Optimization of Coulomb Energies in Gigantic Configurational Spaces of Multi-Element Ionic Crystals
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arXiv
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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| _version_ | 1866911035599880192 |
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| author | Köster, Konstantin Binninger, Tobias Kaghazchi, Payam |
| author_facet | Köster, Konstantin Binninger, Tobias Kaghazchi, Payam |
| contents | Most of the novel energy materials contain multiple elements occupying a single site in their lattice. The exceedingly large configurational space of these materials imposes challenges in determining their ground-state structures. Coulomb energies of possible configurations generally show a satisfactory correlation to computed energies at higher levels of theory and thus allow to screen for minimum-energy structures. Employing a second-order cluster expansion, we obtain an efficient Coulomb energy optimizer using Monte Carlo and Genetic Algorithms. The presented optimization package, GOAC (Global Optimization of Atomistic Configurations by Coulomb), can achieve a speed up of several orders of magnitude compared to existing software. Our code is able to find low-energy configurations of complex systems involving up to $10^{920}$ structural configurations. The GOAC package thus provides an efficient method for constructing ground-state atomistic models for multi-element materials with gigantic configurational spaces. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_08808 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Optimization of Coulomb Energies in Gigantic Configurational Spaces of Multi-Element Ionic Crystals Köster, Konstantin Binninger, Tobias Kaghazchi, Payam Materials Science Computational Physics Most of the novel energy materials contain multiple elements occupying a single site in their lattice. The exceedingly large configurational space of these materials imposes challenges in determining their ground-state structures. Coulomb energies of possible configurations generally show a satisfactory correlation to computed energies at higher levels of theory and thus allow to screen for minimum-energy structures. Employing a second-order cluster expansion, we obtain an efficient Coulomb energy optimizer using Monte Carlo and Genetic Algorithms. The presented optimization package, GOAC (Global Optimization of Atomistic Configurations by Coulomb), can achieve a speed up of several orders of magnitude compared to existing software. Our code is able to find low-energy configurations of complex systems involving up to $10^{920}$ structural configurations. The GOAC package thus provides an efficient method for constructing ground-state atomistic models for multi-element materials with gigantic configurational spaces. |
| title | Optimization of Coulomb Energies in Gigantic Configurational Spaces of Multi-Element Ionic Crystals |
| topic | Materials Science Computational Physics |
| url | https://arxiv.org/abs/2409.08808 |