Application of Machine Learning to Predict Grain Boundary Embrittlement in Metals by Combining Bonding-Breaking and Atomic Size Effects

The strengthening energy or embrittling potency of an alloying element is a fundamental energetics of the grain boundary (GB) embrittlement that control the mechanical properties of metallic materials. A data-driven machine learning approach has recently been used to develop prediction models to unc...

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Detalles Bibliográficos
Autores principales: Wu, Xuebang, Wang, Yu-xuan, He, Kan-ni, Li, Xiangyan, Liu, Wei, Zhang, Yange, Xu, Yichun, Liu, Changsong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6981756/
https://www.ncbi.nlm.nih.gov/pubmed/31906401
http://dx.doi.org/10.3390/ma13010179

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6981756/
https://www.ncbi.nlm.nih.gov/pubmed/31906401
http://dx.doi.org/10.3390/ma13010179

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