Understanding and controlling coupled ionic-polaronic dynamics is crucial for optimizing the electrochemical performance in battery materials. However, studying such coupled dynamics remains challenging due to the intricate interplay between Li-ion configurations, polaron charge ordering, and lattice vibrations. Here, we develop a fine-tuned machine-learned force field (MLFF) for ${\mathrm{Li}}_x{\mathrm{FePO}}_4$ that captures the coupled ion-polaron behavior. Our simulations reveal picosecond-scale polaron hops occurring orders of magnitude faster than Li-ion migration, featuring strong correlation to Li configurations. Notably, polaron charge fluctuations are further enhanced at Li-rich/Li-poor phase boundaries, suggesting a potential interfacial electronic conduction mechanism. These results demonstrate the capability of fine-tuned MLFFs to resolve complex coupled transport and provide insight into emergent ionic-polaronic dynamics in ${\mathrm{Li}}_x{\mathrm{FePO}}_4$ and related multivalent cathode materials.

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• Energy storage
• Polarons
• Transport phenomena
• Density functional theory
• Machine learning models
• Molecular dynamics