Abstract

Lithium thiophosphate (LPS) emerges as a promising solid electrolyte for the next-generation of lithium ion batteries. However, the high reactivity of LPS with common contaminants such as atmospheric water, solvents used for preparation, and common electrode materials hinders commercialization of the cells. The unknown structure, morphology, and chemical behavior of LPS ’s surface prevents strategic solutions to this problem. Here, we employ a machine learning interatomic potential to gain fundamental, atomistic understanding on the mechanical and chemical properties of an LPS surface in contact with water. Our focus lies first on the identification of relevant surface complexions formed by surface reconstructions, which differ greatly in properties from the bulk and define the form of the reactive sites. Metadynamics and nudged-elastic band simulations then reveal the complex reactivity of the LPS surface with water. This allows us to identify the surface moteties that play a relevant role in the material’s degradation.