| Full text | |
| Author(s): |
Stoco, Caroline Binde
;
Cassar, Daniel Roberto
;
Santana, Geovana Lira
;
Kaufman, Michael
;
Clarke, Amy
;
Coury, Francisco Gil
Total Authors: 6
|
| Document type: | Journal article |
| Source: | MATERIALS TODAY COMMUNICATIONS; v. 41, p. 9-pg., 2024-12-01. |
| Abstract | |
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) | |
| FAPESP's process: | 21/12044-9 - Production of a multicomponent alloy with good combinations of mechanical properties selected by a genetic algorithm |
| Grantee: | Caroline Binde Stoco |
| Support Opportunities: | Scholarships in Brazil - Scientific Initiation |
| FAPESP's process: | 22/01327-2 - Phase equilibria and lattice distortion X-ray diffraction characterization of multicomponent alloys selected by a genetic algorithm |
| Grantee: | Caroline Binde Stoco |
| Support Opportunities: | Scholarships abroad - Research Internship - Scientific Initiation |
| FAPESP's process: | 23/04907-2 - Production and Characterization of High Toughness HEAs by Genetic Algorithm |
| Grantee: | Caroline Binde Stoco |
| Support Opportunities: | Scholarships in Brazil - Master |
| FAPESP's process: | 22/02770-7 - Integrated Computational Materials Engineering ICME: applied to modeling, production, characterization and testing high entropy alloys |
| Grantee: | Francisco Gil Coury |
| Support Opportunities: | Research Grants - Initial Project |