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MM: Fachverband Metall- und Materialphysik

MM 37: Transport in Materials: Diffusion, Conduction of Charge or Heat IV

MM 37.2: Vortrag

Mittwoch, 20. März 2024, 12:00–12:15, C 264

Navigating the Interface: Exploring Grain Boundaries in Solid-State Electrolytes through Ultrafast Interpretable ML Potentials — •Tabea Huss, Carsten G. Staacke, Karsten Reuter, and Christoph Scheurer — Fritz-Haber-Institut der MPG, Berlin

The lithium thiophosphate (LPS) material class provides promising candidates for solid-state electrolytes (SSE) in lithium ion batteries due to high lithium ion conductivities and low material cost. The most performant glass-ceramic SSEs from the LPS class are characterized by omnipresent two-dimensional interfaces between crystalline and glassy domains, which can dominate the material performance and cycle stability.

Atomistic simulations are challenged by the complexity of these grain boundaries, having to both capture the complex chemistry of these materials and their low degree of order. Here, we tackle this with newly introduced ultra-fast interpretable machine learning potentials (UFP)[1] to combine the high accuracy of machine learned potentials with the speed of classical ones. This enables us to explore polycrystalline solid-solid interfaces within the LPS system on a grand scale, encompassing system sizes exceeding 10,000 atoms and time scales spanning multiple nanoseconds across substantial ensemble sizes. Ultimately we conduct a comprehensive analysis of grain boundaries in LPS aiming to understand their stability and their influence on the transport of lithium ions.

[1] S. R. Xie et al., npj Comp. Mater. 9, 162 (2023).

Keywords: LPS; Solid-State Electrolytes; Batteries; MLIPs