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Predicting phase behavior of grain boundaries with evolutionary search and machine learning
The study of grain boundary phase transitions is an emerging field until recently dominated by experiments. The major bottleneck in the exploration of this phenomenon with atomistic modeling has been the lack of a robust computational tool that can predict interface structure. Here we develop a comp...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2018
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5794988/ https://www.ncbi.nlm.nih.gov/pubmed/29391453 http://dx.doi.org/10.1038/s41467-018-02937-2 |