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

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.