| Hauptseite > Publikationsdatenbank > Microstructural insights into fast ion transport in solid electrolytes via multiscale modeling |
| Journal Article | FZJ-2026-05062 |
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2026
Springer Nature
[London]
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Please use a persistent id in citations: doi:10.1038/s41467-026-76216-w doi:10.34734/FZJ-2026-05062
Abstract: Improving solid electrolytes is critical for high-performance all-solid-state batteries, yet the microstructural features that enable fast ion transport remain poorly understood. Here, we use multiscale modeling to resolve polycrystalline ion transport from atomic-scale hopping at grain boundaries to continuum-scale percolation, thereby providing insights into realistic solid-electrolyte microstructures. Accurate lightweight machine-learning potentials—developed via closed-loop active learning for exemplar argyrodites $Li_6PS_5X$, $X $∈ {$Cl, Br, I$} — are employed to integrate molecular dynamics with finite element simulations. We find that diffusion barriers of the anion-ordered bulk scale linearly with anion radius. Grain boundaries exert opposite effects depending on the bulk: enhancing ion diffusion in low-diffusivity phases but suppressing it in fast-diffusing ones. $Li_6PS_5I$ exhibits non-Arrhenius transport behavior consistent with experimental observations. Our results clarify the pivotal role of grain boundaries in ion transport and guide a priori microstructural design of advanced solid electrolytes.
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