Predicting defect behavior in B2 intermetallics by merging ab initio modeling and machine learning
Machine learning a defect’s effect A method for quickly predicting the dominant equilibrium atomic-level defects in a material is developed by researchers in the USA. Crystalline materials derive many of their attributes from the regular and symmetric arrangement of their atoms. Consequently, a miss...
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| Autores principales: | , , , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2016
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/a32c20d9819043b39e1bf57b270fa447 |
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