Insights into Lithium Sulfide Glass Electrolyte Structures and Ionic Conductivity via Machine Learning Force Field Simulations

Abstract

Sulfide-based solid electrolytes (SEs) are important for advancing all-solid-state batteries (ASSBs), primarily due to their high ionic conductivities and robust mechanical stability. Glassy SEs (GSEs) comprising mixed Si and P glass formers are particularly promising for their synthesis process and their ability to prevent lithium dendrite growth. However, to date, the complexity of their glassy structures hinders a complete understanding of the relationships between their structures and properties. This study introduces a new machine learning force field (ML-FF) tailored for lithium sulfide-based GSEs, enabling the exploration of their structural characteristics, mechanical properties, and lithium ionic conductivities. Using molecular dynamic (MD) simulations with this ML-FF, we explore the glass structures in varying compositions, including binary Li 2 S−SiS 2 and Li 2 S− P 2 S 5 as well as ternary Li 2 S−SiS 2 −P 2 S 5 . Our simulations yielded consistent results in terms of density, elastic modulus, radial distribution functions, and neutron structure factors compared to DFT and experimental work. Our findings reveal distinct local environments for Si and P within these glasses, with most Si atoms in edge-sharing configurations in Li 2 S−SiS 2 and a mix of cornerand edge-sharing tetrahedra in the ternary Li 2 S−SiS 2 −P 2 S 5 composition. For lithium ionic conductivity at 300 K, the 50Li 2 S−50SiS 2 glass displayed the lowest conductivity at 2.1 mS/cm, while the 75Li 2 S−25P 2 S 5 composition exhibited the highest conductivity at 3.6 mS/cm. The ternary glass showed a conductivity of 2.6 mS/cm, sitting between the two. Moreover, an in-depth analysis of lithium ion diffusion over the MD trajectory in the ternary glass demonstrated a significant correlation between diffusion pathways and the rotational dynamics of nearby SiS 4 or PS 4 tetrahedra. The ML-FF developed in this study provides an important tool for exploring a broad spectrum of solid-state and mixed former sulfide-based electrolytes.