Computational screening of anode coatings for garnet-type solid-state batteries

Abstract

Making use of a large materials database of DFT-derived structures and energies, we applied a high-throughput computational screening framework to identify Li-containing oxides as potential anode coatings for lithium garnet. A preselection of candidate materials was made based on their phase stability, electrochemical stability, and chemical stability, as emerging from this database. Then first-principles calculations (periodic DFT calculations at the PBE level) were performed to further evaluate the Li-ion conductivity and Li wettability of these coatings. A total of 10 Li-M-O compounds (Li3BO3, LiAlO2, Li5AlO4, Li4SiO4, Li8SiO6, Li4TiO4, Li8TiO6, Li6Zr2O7, Li2HfO3 and Li6Hf2O7) were identified as the most promising anode coatings. According to our findings, lithium concentration can affect the desired electrochemical stability and Li wettability in an opposing way. Compounds with high Li content tend to have low reduction potential with poor lithium wettability. Target materials may have a "sweet spot" in terms of Li content, where all key properties are balanced in an optimal way.