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Material symmetry recognition and property prediction accomplished by crystal capsule representation
Learning the global crystal symmetry and interpreting the equivariant information is crucial for accurately predicting material properties, yet remains to be fully accomplished by existing algorithms based on convolution networks. To overcome this challenge, here we develop a machine learning (ML) m...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10457372/ https://www.ncbi.nlm.nih.gov/pubmed/37626032 http://dx.doi.org/10.1038/s41467-023-40756-2 |