The LDA+DMFT route to identify good thermoelectrics

TL;DR

This paper discusses using the combined LDA+DMFT computational approach to identify and understand promising thermoelectric materials with high figures of merit, focusing on strongly correlated electron systems.

Contribution

It introduces the LDA+DMFT method for thermoelectric material design and reviews recent findings on LiRh₂O₄, highlighting the role of electronic correlations.

Findings

LDA+DMFT effectively predicts thermoelectric properties.

LiRh₂O₄ shows promising thermoelectric performance.

Electronic correlations are crucial for high figure of merit.

Abstract

For technical applications thermoelectric materials with a high figure of merit are desirable, and strongly correlated electron systems are very promising in this respect. Since effects of bandstructure_and_ electronic correlations play an important role for getting large figure of merits, the combination of local density approximation_and_ dynamical mean field theory is an ideal tool for the computational materials design of new thermoelectrics as well as to help us understand the mechanisms leading to large figures of merits in certain materials. This conference proceedings provides for a brief introduction to the method and reviews recent results for LiRh_2O_4.