Predicting accurate cathode properties of layered oxide materials using the SCAN meta-GGA density functional

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Abstract

Layered lithium intercalating transition metal oxides are promising cathode materials for Li-ion batteries. Here, we scrutinize the recently developed strongly constrained and appropriately normed (SCAN) density functional method to study structural, magnetic, and electrochemical properties of prototype cathode materials LiNiO2, LiCoO2, and LiMnO2 at different Li-intercalation limits. We show that SCAN outperforms earlier popular functional combinations, providing results in considerably better agreement with experiment without the use of Hubbard parameters, and dispersion corrections are found to have a small effect. In particular, SCAN fares better than Perdew–Burke–Ernzerhof (PBE) functional for the prediction of band-gaps and absolute voltages, better than PBE+U for the electronic density of states and voltage profiles, and better than both PBE and PBE+U for electron densities and in operando lattice parameters. This overall better performance of SCAN may be ascribed to improved treatment of localized states and a better description of short-range dispersion interactions.

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Chakraborty, A., Dixit, M., Aurbach, D., & Major, D. T. (2018). Predicting accurate cathode properties of layered oxide materials using the SCAN meta-GGA density functional. Npj Computational Materials, 4(1). https://doi.org/10.1038/s41524-018-0117-4

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