Predicting materials properties without crystal structure: deep representation learning from stoichiometry
Predicting the structure of unknown materials’ compositions represents a challenge for high-throughput computational approaches. Here the authors introduce a new stoichiometry-based machine learning approach for predicting the properties of inorganic materials from their elemental compositions.
Guardado en:
Autores principales: | Rhys E. A. Goodall, Alpha A. Lee |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2020
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Materias: | |
Acceso en línea: | https://doaj.org/article/cb261c1294be401abf3c4d88070efdba |
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