Computational discovery of semiconducting high-entropy chalcogenide alloys

High-entropy materials are formed by mixing typically five or more principal components into a single crystal structure. While significant progress has been made to synthesize entropy-stabilized metals and ceramics for structural applications, little attention has been paid to the discovery of new entropy-stabilized semiconductors. Here, we present a new class of entropy-stabilized semiconducting alloys based on the IV-VI binary chalcogenides, namely Ge_xSn_yPb_1–x–yS_zSe_tTe_1–z–t high-entropy chalcogenides (HECs). By utilizing high-throughput first-principles calculations, we investigate the thermodynamic stability of HECs over their entire composition space, and show that more than 50% of the investigated compositions are stable with respect to phase segregation. We further studied the enthalpic effect of the individual elements via machine learning on the high-throughput data. Our work demonstrates the potential of entropy stabilization in the discovery of novel multicomponent semiconductor alloys.