Prediction and design of high hardness high entropy alloy through machine learning

[Display omitted] •Particle swarm algorithm is used to inversely optimize the alloy composition according to target performance.•An optimized feature set including 3 features is obtained by GA, interpretable ML and solid-solution strengthening.•A general design framework is summarized for prediction...

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Veröffentlicht in:	Materials & design Jg. 235; S. 112454
Hauptverfasser:	Ren, Wei, Zhang, Yi-Fan, Wang, Wei-Li, Ding, Shu-Jian, Li, Nan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.11.2023 Elsevier
Schlagworte:	High-entropy alloy Intelligent optimization algorithm Interpretable machine learning Machine learning Solid solution strengthening Interpretable machine learning Solid solution strengthening Intelligent optimization algorithm High-entropy alloy Machine learning
ISSN:	0264-1275, 1873-4197
Online-Zugang:	Volltext
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