Phase Prediction of High-Entropy Alloys by Integrating Criterion and Machine Learning Recommendation Method

The comprehensive properties of high-entropy alloys (HEAs) are highly-dependent on their phases. Although a large number of machine learning (ML) algorithms has been successfully applied to the phase prediction of HEAs, the accuracies among different ML algorithms based on the same dataset vary sign...

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Detalles Bibliográficos
Autores principales: Hou, Shuai, Li, Yujiao, Bai, Meijuan, Sun, Mengyue, Liu, Weiwei, Wang, Chao, Tetik, Halil, Lin, Dong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9105637/
https://www.ncbi.nlm.nih.gov/pubmed/35591654
http://dx.doi.org/10.3390/ma15093321

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9105637/
https://www.ncbi.nlm.nih.gov/pubmed/35591654
http://dx.doi.org/10.3390/ma15093321

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