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