High-Entropy Alloys for Extreme Environments: Processing, Microstructure Control, and Property Prediction
Keywords:
High-entropy alloys, extreme environments, additive manufacturing, microstructure control, predictive modeling, phase stability, corrosion resistance, machine learning, CALPHADAbstract
This study aims to systematically review and synthesize current research on high-entropy alloys (HEAs) designed for extreme environments, focusing on how processing strategies, microstructural engineering, and predictive modeling collectively influence their performance under severe service conditions. A qualitative literature review approach was employed, involving thematic analysis of twelve peer-reviewed articles published between 2015 and 2025. The articles were selected based on theoretical saturation from databases such as Scopus, Web of Science, and ScienceDirect, using targeted search terms related to HEA processing, microstructure, and predictive modeling. Only studies directly addressing HEAs in extreme thermal, corrosive, or irradiated environments were included. Data were analyzed using NVivo 14 software, with a three-phase coding process—open, axial, and selective coding—leading to identification of three core themes and associated subthemes. Three main themes emerged: (1) processing strategies such as additive manufacturing, mechanical alloying, thermomechanical treatments, and surface engineering significantly influence defect control, grain refinement, and phase homogeneity; (2) microstructural control—including phase stability, precipitation hardening, diffusion behavior, and radiation resistance—determines long-term performance in extreme environments; and (3) property prediction through machine learning, CALPHAD thermodynamic modeling, and multiscale simulations enables accelerated design and optimization of HEAs, though challenges remain in model validation and generalizability. The review underscores the interdependence of processing, structure, and modeling in achieving robust HEA performance. An integrated approach to HEA development—combining advanced processing techniques, microstructural tailoring, and reliable performance prediction—is essential for creating next-generation materials capable of withstanding extreme operational environments. Future research should emphasize long-term multistressor validation and data-driven modeling with interpretability to bridge the gap between experimental design and predictive reliability.
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