Performance of Exchange-Correlation Approximations to Density-Functional Theory for Rare-earth Oxides

TL;DR

This paper evaluates various exchange-correlation functionals within density-functional theory to improve the prediction of properties in rare-earth oxides, addressing challenges in modeling their strong electron correlation.

Contribution

It provides a comprehensive assessment of thirteen DFT functionals, including SCAN meta-GGA, for accurately predicting properties of rare-earth oxides, guiding functional selection.

Findings

SCAN meta-GGA improves property predictions over traditional functionals

Hubbard U corrections and spin-orbit coupling enhance accuracy

Guidelines for selecting optimal DFT functionals for REOs

Abstract

Rare-earth oxides (REOs) are an important class of materials owing to their unique properties, including high ionic conductivities, large dielectric constants, and elevated melting temperatures, making them relevant to several technological applications such as catalysis, ionic conduction, and sensing. The ability to predict these properties at moderate computational cost is essential to guiding materials discovery and optimizing materials performance. Although density-functional theory (DFT) is the favored approach for predicting electronic and atomic structures, its accuracy is limited in describing strong electron correlation and localization inherent to REOs. The newly developed strongly constrained and appropriately normed (SCAN) meta-generalized-gradient approximations (meta-GGAs) promise improved accuracy in modeling these strongly correlated systems. We assess the performance of these meta-GGAs on binary REOs by comparing the numerical accuracy of thirteen exchange-correlation approximations in predicting structural, magnetic, and electronic properties. Hubbard U corrections for self-interaction errors and spin-orbit coupling are systematically considered. Our comprehensive assessment offers insights into the physical properties and functional performance of REOs predicted by first-principles and provides valuable guidance for selecting optimal DFT functionals for exploring these materials.