Effect of fabrication techniques of high entropy alloys: A review with integration of machine learning

High Entropy Alloys (HEAs) are an emerging class of materials distinguished by equimolar or near-equimolar compositions of five or more principal elements. HEAs display exceptional mechanical properties, thermal stability, and wear resistance, making them suitable for advanced aerospace, biomedical, and automotive engineering applications. This review thoroughly explores various fabrication techniques for HEAs, including Vacuum Arc Melting (VAM), Hot Compression (HC), Laser Cladding (LC), and Spark Plasma Sintering (SPS). Each method's advantages, limitations, and impacts on microstructural properties are discussed in detail. Additionally, the integration of Machine Learning (ML) techniques in HEA research is highlighted, demonstrating their potential for optimizing fabrication parameters and predicting phase stability, microstructure evolution, and mechanical properties. The review concludes by identifying challenges in HEA fabrication, such as data availability and sustainability, and proposes future research directions to address these gaps. This work aims to provide researchers and engineers with a consolidated resource for advancing the development and application of HEAs.