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Main Authors: Ou, Yongliang, Scholz, Lena, Keshav, Sanath, Ikeda, Yuji, Kraft, Marvin, Divinski, Sergiy, Gómez-Bombarelli, Rafael, Zeier, Wolfgang G., Fritzen, Felix, Grabowski, Blazej
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2510.18630
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author Ou, Yongliang
Scholz, Lena
Keshav, Sanath
Ikeda, Yuji
Kraft, Marvin
Divinski, Sergiy
Gómez-Bombarelli, Rafael
Zeier, Wolfgang G.
Fritzen, Felix
Grabowski, Blazej
author_facet Ou, Yongliang
Scholz, Lena
Keshav, Sanath
Ikeda, Yuji
Kraft, Marvin
Divinski, Sergiy
Gómez-Bombarelli, Rafael
Zeier, Wolfgang G.
Fritzen, Felix
Grabowski, Blazej
contents Argyrodite solid electrolytes, such as Li$_6$PS$_5$Cl, exhibit some of the highest known superionic conductivities. Yet, the mechanistic understanding of Li$^+$ transport in realistic argyrodite microstructures -- where atomic-scale mechanisms interplay with continuum-scale dynamics at grain boundaries -- remains limited. Here, we resolve Li$^+$ transport in silico by developing accurate machine-learning potentials via closed-loop active learning and embedding the potentials in a multiscale modeling framework that integrates molecular dynamics with finite element simulations. We show that bulk diffusion barriers scale linearly with anion radius. Grain boundaries have opposite effects depending on the bulk -- enhancing Li$^+$ diffusion in low-diffusivity phases but suppressing it in fast-diffusing ones. Simulations of polycrystalline Li$_6$PS$_5$I reveal non-Arrhenius transport behaviors consistent with experiments. Grain-size-dependent predictions indicate that grain refinement improves intergranular contacts in argyrodites without compromising superionic conductivity, while nanosizing can activate ionic transport in electrolytes lacking intrinsic superionic behavior. Our findings highlight the decisive role of microstructure in developing solid electrolytes.
format Preprint
id arxiv_https___arxiv_org_abs_2510_18630
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Non-Arrhenius Li-ion transport and grain-size effects in argyrodite solid electrolytes
Ou, Yongliang
Scholz, Lena
Keshav, Sanath
Ikeda, Yuji
Kraft, Marvin
Divinski, Sergiy
Gómez-Bombarelli, Rafael
Zeier, Wolfgang G.
Fritzen, Felix
Grabowski, Blazej
Materials Science
Argyrodite solid electrolytes, such as Li$_6$PS$_5$Cl, exhibit some of the highest known superionic conductivities. Yet, the mechanistic understanding of Li$^+$ transport in realistic argyrodite microstructures -- where atomic-scale mechanisms interplay with continuum-scale dynamics at grain boundaries -- remains limited. Here, we resolve Li$^+$ transport in silico by developing accurate machine-learning potentials via closed-loop active learning and embedding the potentials in a multiscale modeling framework that integrates molecular dynamics with finite element simulations. We show that bulk diffusion barriers scale linearly with anion radius. Grain boundaries have opposite effects depending on the bulk -- enhancing Li$^+$ diffusion in low-diffusivity phases but suppressing it in fast-diffusing ones. Simulations of polycrystalline Li$_6$PS$_5$I reveal non-Arrhenius transport behaviors consistent with experiments. Grain-size-dependent predictions indicate that grain refinement improves intergranular contacts in argyrodites without compromising superionic conductivity, while nanosizing can activate ionic transport in electrolytes lacking intrinsic superionic behavior. Our findings highlight the decisive role of microstructure in developing solid electrolytes.
title Non-Arrhenius Li-ion transport and grain-size effects in argyrodite solid electrolytes
topic Materials Science
url https://arxiv.org/abs/2510.18630