Low-temperature transport in high-conductivity correlated metals: a density-functional plus dynamical mean-field study of cubic perovskites

TL;DR

This study employs advanced DFT+DMFT techniques to accurately analyze electron-electron scattering effects on low-temperature transport in high-conductivity cubic perovskite oxides, revealing insights into correlated metal behavior.

Contribution

It introduces a robust DFT+DMFT methodology with adaptive integration and precise self-energies for analyzing low-temperature transport in correlated metals.

Findings

Successfully describes electron-electron contributions to resistivity in perovskites.

Provides a predictive framework for transport properties in correlated materials.

Enhances understanding of electronic correlations in high-conductivity oxides.

Abstract

While methods based on density-functional perturbation theory have dramatically improved our understanding of electron-phonon contributions to transport in materials, methods for accurately capturing electron-electron scattering relevant to low temperatures have seen significantly less development. The case of high-conductivity, moderately correlated materials characterized by low scattering rates is particularly challenging, since exquisite numerical precision of the low-energy electronic structure is required. Recent methodological advancements to density-functional theory combined with dynamical mean-field theory (DFT+DMFT), including adaptive Brillouin-zone integration and numerically precise self-energies, enable a rigorous investigation of electron-electron scattering in such materials. In particular, these tools may be leveraged to perform a robust scattering-rate analysis on both real- and imaginary-frequency axes. Applying this methodology to a subset of ABO$_3$ perovskite oxides -- SrVO$_3$, SrMoO$_3$, PbMoO$_3$, and SrRuO$_3$ -- we demonstrate its ability to qualitatively and quantitatively describe electron-electron contributions to the temperature-dependent direct-current resistivity. This combination of numerical techniques offers fundamental insight into the role of electronic correlations in transport phenomena and provides a predictive tool for identifying materials with potential for technological applications.