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...

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Autores principales: Olexandr Isayev, Corey Oses, Cormac Toher, Eric Gossett, Stefano Curtarolo, Alexander Tropsha
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2017
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Acceso en línea:https://doaj.org/article/e51aabf9bad84fe6a8a7bf233cac04c5
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