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

摘要

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.