Effect of exchange-correlation functionals on the estimation of migration barriers in battery materials

Abstract

AbstractFacile ionic mobility within host frameworks is crucial to the design of high-energy-density batteries with high-power-densities, where the migration barrier (Em) is the governing factor. Here, we assess the accuracy and computational performance of generalized gradient approximation (GGA), the strongly constrained and appropriately normed (SCAN), and their HubbardUcorrections, GGA+Uand SCAN+U, within the density functional theory-nudged elastic band framework, in the prediction of Emas benchmarked against experimental data. Importantly, we observe SCAN to be more accurate than other frameworks, on average, albeit with higher computational costs and convergence difficulties, while GGA is a feasible choice for “quick” and “qualitative” Empredictions. Further, we quantify the sensitivity of Emwith adding uniform background charge and/or the climbing image approximation in solid electrolytes, and the HubbardUcorrection in electrodes. Our findings will improve the quality of Empredictions which will enable identifying better materials for energy storage applications.