Application of Materials Genome Methods in Thermoelectrics - Cao, Yan; Sheng, Ye; Li, Xin; Xi, Lili; Yang, Jiong (Frontiers in Materials, 2022)
Materials genome methods have played an essential role in accelerating the discovery of high-performance novel materials, and include high-throughput calculation, database construction, and machine learning. Over the past decades, these approaches have been increasingly used in lithium battery materials, solar cells, transparent conductors, and thermoelectrics. Thermoelectrics are functional materials that can directly convert electricity into heat and vice versa, offering new ideas for conventional power generation and refrigeration. The application of high-throughput methods can achieve more efficient screening of new thermoelectric materials and accelerate experimental development. This review summarizes the recent progress in the application of materials genome methods for different thermoelectric materials, such as half-Heuslers, diamond-like structures, oxides, and other materials. Finally, current advances in machine learning for thermoelectrics are discussed. The progress of the theoretical design of thermoelectrics has driven the development of high-performance thermoelectrics.