08-Sulfur-Hessian-Training-Coverage-Supplement-v1.1/generate.py
new file mode 100644
index 00000000..57f91cc7
--- /dev/null
+++ b/submissions/2024-11-08-Sulfur-Hessian-Training-Coverage-Supplement-v1.1/generate.py
@@ -0,0 +1,115 @@
+from pathlib import Path
+
+import numpy as np
+import qcportal  # noqa avoid zstd disaster
+from openff.qcsubmit.results import OptimizationResultCollection
+from openff.qcsubmit.results.filters import (
+    ConnectivityFilter,
+    RecordStatusEnum,
+    RecordStatusFilter,
+)
+from openff.qcsubmit.utils import _CachedPortalClient, portal_client_manager
+from openff.toolkit import ForceField
+from qcaide import Submission
+from qcportal.singlepoint import SinglepointDriver
+
+# Load config file and force field
+ff = ForceField("openff-2.1.0.offxml")
+config = Submission.from_toml("opt.toml")
+
+client = _CachedPortalClient("https://api.qcarchive.molssi.org", ".")
+opt = OptimizationResultCollection.from_server(
+    client,
+    datasets=["OpenFF Sulfur Optimization Training Coverage Supplement v1.0"],
+)
+
+print(f"Retrieved {opt.n_results} results")
+
+with portal_client_manager(lambda _: client):
+    opt = opt.filter(
+        RecordStatusFilter(status=RecordStatusEnum.complete),
+        ConnectivityFilter(tolerance=1.2),
+    )
+
+    opt_hashes = {
+        rec.final_molecule.get_hash() for rec, _mol in opt.to_records()
+    }
+
+print(f"Filtered to {opt.n_results} completed records")
+
+# populate dataset
+dataset = opt.create_basic_dataset(
+    dataset_name=config.name,
+    description=config.description,
+    tagline=config.name,
+    driver=SinglepointDriver.hessian,
+)
+dataset.metadata.submitter = config.submitter
+dataset.metadata.long_description_url = (
+    "https://github.com/openforcefield/qca-dataset-submission/tree/master/"
+    "submissions/" + str(Path.cwd().name)
+)
+
+# confirm that the qcelemental molecule hashes have not changed
+new_hashes = {
+    qcemol.identifiers.molecule_hash
+    for moldata in dataset.dataset.values()
+    for qcemol in moldata.initial_molecules
+}
+
+assert opt_hashes == new_hashes
+
+print("all hashes match")
+
+
+# summarize dataset for readme
+confs = np.array([len(mol.conformers) for mol in dataset.molecules])
+
+print("* Number of unique molecules:", dataset.n_molecules)
+print("* Number of filtered molecules:", dataset.n_filtered)
+print("* Number of conformers:", sum(confs))
+print(
+    "* Number of conformers per molecule (min, mean, max): "
+    f"{confs.min()}, {confs.mean():.2f}, {confs.max()}"
+)
+
+masses = [
+    [
+        sum([atom.mass.m for atom in molecule.atoms])
+        for molecule in dataset.molecules
+    ]
+]
+print(f"* Mean molecular weight: {np.mean(np.array(masses)):.2f}")
+print(f"* Max molecular weight: {np.max(np.array(masses)):.2f}")
+print("* Charges:", sorted(set(m.total_charge.m for m in dataset.molecules)))
+
+print("## Metadata")
+print(f"* Elements: {{{', '.join(dataset.metadata.dict()['elements'])}}}")
+
+
+def print_field(od, field):
+    print(f"\t* {field}: {od[field]}")
+
+
+fields = [
+    "basis",
+    "implicit_solvent",
+    "keywords",
+    "maxiter",
+    "method",
+    "program",
+]
+for spec, obj in dataset.qc_specifications.items():
+    od = obj.dict()
+    print("* Spec:", spec)
+    for field in fields:
+        print_field(od, field)
+    print("\t* SCF properties:")
+    for field in od["scf_properties"]:
+        print(f"\t\t* {field}")
+
+
+# write output files
+dataset.export_dataset("dataset.json.bz2")
+dataset.molecules_to_file("output.smi", "smi")
+dataset.visualize("dataset.pdf", columns=8)
diff --git a/submissions/2024-11-08-Sulfur-Hessian-Training-Coverage-Supplement-v1.1/input-environment.yaml b/submissions/2024-11-08-Sulfur-Hessian-Training-Coverage-Supplement-v1.1/input-environment.yaml
new file mode 100644
index 00000000..c4f8df3d
--- /dev/null
+++ b/submissions/2024-11-08-Sulfur-Hessian-Training-Coverage-Supplement-v1.1/input-environment.yaml
@@ -0,0 +1,15 @@
+name: qcarchive-user-submit
+
+channels:
+  - conda-forge
+  - openeye
+
+dependencies:
+  - python =3.11
+  - pip
+  - qcportal >=0.49
+  - openff-qcsubmit >= 0.54
+  - openff-toolkit
+  - openeye-toolkits
+  - pip:
+    - git+https://github.com/ntBre/qcaide
diff --git a/submissions/2024-11-08-Sulfur-Hessian-Training-Coverage-Supplement-v1.1/opt.toml b/submissions/2024-11-08-Sulfur-Hessian-Training-Coverage-Supplement-v1.1/opt.toml
new file mode 100644
index 00000000..1ad15489
--- /dev/null
+++ b/submissions/2024-11-08-Sulfur-Hessian-Training-Coverage-Supplement-v1.1/opt.toml
@@ -0,0 +1,51 @@
+name = "OpenFF Sulfur Hessian Training Coverage Supplement v1.1"
+description = """
+
+A basic data set created to improve the training coverage of sulfonic and
+phosphonic acids, sulfone, sulfonate, sulfinyl, sulfoximine, sulfonamides,
+thioether, and 1,3-thiazole groups. The structures in this data set are the
+optimized geometries from `OpenFF Sulfur Optimization Training Coverage
+Supplement v1.0`.
+
+"""
+short_description = "Additional Hessian training data for Sage sulfur and phosphorus parameters"
+class = "optimization"
+purpose = "Improve coverage in Sage"
+submitter = "Brent Westbrook"
+
+[[pipeline]]
+filename = "generate-dataset.py"
+description = "This script shows how the dataset was prepared."
+
+# input files
+[[manifest]]
+filename = "generate-dataset.py"
+description = "Script describing dataset generation and submission"
+
+[[manifest]]
+filename = "input-environment.yaml"
+description = "Environment file used to create the Python environment for the script"
+
+[[manifest]]
+filename = "full-environment.yaml"
+description = "Fully-resolved environment used to execute the script"
+
+[[manifest]]
+filename = "opt.toml"
+description = """
+Experimental [qcaide](https://github.com/ntBre/qcaide) input file for defining
+variables used throughout the QCA submission process
+"""
+
+# output files
+[[manifest]]
+filename = "dataset.json.bz2"
+description = "Compressed dataset ready for submission"
+
+[[manifest]]
+filename = "dataset.pdf"
+description = "Visualization of dataset molecules"
+
+[[manifest]]
+filename = "dataset.smi"
+description = "SMILES strings for dataset molecules"
\ No newline at end of file
diff --git a/submissions/2024-11-08-Sulfur-Hessian-Training-Coverage-Supplement-v1.1/output.smi b/submissions/2024-11-08-Sulfur-Hessian-Training-Coverage-Supplement-v1.1/output.smi
new file mode 100644
index 00000000..bee32d71
--- /dev/null
+++ b/submissions/2024-11-08-Sulfur-Hessian-Training-Coverage-Supplement-v1.1/output.smi
@@ -0,0 +1,129 @@
+C(C(=O)O)S(=O)(=O)CC(=O)O
+C(C(C(=O)O)N)P(=O)(O)O
+C(CBr)S(=O)(=O)CCBr
+C(CCS(=O)(=O)O)CN(Cl)Cl
+C(CCS(=O)(=O)[O-])CO
+C(CS(=O)(=O)N)N
+C1=CSC(=C1)S(=O)(=O)CC#N
+C1=CSC(=C1)S(=O)(=O)CC(=S)N
+C1=CSC2=C1C(=NC(=O)N2)N
+C1CCS(=O)(=O)C1
+C1CS(=O)(=O)NCO1
+C1CS1
+C1[C@H](N=C(S1)N)CC(=O)O
+C=CCS(=O)(=O)CC=C
+C=CS(=O)(=O)C=C
+C=CS(=O)(=O)N
+CCN1C=NN=C1SC
+CCS(=O)(=O)C1=NON=C1C
+CCS(=O)(=O)NO
+CS(=O)(=O)CC(=O)/C=N/O
+CS(=O)(=O)c1ccccc1
+CSC
+CSc1c2c(ncn1)N=CC2
+C[C@@H]1[C@@H](O1)P(=O)(O)O
+c1cc2c(cc1F)SC(=N2)NN
+c1ccc(cc1)C(F)P(=O)(O)O
+c1ccc(cc1)S(=O)(=O)CC#N
+c1ccc2c(c1)C(=O)C(=CS2(=O)=O)Br
+c1ccc2c(c1)C=CS2(=O)=O
+C1(=NN=C(S1)S(=O)(=O)N)N
+C1=C(SC2=C1C=C(S2)S(=O)(=O)N)CN
+C1=CSC=C1
+C1=NN=C(S1)Br
+C1=NSC(=N1)N
+C1CC1C(=O)NC2=NN=CS2
+CC(CN)S(=O)(=O)C
+CCS(=N)(=O)c1ccc(cc1)Nc2ncc(c(n2)N[C@@H](C)C(C)(C)O)Br
+CCSc1ncnc(n1)N
+CC[C@@H](CS(=O)(=O)O)[N+](=O)[O-]
+CN1C(=O)SSC1=O
+COC1=CSC=C1C(=O)O
+COS(=O)(=O)CS(=O)(=O)C
+CS(=O)(=O)CC#N
+CS(=O)(=O)CCC#N
+CS(=O)(=O)N
+CS(=O)(=O)c1ccncc1N
+CS/C(=C(\C#N)/SC)/C#N
+CSC1=NN=C(S1)NS(=O)(=O)N
+Cc1cccc2c1N=C(S2)S
+c1cc(ccc1/N=N/c2c3ccc(cc3ccc2O)S(=O)(=O)[O-])S(=O)(=O)[O-]
+C(/C=C\C(C(=O)O)N)P(=O)(O)O
+C(C(C(=O)O)N)SCP(=O)(O)O
+C1=CSC=N1
+C1=NC(=C(N1)N)S(=O)(=O)N
+C1C2=C(NN=C2CS1(=O)=O)C(=O)O
+C1CC(=C/C(=C\P(=O)(O)O)/C1)C(=O)O
+C1[C@@H]([C@]1(C(=O)O)N)CP(=O)(O)O
+CC1(CN(C(=O)N1Cl)CCS(=O)(=O)[O-])C
+CS(=N)(=O)CCCOC1=NN2C(=NC=C2C3=Cc4ccccc4O3)C=C1
+C[C@@H]1[C@@H]([C@@H]([C@H]([C@@H](N1)S(=O)(=O)O)O)O)O
+C[C@H]([C@@H](C)O)Nc1c(cnc(n1)Nc2ccc(cc2)S(=N)(=O)C)Br
+C[C@H]([C@@H](C)O)Nc1c(cnc(n1)Nc2ccc(cc2)S(=N)(=O)CCO)Br
+c1cc(ccc1C(CN)CS(=O)(=O)O)Cl
+C(/C=C/P(=O)(O)O)C(C(=O)O)N
+C(C[C@@H](CS)N)CS(=O)(=O)[O-]
+C1=C(SC(=N1)NC(=O)C(=O)O)Br
+C1C(C2=C(SC=C2C1=O)Br)O
+C1C=CCS1(=O)=O
+C1CNS(=O)(=O)C1
+CC(c1ccc(cc1)S(=O)(=O)O)(C(=O)O)N
+CN1C(=NC(=N1)[N+](=O)[O-])S(=O)(=O)C
+COc1cc(ccc1c2cc(ncc2F)Nc3cc(ccn3)C[S@](=N)(=O)C)F
+CS(=O)(=O)NO
+C[N+]1(CCCCC1)CS(=O)(=O)[O-]
+Cc1cc(ccc1S(=N)(=O)C)Nc2ncc(c(n2)N[C@H](C)C(C)(C)O)Br
+c1cc(ccc1C(CN)(CS(=O)(=O)O)O)Cl
+c1cc(ccc1CN)S(=O)(=O)N
+c1ccc(cc1)[C@H](CO)S(=O)(=O)O
+c1ccc2c(c1)ccc(c2/N=N/c3ccc(cc3)S(=O)(=O)[O-])O
+C([C@@H](C(=O)O)N)NCP(=O)(O)O
+C1(=NN=C(S1)S)S
+C1=C(SC(=N1)NC(=O)C(=O)O)C#N
+C1=CN=C(N1)S(=O)(=O)N
+C1CS(=O)(=O)CCN1
+C1[C@@H]([C@H]1P(=O)(O)O)[C@@H](C(=O)O)N
+CC(NC(=O)C(Cc1ccccc1)CS)S(=O)(=O)[O-]
+CC1=[N+](c2ccccc2S1)CCCS(=O)(=O)[O-]
+CCCN1C(=O)c2cccc3c2c(cc(c3N)S(=O)(=O)[O-])C1=O
+CN1C(CC2=C/C(=N/NC(=O)N)/C(=O)C=C21)S(=O)(=O)[O-]
+CN1CCS(=O)(=O)C1=O
+CNCC(c1ccc(c(c1)O)O)S(=O)(=O)O
+COc1cccc2c1C=C(O2)C3=CN=C4N3N=C(C=C4)OCCCS(=N)(=O)C
+C[C@H]([C@H](C)O)Nc1c(cnc(n1)Nc2ccc(c(c2)OC)S(=N)(=O)C)Br
+c1cc(c(cc1[N+](=O)[O-])S(=O)(=O)[O-])/C=C/c2ccc(cc2S(=O)(=O)[O-])[N+](=O)[O-]
+c1cc2c(cc1N)SC(=C2)S(=O)(=O)N
+c1nc(c2c(n1)SC=N2)N
+C(CP(=O)(O)O)[C@@H](C(=O)O)N
+C1CN(S(=O)(=O)C1)N=O
+C1[C@@H]([C@H](C(N1)S(=O)(=O)O)O)O
+CC(C(C)(C)O)Sc1c(cnc(n1)Nc2ccc(cc2)S(=N)(=O)C)Br
+CC(C)(C)/[N+](=C/c1ccc(cc1S(=O)(=O)[O-])S(=O)(=O)[O-])/[O-]
+CC1(COC(=O)N1Cl)CS(=O)(=O)CCS(=O)(=O)[O-]
+CC1=Nc2cc(ccc2S1)O
+CCCCCCCCS(=O)(=O)[O-]
+CS(=N)(=O)CC[C@@H](C(=O)O)N
+CS(=O)(=O)C
+CS(=O)(=O)C=C
+C[C@H](C(C)(C)O)Nc1c(cnc(n1)Nc2ccc(cc2)S(=N)(=O)C)Br
+c1cc(ccc1C2=NNC(=O)S2)Cl
+c1cc2c(ccc(c2c(c1)S(=O)(=O)O)N)S(=O)(=O)O
+c1ccc(cc1)/N=N/c2c(ccc3c2c(cc(c3)S(=O)(=O)[O-])S(=O)(=O)[O-])O
+c1ccc(cc1)C(O)P(=O)(O)O
+c1ccc(cc1)C=C(c2ccccc2)S(=O)(=O)O
+C/C(=C\C(C(=O)O)N)/CP(=O)(O)O
+C1=C(N=CN1)/C=C\2/C(=O)NC(=O)S2
+C1=CN=C2N(C1=O)N=C(S2)S(=O)(=O)N
+C1[C@H]([C@H]1S(=O)(=O)O)[C@H](C(=O)O)N
+CC1C(C(C(N1)S(=O)(=O)O)O)O
+CC[S@@](=N)(=O)c1ccc(cc1)Nc2ncc(c(n2)N[C@H](C)[C@@H](C)O)Br
+CN1C=CC(=O)C(=C1)S(=O)(=O)N
+COc1cc(cc(c1NC(=O)c2ccc(cc2)S(=N)(=O)C)C(=O)Nc3ccc(cn3)Cl)Cl
+C[C@@H]([C@H](COC)Nc1c(cnc(n1)Nc2ccc(cc2)S(=N)(=O)C)Br)O
+C[C@H](C(=O)CP(=O)(O)O)N
+c1cc(ccc1C[C@@H](C(=O)O)N)S(=O)(=O)O
+c1cc(ccc1[C@@H](C(=O)O)N)P(=O)(O)O
+c1ccc2c(c1)N3C(=NN=N3)S2
+c1ccc2c(c1)N=C(S2)NC(=O)CCS(=O)(=O)O
+CC(CSc1c(cnc(n1)Nc2ccc(cc2)S(=N)(=O)C)Br)O
+COC(=O)C1=CSC2=C1N=NS2