Melting line of silicon modelled with a machine-learning potential
Fuente:
arXiv
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866918178865545216 |
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| author | Fomin, Yu. D. |
| author_facet | Fomin, Yu. D. |
| contents | In the present study we investigate the phase diagram of silicon within the framework of SNAP machine learning potential model. We show that the melting line of diamond phase of silicon is a linear function of pressure, which is in good agreement with experimental data. At the same time the melting temperature is strongly underestimated. Also, this model fails to predict the high pressure phases of silicon. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_26214 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Melting line of silicon modelled with a machine-learning potential Fomin, Yu. D. Soft Condensed Matter In the present study we investigate the phase diagram of silicon within the framework of SNAP machine learning potential model. We show that the melting line of diamond phase of silicon is a linear function of pressure, which is in good agreement with experimental data. At the same time the melting temperature is strongly underestimated. Also, this model fails to predict the high pressure phases of silicon. |
| title | Melting line of silicon modelled with a machine-learning potential |
| topic | Soft Condensed Matter |
| url | https://arxiv.org/abs/2510.26214 |