Computation-Driven Materials Search for Thermoelectric Applications

Abstract

© The Author(s) 2017. Published by ECS. All rights reserved. The advancement of computational tools for material property predictions enables broad search of novel materials for various energy-related applications. However, challenges still exist in accurately predicting the mean free paths of electrons and phonons in a high throughput frame for thermoelectric property predictions, which largely hinders the computation-driven material search for novel materials. In this work, this need is eliminated under the small-grain-size limit, in which these mean free paths are restricted by the grain sizes within a bulk material. A new criterion for ZT evaluation is proposed for general nanograined bulk materials and is demonstrated with representative oxides.