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...
Uloženo v:
| Hlavní autoři: | , , , |
|---|---|
| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
Nature Portfolio
2022-04-01
|
| Edice: | npj Computational Materials |
| On-line přístup: | https://doi.org/10.1038/s41524-022-00768-w |
| Tagy: |
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
|