Charting Lattice Thermal Conductivity For Inorganic Crystals And Discovering Rare Earth Chalcogenides For Thermoelectrics

Thermoelectric power generation represents a promising approach to utilize waste heat. The most effective thermoelectric materials exhibit low thermal conductivity kappa. However, less than 5% out of about 10(5) synthesized inorganic materials are documented with their kappa values, while for the remaining 95% kappa values are missing and challenging to predict. In this work, by combining graph neural networks and random forest approaches, we predict the thermal conductivity of all known inorganic materials in the Inorganic Crystal Structure Database, and chart the structural chemistry of kappa into extended van-Arkel triangles. Together with the newly developed kappa map and our theoretical tool, we identify rare-earth chalcogenides as promising candidates, of which we measured ZT exceeding 1.0. We note that the kappa chart can be further explored, and our computational and analytical tools are applicable generally for materials informatics.