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

Facile ionic mobility within host frameworks is crucial to the design of high-energy-density batteries with high-power-densities, where the migration barrier (E-m) 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 Hubbard U corrections, GGA+U and SCAN+U, within the density functional theory-nudged elastic band framework, in the prediction of E-m as 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 E-m predictions. Further, we quantify the sensitivity of E-m with adding uniform background charge and/or the climbing image approximation in solid electrolytes, and the Hubbard U correction in electrodes. Our findings will improve the quality of E-m predictions which will enable identifying better materials for energy storage applications.

Automated summary

This study evaluates the accuracy and computational performance of different methods in predicting ion migration barriers. It finds that the SCAN method is more accurate but computationally more expensive, while the GGA method is a feasible choice for quick and qualitative predictions. The study also investigates the sensitivity of the migration barriers to different factors.