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Predicting materials properties without crystal structure: deep representation learning from stoichiometry
Machine learning has the potential to accelerate materials discovery by accurately predicting materials properties at a low computational cost. However, the model inputs remain a key stumbling block. Current methods typically use descriptors constructed from knowledge of either the full crystal stru...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Nature Publishing Group UK
2020
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7722901/ https://www.ncbi.nlm.nih.gov/pubmed/33293567 http://dx.doi.org/10.1038/s41467-020-19964-7 |