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...
| Published in: | npj Computational Materials |
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| Main Authors: | , , , |
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2022-04-01
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| Online Access: | https://doi.org/10.1038/s41524-022-00768-w |