Design and Synthesis of High Entropy Alloys

The selection of elements and their optimized concentration in the composition of HEAs is critical, as the microstructure and mechanical properties depend on it. Computational methods, such as CALPHAD, which use databases based on thermodynamics, kinetics, and phase stability, make the HEA design more focused. In this chapter, various computational methods that provide precise information on the thermal conductivity, electrical resistivity, and phase compositions along with the solidification behavior of HEAs are discussed. Moreover, the implementation of artificial intelligence and machine learning in HEA design has proven to be an effective way to predict material characteristics such as mechanical properties, stacking fault energies, and microstructures. Numerous fabrication routes for HEAs, such as casting (arc melting, Bridgman solidification) and additive manufacturing (selective laser melting, mechanical alloying, and wire arc additive manufacturing) have been explained.