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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...

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Detalhes bibliográficos
Publicado no:Nat Commun
Main Authors: Zhu, Qiang, Samanta, Amit, Li, Bingxi, Rudd, Robert E., Frolov, Timofey
Formato: Artigo
Idioma:Inglês
Publicado em: Nature Publishing Group UK 2018
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC5794988/
https://ncbi.nlm.nih.gov/pubmed/29391453
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41467-018-02937-2
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