Density of states prediction for materials discovery via contrastive learning from probabilistic embeddings

Machine learning for materials discovery has largely focused on predicting an individual scalar rather than multiple related properties, where spectral properties are an important example. Fundamental spectral properties include the phonon density of states (phDOS) and the electronic density of stat...

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Detalles Bibliográficos
Autores principales: Kong, Shufeng, Ricci, Francesco, Guevarra, Dan, Neaton, Jeffrey B., Gomes, Carla P., Gregoire, John M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8854636/
https://www.ncbi.nlm.nih.gov/pubmed/35177607
http://dx.doi.org/10.1038/s41467-022-28543-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8854636/
https://www.ncbi.nlm.nih.gov/pubmed/35177607
http://dx.doi.org/10.1038/s41467-022-28543-x

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