Accelerated computational design of BCC refractory high entropy alloys using metaheuristics, CALPHAD, and artificial neural networks

Refractory high-entropy alloys are a novel class of materials for diverse fields. Their design has been enhanced by several empirical models, thermodynamic calculation methods, and artificial intelligence techniques, allowing continuous advancements in the search for specific properties. In this stu...

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Veröffentlicht in:	Materials today communications Jg. 47; S. 113102
Hauptverfasser:	Román-Sedano, A. Monzamodeth, Aranda, V., Hernández-Mecinas, E., Espinosa-Rangel, S., Villalobos, J., Figueroa, I.A., González, G.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.07.2025
Schlagworte:	Artificial neural networks Calphad method Mechanical properties Metaheuristics algorithms Microstructure Refractory high entropy alloys Refractory high entropy alloys Mechanical properties Metaheuristics algorithms Microstructure Artificial neural networks Calphad method
ISSN:	2352-4928, 2352-4928
Online-Zugang:	Volltext
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