Automated atomistic simulations of dissociated dislocations with ab initio accuracy
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arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2023
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| _version_ | 1866911815341965312 |
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| author | Mismetti, Laura Hodapp, Max |
| author_facet | Mismetti, Laura Hodapp, Max |
| contents | In (M Hodapp and A Shapeev 2020 Mach. Learn.: Sci. Technol. 1 045005), we have proposed an algorithm that fully automatically trains machine-learning interatomic potentials (MLIPs) during large-scale simulations, and successfully applied it to simulate screw dislocation motion in body-centered cubic tungsten. The algorithm identifies local subregions of the large-scale simulation region where the potential extrapolates, and then constructs periodic configurations of 100--200 atoms out of these non-periodic subregions that can be efficiently computed with plane-wave Density Functional Theory (DFT) codes.
In this work, we extend this algorithm to dissociated dislocations with arbitrary character angles and apply it to partial dislocations in face-centered cubic aluminum. Given the excellent agreement with available DFT reference results, we argue that our algorithm has the potential to become a universal way of simulating dissociated dislocations in face-centered cubic and possibly also other materials, such as hexagonal closed-packed magnesium, and their alloys. Moreover, it can be used to construct reliable training sets for MLIPs to be used in large-scale simulations of curved dislocations. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2311_01830 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Automated atomistic simulations of dissociated dislocations with ab initio accuracy Mismetti, Laura Hodapp, Max Computational Physics Materials Science In (M Hodapp and A Shapeev 2020 Mach. Learn.: Sci. Technol. 1 045005), we have proposed an algorithm that fully automatically trains machine-learning interatomic potentials (MLIPs) during large-scale simulations, and successfully applied it to simulate screw dislocation motion in body-centered cubic tungsten. The algorithm identifies local subregions of the large-scale simulation region where the potential extrapolates, and then constructs periodic configurations of 100--200 atoms out of these non-periodic subregions that can be efficiently computed with plane-wave Density Functional Theory (DFT) codes. In this work, we extend this algorithm to dissociated dislocations with arbitrary character angles and apply it to partial dislocations in face-centered cubic aluminum. Given the excellent agreement with available DFT reference results, we argue that our algorithm has the potential to become a universal way of simulating dissociated dislocations in face-centered cubic and possibly also other materials, such as hexagonal closed-packed magnesium, and their alloys. Moreover, it can be used to construct reliable training sets for MLIPs to be used in large-scale simulations of curved dislocations. |
| title | Automated atomistic simulations of dissociated dislocations with ab initio accuracy |
| topic | Computational Physics Materials Science |
| url | https://arxiv.org/abs/2311.01830 |