All solid-state lithium-metal batteries (ASSLMBs) using sulfide electrolytes offer tremendous promise due to their increased safety and high theoretical specific capacity. Lithium argyrodites have emerged as a lucrative class of solid-state electrolytes (SSEs) for ASSMLBs, owing to their high Li-ion conductivity (~10-4–10-3 S/cm), good elastic stiffness (~30 GPa), and low flammability. The Li-ion conduction pathways in single-crystalline compounds are typically examined using ab initio molecular dynamics (AIMD) simulations. However, the real-world materials have an added complexity of accounting for grain boundaries (GBs), which makes the AIMD simulations computationally expensive. To circumvent this limitation, we developed a novel ReaxFF interatomic potential, an empirical bond-order based force field, to investigate the effect of GBs on the Li-ion conductivity in argyrodite electrolytes. To carry out the fitting procedure, we used the fundamental static properties such as lattice parameters, heats of formation, elastic constants, surface energies, and equation of states in order to find the best set of ReaxFF parameters for LiPS system. All the static properties used in the fitting process were calculated using the periodic density functional theory. ReaxFF produced lithium diffusion maps of Li7PS6-LT and Li7PS6-HT clearly reproduces the formation of lithium diffusive cages around the sulfur atoms which validates the accuracy of the ReaxFF potential.At the atomic scale, we characterized the energetics, composition, and transport properties of three low-energy (Σ3 and Σ5) symmetric tilt GBs in lithium argyrodites. Our findings indicate that the presence of GBs impede the diffusion of Li ions. The activation energies for Li-ion conduction crossing the grain boundaries are consistently higher than that of the bulk crystal which confirms the significant grain boundary resistance in this material. We also formulate a polycrystalline model to quantify the atomistic effects of the grain boundaries. In this talk, we have explored these results to critically understand the role of grain boundaries on Li conductivity, and how altering the microstructure can be utilized to optimize new high-performance SSEs for emerging ASSLMBs.
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