While alternative strategies such as doping, tailoring the particle morphology or core–shell structures have been suggested, a common approach to suppressing cathode degradation has been applying protective coatings on cathode particles. Stable binary oxides, such as Al2O3, MgO, ZnO, ZrO2, SiO2 and TiO2 may reduce the HF-content in the electrolyte, but their performance in suppressing the transition metal-loss from the cathode or the capacity fade can vary significantly. However, the complex nature of reactions between the cathode, coating and electrolyte prohibited the design of generic guidelines to find effective coatings beyond such simple binary oxides. Recently, we introduced a density functional theory (DFT)-based materials design approach considering the thermodynamic aspects of binary metal oxide cathode coatings, which reproduced the known effective coatings such as Al2O3, and predicted trivalent transition metal oxides as a promising class of under-explored cathode coatings. This framework was limited to only binary metal oxides, because the description of HF-reactivity and electrochemical stability of coatings were described by hypothesized reactions based on ‘chemical intuition’ (that is, reactions that had predefined forms) and could not be extended to other more complex materials.
In recent years, high-throughput (HT) computational methods have significantly accelerated the search for new and better battery components. Here we introduce a comprehensive HT materials design framework to discover cathode coatings by combining the Open Quantum Materials Database (OQMD), a large collection of HT DFT calculations of ~500,000 inorganic materials, with reaction models to describe thermodynamic stability, electrochemical stability and HF-reactivity for any oxygen-bearing coating with non-intuitive, fully automated prediction of reaction products. With this framework, we design coatings with various functionalities geared towards specific battery chemistries; namely, (1) physical barriers for acid-free electrolytes, (2) HF-barriers for cathode particles fully covered with coatings and (3) HF-scavengers for particles with patchy coatings requiring active protection from HF-attack. We screen more than 130,000 oxygen-bearing materials (oxides and oxyanion compounds) available in the OQMD, and use multiobjective optimization methods, namely weighted-sum and rank aggregation, to select the best candidates for several distinct coating categories based on desired function of the coating (HF scavenger, physical barrier, or HF barrier) . We further show that coatings optimized for a particular cathode material (here, for layered- LiCoO2 and spinel-LiMn2O4) can be designed by incorporating the cathode material itself into the chemical space; that is, considering the cathode-coating reactivity and including the cathode in all chemical reactions of the framework.
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.