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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Vydané v:	Materials today communications Ročník 47; s. 113102
Hlavní autori:	Román-Sedano, A. Monzamodeth, Aranda, V., Hernández-Mecinas, E., Espinosa-Rangel, S., Villalobos, J., Figueroa, I.A., González, G.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Ltd 01.07.2025
Predmet:	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
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