Density of States Prediction for Materials Discovery via Contrastive Learning from Probabilistic Embeddings

Creators: Gregoire, John M¹; Kong, Shufeng²; Ricci, Francesco³; Guevarra, Dan¹; Neaton, Jeffrey B.³; Gomes, Carla P²

1. California Institute of Technology
2. Cornell University
3. Lawrence Berkeley National Laboratory

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Gregoire, J. M., Kong, S., Ricci, F., Guevarra, D., Neaton, J. B., & Gomes, C. P. (2022). Density of States Prediction for Materials Discovery via Contrastive Learning from Probabilistic Embeddings (1.0) [Data set]. CaltechDATA. https://doi.org/10.22002/D1.8975

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Data related to the publication are provided as a single .zip that contains ascii, .csv, and .json files as well as .pkl, .npy, and .chkpt files referenced in the code repository available at TBD

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Mat2Spec_DATA.zip

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Mat2Spec_DATA.zip md5:11cc35a21f7d10f5f9862f7f6787b411	241.6 MB	Preview Download

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Related Publication: Density of states prediction for materials discovery via contrastive learning from probabilistic embeddings Nature Communications 2022-02-17 https://doi.org/10.1038/s41467-022-28543-x eng

Density of States Prediction for Materials Discovery via Contrastive Learning from Probabilistic Embeddings

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