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

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