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Deep neural networks for accurate predictions of crystal stability

Predicting the stability of crystals is one of the central problems in materials science. Today, density functional theory (DFT) calculations remain comparatively expensive and scale poorly with system size. Here we show that deep neural networks utilizing just two descriptors—the Pauling electroneg...

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Détails bibliographiques
Publié dans:Nat Commun
Auteurs principaux: Ye, Weike, Chen, Chi, Wang, Zhenbin, Chu, Iek-Heng, Ong, Shyue Ping
Format: Artigo
Langue:Inglês
Publié: Nature Publishing Group UK 2018
Sujets:
Accès en ligne:https://ncbi.nlm.nih.gov/pmc/articles/PMC6143552/
https://ncbi.nlm.nih.gov/pubmed/30228262
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41467-018-06322-x
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