High-Throughput Computational Screening of thermal conductivity, Debye temperature and Gr'uneisen parameter using a quasi-harmonic Debye Model

摘要

The quasi-harmonic Debye approximation has been implemented within the AFLOWand Materials Project frameworks for high-throughput computational science(Automatic Gibbs Library, AGL), in order to calculate thermal properties suchas the Debye temperature and the thermal conductivity of materials. Wedemonstrate that the AGL method, which is significantly cheaper computationallycompared to the fully ab initio approach, can reliably predict the ordinalranking of the thermal conductivity for several different classes ofsemiconductor materials. We also find that for the set of 182 materialsinvestigated in this work the Debye temperature, calculated with the AGL, isoften a better predictor of the ordinal ranking of the experimental thermalconductivities than the calculated thermal conductivity. The Debye temperatureis thus a potential descriptor for high-throughput screening of the thermalproperties of materials.