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Optimizing toughness in high entropy alloys using a genetic algorithm: A combined computational and experimental approach

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Autor(es):
Stoco, Caroline Binde ; Cassar, Daniel Roberto ; Santana, Geovana Lira ; Kaufman, Michael ; Clarke, Amy ; Coury, Francisco Gil
Número total de Autores: 6
Tipo de documento: Artigo Científico
Fonte: MATERIALS TODAY COMMUNICATIONS; v. 41, p. 9-pg., 2024-12-01.
Resumo

A genetic algorithm (GA) was developed to search for high entropy alloys (HEAs) with good combinations of mechanical properties. The algorithm was designed find single-phase face-centered cubic (FCC) HEAs, already known for their ductility, with high Hall-Petch constants (K) and high critical resolved shear stresses (tau Y). The objective was to develop a methodology that allows the design of HEAs in a multi-objective environment, focusing on alloys that exhibit enhanced ductility and strength, achieved through an increase in its yield point without significant loss of its ultimate deformation via adjustments of K and tau Y values, resulting in an alloy with high toughness. The most promising alloy suggested by the genetic algorithm was an unconventional composition (Co 32.73 Cu 15.11 Fe 0.72 Hf 0.72 Mn 35.97 Mo 3.96 Ni 10.43 Sn 0.36 ), with eight different elements in non-equiatomic ratios with maximized K and tau Y values. This alloy was then experimentally produced and characterized by scanning electron microscopy (SEM), synchrotron x-ray diffraction (XRD), transmission electron microscopy (TEM) and microhardness, with the objective of validating the predictions made by the GA. An advantage of the proposed method is the possibility of more systematically identifying and exploring new compositions in the complex composition space characteristic of these multicomponent alloys, as it directs its search towards domains that can be used to solve challenging problems involving multi-objective optimization. However, the thermodynamic parameters used for single-phase FCC prediction, namely the valence electron concentration (VEC) and the dimensionless thermodynamic parameter phi, exhibited limitations. These limitations were further explored in the present study, as evidenced by the fact that the microstructure of the selected alloy was not single-phase, which hindered the study of the mechanical properties, predicted exclusively for monophasic FCC alloys. Therefore, this work highlights the necessity for the development of novel thermodynamic equations for phase prediction, or even the integration of the genetic algorithm with other methodologies, such as CALPHAD calculations, to achieve enhanced results. (AU)

Processo FAPESP: 21/12044-9 - Produção de liga multicomponente com boas combinações de propriedades mecânicas selecionadas por algoritmo genético
Beneficiário:Caroline Binde Stoco
Modalidade de apoio: Bolsas no Brasil - Iniciação Científica
Processo FAPESP: 22/01327-2 - Caracterização por difração de raios X do equilíbrio de fases e distorção da rede de ligas multicomponente selecionadas por algoritmo genético
Beneficiário:Caroline Binde Stoco
Modalidade de apoio: Bolsas no Exterior - Estágio de Pesquisa - Iniciação Científica
Processo FAPESP: 23/04907-2 - Produção e Caracterização de HEAs de Alta Tenacidade por Algoritmo Genético
Beneficiário:Caroline Binde Stoco
Modalidade de apoio: Bolsas no Brasil - Mestrado
Processo FAPESP: 22/02770-7 - Engenharia de Materiais Computacional Integrada ICME: aplicada à modelagem, fabricação, teste e caracterização de ligas de alta entropia
Beneficiário:Francisco Gil Coury
Modalidade de apoio: Auxílio à Pesquisa - Projeto Inicial