Feature engineering descriptors, transforms, and machine learning for grain boundaries and variable-sized atom clusters
Abstract Obtaining microscopic structure-property relationships for grain boundaries is challenging due to their complex atomic structures. Recent efforts use machine learning to derive these relationships, but the way the atomic grain boundary structure is represented can have a significant impact...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-01-01
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| Series: | npj Computational Materials |
| Online Access: | https://doi.org/10.1038/s41524-024-01509-x |
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