A systematic approach to generating accurate neural network potentials: the case of carbon
Abstract Availability of affordable and widely applicable interatomic potentials is the key needed to unlock the riches of modern materials modeling. Artificial neural network-based approaches for generating potentials are promising; however, neural network training requires large amounts of data, s...
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Autores principales: | Yusuf Shaidu, Emine Küçükbenli, Ruggero Lot, Franco Pellegrini, Efthimios Kaxiras, Stefano de Gironcoli |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
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Materias: | |
Acceso en línea: | https://doaj.org/article/3615bdf517374055a6e295aa00227d24 |
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