Crystal Structure Generation Based on Polyhedra using Dual Periodic Graphs
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arXiv
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| Auteurs principaux: | , , |
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| Format: | Preprint |
| Publié: |
2023
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| _version_ | 1866909092315922432 |
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| author | Yokoyama, Tomoyasu Ichikawa, Kazuhide Naito, Hisashi |
| author_facet | Yokoyama, Tomoyasu Ichikawa, Kazuhide Naito, Hisashi |
| contents | Crystal structure design is important for the discovery of new highly functional materials because crystal structure strongly influences material properties. Crystal structures are composed of space-filling polyhedra, which affect material properties such as ionic conductivity and dielectric constant. However, most conventional methods of crystal structure prediction use random structure generation methods that do not take space-filling polyhedra into account, contributing to the inefficiency of materials development. In this work, we propose a crystal structure generation method based on discrete geometric analysis of polyhedra information. In our method, the shape and connectivity of a space-filling polyhedron are represented as a dual periodic graph, and the crystal structure is generated by the standard realization of this graph. We demonstrate that this method can correctly generate face-centered cubic, hexagonal close-packed, and body-centered cubic structures from dual periodic graphs. This work is a first step toward generating undiscovered crystal structures based on the target polyhedra, leading to major advances in materials design in areas including electronics and energy storage. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2312_09060 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Crystal Structure Generation Based on Polyhedra using Dual Periodic Graphs Yokoyama, Tomoyasu Ichikawa, Kazuhide Naito, Hisashi Materials Science Computational Physics Crystal structure design is important for the discovery of new highly functional materials because crystal structure strongly influences material properties. Crystal structures are composed of space-filling polyhedra, which affect material properties such as ionic conductivity and dielectric constant. However, most conventional methods of crystal structure prediction use random structure generation methods that do not take space-filling polyhedra into account, contributing to the inefficiency of materials development. In this work, we propose a crystal structure generation method based on discrete geometric analysis of polyhedra information. In our method, the shape and connectivity of a space-filling polyhedron are represented as a dual periodic graph, and the crystal structure is generated by the standard realization of this graph. We demonstrate that this method can correctly generate face-centered cubic, hexagonal close-packed, and body-centered cubic structures from dual periodic graphs. This work is a first step toward generating undiscovered crystal structures based on the target polyhedra, leading to major advances in materials design in areas including electronics and energy storage. |
| title | Crystal Structure Generation Based on Polyhedra using Dual Periodic Graphs |
| topic | Materials Science Computational Physics |
| url | https://arxiv.org/abs/2312.09060 |