High-throughput computational design of cathode coatings for Li-ion batteries

Abstract

Cathode degradation is a key factor that limits the lifetime of Li-ion batteries. To identify functional coatings that can suppress this degradation, we present a high-throughput density functional theory based framework which consists of reaction models that describe thermodynamic and electrochemical stabilities, and acid-scavenging capabilities of materials. Screening more than 130,000 oxygen-bearing materials, we suggest physical and hydrofluoric-acid barrier coatings such as WO₃, LiAl₅O₈ and ZrP₂O₇ and hydrofluoric-acid scavengers such as Sc₂O₃, Li₂CaGeO₄, LiBO₂, Li₃NbO₄, Mg₃(BO₃)₂ and Li₂MgSiO₄. Using a design strategy to find the thermodynamically optimal coatings for a cathode, we further present optimal hydrofluoric-acid scavengers such as Li₂SrSiO₄, Li₂CaSiO₄ and CaIn₂O₄ for the layered LiCoO₂, and Li₂GeO₃, Li₄NiTeO₆ and Li₂MnO₃ for the spinel LiMn₂O₄ cathodes. These coating materials have the potential to prolong the cycle-life of Li-ion batteries and surpass the performance of common coatings based on conventional materials such as Al₂O₃, ZnO, MgO or ZrO₂.