Design Approaches of High‐Entropy Alloys Using Artificial Intelligence: A Review

Abstract

This review explores the complex process of designing high‐entropy alloys by combining theoretical guidelines, thermodynamic characteristics, and several modeling tools, including artificial intelligence approaches. It tackles issues in the design of high‐entropy alloys, emphasizing the wide composition range, difficulty in forecasting phase stability, and requirement for specialized production techniques. The investigation expands on strategies for creating high‐entropy alloys, emphasizing their benefits and limitations. This article discusses machine learning applications for predicting elastic characteristics, as well as the accompanying challenges and solutions. The future scenario predicts a collaborative world in which machine learning plays a critical role in the data‐driven alloy design of high‐entropy alloys, emphasizing ethical considerations and continual experimental validation for practical advances across industries.