A machine-learned interatomic potential for silica and its relation to empirical models
Abstract Silica (SiO2) is an abundant material with a wide range of applications. Despite much progress, the atomistic modelling of the different forms of silica has remained a challenge. Here we show that by combining density-functional theory at the SCAN functional level with machine-learning-base...
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| Principais autores: | , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Nature Portfolio
2022-04-01
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| coleção: | npj Computational Materials |
| Acesso em linha: | https://doi.org/10.1038/s41524-022-00768-w |
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