Radiation damage and phase stability of Al$_x$CrCuFeNi$_y$ alloys using a machine-learned interatomic potential
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arXiv
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| Auteurs principaux: | , , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866910015825117184 |
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| author | Fellman, Aslak Byggmästar, Jesper Granberg, Fredric Djurabekova, Flyura Nordlund, Kai |
| author_facet | Fellman, Aslak Byggmästar, Jesper Granberg, Fredric Djurabekova, Flyura Nordlund, Kai |
| contents | We develop a machine-learned interatomic potential for AlCrCuFeNi high-entropy alloys (HEA) using a diverse set of structures from density functional theory calculated including magnetic effects. The potential is based on the computationally efficient tabulated version of the Gaussian approximation potential method (tabGAP) and is a general-purpose model for molecular dynamics simulation of the HEA system, with additional emphasis on radiation damage effects. We use the potential to study key properties of AlCrCuFeNi HEAs at different compositions, focusing on the FCC/BCC phase stability. Monte Carlo swapping simulations are performed to understand the stability and segregation of the HEA and reveal clear FeCr and Cu segregation. Close to equiatomic composition, a transition from FCC to BCC is detected, following the valence electron concentration stability rule. Furthermore, we perform overlapping cascade simulations to investigate radiation damage production and tolerance. Different alloy compositions show significant differences in defect concentrations, and all alloy compositions show enrichment of some elements in or around defects. We find that, generally, a lower Al content corresponds to lower defect concentrations during irradiation. Furthermore, clear short-range ordering is observed as a consequence of continued irradiation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_07344 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Radiation damage and phase stability of Al$_x$CrCuFeNi$_y$ alloys using a machine-learned interatomic potential Fellman, Aslak Byggmästar, Jesper Granberg, Fredric Djurabekova, Flyura Nordlund, Kai Materials Science We develop a machine-learned interatomic potential for AlCrCuFeNi high-entropy alloys (HEA) using a diverse set of structures from density functional theory calculated including magnetic effects. The potential is based on the computationally efficient tabulated version of the Gaussian approximation potential method (tabGAP) and is a general-purpose model for molecular dynamics simulation of the HEA system, with additional emphasis on radiation damage effects. We use the potential to study key properties of AlCrCuFeNi HEAs at different compositions, focusing on the FCC/BCC phase stability. Monte Carlo swapping simulations are performed to understand the stability and segregation of the HEA and reveal clear FeCr and Cu segregation. Close to equiatomic composition, a transition from FCC to BCC is detected, following the valence electron concentration stability rule. Furthermore, we perform overlapping cascade simulations to investigate radiation damage production and tolerance. Different alloy compositions show significant differences in defect concentrations, and all alloy compositions show enrichment of some elements in or around defects. We find that, generally, a lower Al content corresponds to lower defect concentrations during irradiation. Furthermore, clear short-range ordering is observed as a consequence of continued irradiation. |
| title | Radiation damage and phase stability of Al$_x$CrCuFeNi$_y$ alloys using a machine-learned interatomic potential |
| topic | Materials Science |
| url | https://arxiv.org/abs/2503.07344 |