Design methods of high-entropy alloys: Current status and prospects

High-entropy alloys (HEAs), with their outstanding comprehensive properties, hold significant potential for applications in aerospace, energy, and military fields. However, due to the vast compositional space of HEAs, the traditional trial-and-error approach not only consumes considerable resources but also suffers from low efficiency, severely hindering the development of these alloys. In recent years, the rapid advancements in highthroughput experiments, computational materials science, and machine learning have offered new opportunities for the design of HEAs. This paper aims to explore the design methods for HEAs, including those based on high-throughput experiments, computational materials science, materials science, and machine learning. It discusses the current state of research on these four design methods, analyzing the advantages and limitations of each. Finally, the paper addresses the future trends in the development of design methods for HEAs.