Universal fragment descriptors for predicting properties of inorganic crystals
Machine learning methods can be useful for materials discovery; however certain properties remain difficult to predict. Here, the authors present a universal machine learning approach for modelling the properties of inorganic crystals, which is validated for eight electronic and thermomechanical pro...
Guardado en:
Autores principales: | Olexandr Isayev, Corey Oses, Cormac Toher, Eric Gossett, Stefano Curtarolo, Alexander Tropsha |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2017
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Materias: | |
Acceso en línea: | https://doaj.org/article/e51aabf9bad84fe6a8a7bf233cac04c5 |
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