Recent progress in computational discovery of Heusler alloys

Abstract Heusler alloy is an intermetallic alloy with a wide range of compositional space. Due to this compositional tunability, novel Heusler alloys have been studied for a variety of applications including permanent magnets, thermoelectric, and catalysis. Recently, computational approaches have been actively used to aid the fast discovery of novel Heusler alloys by identifying stable compositions with desired properties. In this mini‐review, we briefly overview several computational approaches used for Heusler alloys, namely, density functional theory (DFT) calculations, high‐throughput virtual screening (HTVS), and machine learning (ML) to further accelerate these screening processes. Future directions for the computational screening of Heusler alloy in other application fields are discussed.