Solid-state ionic conductors are pivotal for advancing energy storage technologies, yet their performance is critically governed by mesoscale structural features that influence ionic percolation pathways. In this work, random resistance model is employed to unravel the effects of mesoscopic features, including the size, shape, and alignment of grains and pores, on ionic transport percolation networks in polycrystalline ionic conductors. Our simulations reveal that larger grain sizes and vertically aligned columnar grains significantly enhance ionic conductivity by reducing percolation thresholds. Notably, vertically aligned pores further optimize percolation networks, enabling conductivity exceeding that of fully dense materials in specific configurations. By correlating simulated results with experimental data for garnet-type lithium-ion and oxygen-ion conductors, we demonstrate the model's robustness in predicting structure-property relationships. These insights establish a universal framework for designing high-performance solid electrolytes through mesoscale engineering, with broad implications for batteries, fuel cells, and beyond.

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• Batteries
• Fuel cells
• Ionic conductivity
• Percolation
• Ceramics
• Complex oxides
• Solid-state batteries
• Materials modeling