The transformative capability of quantum-accurate machine learning interatomic potentials
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arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866912410924744704 |
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| author | Correa, Alfredo A. Hamel, Sebastien |
| author_facet | Correa, Alfredo A. Hamel, Sebastien |
| contents | Many materials's properties and phase boundaries are generally not well known under extreme pressure and temperature conditions. This is a consequence of the scarcity of experimental information and the difficulty of extrapolating approximations to the atomic interactions in such conditions. Nguyen-Cong and colleagues, in their publication (J.Phys.Chem.Lett. 15, 1152 (2024)), achieved an impressive result using a SNAP (Spectral Neighbor Analysis Potential), an interatomic potential for carbon obtained by machine learning techniques. In a way, their contribution closes a full circle of research that spanned more than three decades. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_02328 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | The transformative capability of quantum-accurate machine learning interatomic potentials Correa, Alfredo A. Hamel, Sebastien Computational Physics Many materials's properties and phase boundaries are generally not well known under extreme pressure and temperature conditions. This is a consequence of the scarcity of experimental information and the difficulty of extrapolating approximations to the atomic interactions in such conditions. Nguyen-Cong and colleagues, in their publication (J.Phys.Chem.Lett. 15, 1152 (2024)), achieved an impressive result using a SNAP (Spectral Neighbor Analysis Potential), an interatomic potential for carbon obtained by machine learning techniques. In a way, their contribution closes a full circle of research that spanned more than three decades. |
| title | The transformative capability of quantum-accurate machine learning interatomic potentials |
| topic | Computational Physics |
| url | https://arxiv.org/abs/2506.02328 |