Organic Photovoltaic (OPV) Database

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A database of quantum mechanical calculations on organic photovoltaic candidate molecules.

Related Publications:
Peter C. St. John, Caleb Phillips, Travis W. Kemper, A. Nolan Wilson, Michael F. Crowley, Mark R. Nimlos, Ross E. Larsen. (2018) Message-passing neural networks for high-throughput polymer screening arXiv:1807.10363

DFT calculations performed with a variety of functiona/basis set combinations. Format: The data is stored as a gzipped csv file. The fields are as follows: mol: a SDF-style string containing the optimized 3D molecule coordinates ctag: A tag for molecule identification (unused) basis: the DFT functional / basis set combination total_energy optical_lumo gap homo lumo spectral_overlap delta_homo delta_lumo delta_optical_lumo homo_extrapolated lumo_extrapolated gap_extrapolated optical_lumo_extrapolated smile: a canonicalized SMILES string representation of the molecule's 2D geometry

DFT calculations performed with a variety of functiona/basis set combinations. Format: The data is stored as a gzipped csv file. The fields are as follows: mol: ... more

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Test set data for SchNet-like models train on optimized 3D geometry.

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Test set data for SchNet-like models, but with the 3D geometry generated via DFT replaced by an approximate 3D structure optimized from the SMILES string using UFF as implemented in rdkit.

Test set data for SchNet-like models, but with the 3D geometry generated via DFT replaced by an approximate 3D structure optimized from the SMILES string using UFF as i... more

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Test set data for the models considering only unique SMILES strings as molecule inputs.

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Training set data for SchNet-like models train on optimized 3D geometry.

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Training set data for the models considering only unique SMILES strings as molecule inputs.

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Validation set data for SchNet-like models train on optimized 3D geometry.

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Validation set data for the models considering only unique SMILES strings as molecule inputs.

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Citation Formats

Computational Science. (2024). Organic Photovoltaic (OPV) Database [data set].  Retrieved from b5499938-55b7-4fd5-93a4-24cfb8911742.

Export Citation to RIS

St. John, . Organic Photovoltaic (OPV) Database. United States: N.p., 10 Apr, 2024. Web. b5499938-55b7-4fd5-93a4-24cfb8911742.

St. John, . Organic Photovoltaic (OPV) Database. United States. b5499938-55b7-4fd5-93a4-24cfb8911742

St. John, . 2024. "Organic Photovoltaic (OPV) Database". United States. b5499938-55b7-4fd5-93a4-24cfb8911742.

@div{oedi_6428, title = {Organic Photovoltaic (OPV) Database}, author = {St. John, .}, abstractNote = {A database of quantum mechanical calculations on organic photovoltaic candidate molecules.



Related Publications:

Peter C. St. John, Caleb Phillips, Travis W. Kemper, A. Nolan Wilson, Michael F. Crowley, Mark R. Nimlos, Ross E. Larsen. (2018) Message-passing neural networks for high-throughput polymer screening arXiv:1807.10363}, doi = {}, url = {b5499938-55b7-4fd5-93a4-24cfb8911742}, journal = {}, number = , volume = , place = {United States}, year = {2024}, month = {04}}

Details

Data from Apr 10, 2024

Last updated Dec 18, 2024

Submitted Apr 10, 2024

Organization

Computational Science

Contact

Peter St. John

Authors

St. John

NREL

Original Source

b5499938-55b7-4fd5-93a4-24cfb8911742

Research Areas

Computational Science Materials Science Solar Power

Keywords

OPV, organic photovoltaic

Organic Photovoltaic (OPV) Database

Citation Formats

Details

Organization

Contact

Authors

Original Source

Research Areas

Keywords

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