Stacking fault energy prediction for austenitic steels: thermodynamic modeling vs. machine learning

Stacking fault energy (SFE) is of the most critical microstructure attribute for controlling the deformation mechanism and optimizing mechanical properties of austenitic steels, while there are no accurate and straightforward computational tools for modeling it. In this work, we applied both thermod...

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Detalles Bibliográficos
Autores principales: Wang, Xin, Xiong, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2020
Materias:
Engineering and Structural materials
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7534312/
https://www.ncbi.nlm.nih.gov/pubmed/33061835
http://dx.doi.org/10.1080/14686996.2020.1808433

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7534312/
https://www.ncbi.nlm.nih.gov/pubmed/33061835
http://dx.doi.org/10.1080/14686996.2020.1808433

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