Machine learning potential assisted exploration of complex defect potential energy surfaces
Abstract Atomic-scale defects generated in materials under both equilibrium and irradiation conditions can significantly impact their physical and mechanical properties. Unraveling the energetically most favorable ground-state configurations of these defects is an important step towards the fundamen...
| Hlavní autoři: | , , , |
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| Médium: | Článek |
| Jazyk: | English |
| Vydáno: |
Nature Portfolio
2024-01-01
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| Edice: | npj Computational Materials |
| On-line přístup: | https://doi.org/10.1038/s41524-024-01207-8 |