Digital Twin‐Driven Mechanical Degradation Diagnostics: Unraveling Microstructure Evolution of Silicon‐based Lithium‐Ion Battery Anodes

Abstract Silicon is a promising anode material due to its high theoretical capacity, but its extreme volume change (>300%) during cycling leads to contact loss, electrode delamination, and crack propagation, ultimately compromising mechanical integrity. While operando imaging captures morphological evolution, it remains insufficient to resolve the coupled electrochemical, mechanical, and microstructural dynamics that govern degradation. Here, a microstructure‐resolved digital twin model of SiO _x /graphite composite electrodes is presented to diagnose electrochemo‐mechanical behavior. A 3D structure reconstructed from high‐resolution FIB‐SEM tomography is integrated into a coupled simulation framework that captures Li⁺ diffusion, interfacial electrochemical reactions, and concentration‐dependent mechanical strain. Simulations reveal that volumetric expansion distorts internal conduction pathways—enhancing electronic conduction via broadened solid–solid interfaces while impeding ion transport through increased tortuosity. Moreover, charge‐rate‐dependent analysis shows that the charging rate governs the balance between the state of charge (SoC) and local stress. Increasing the rate from 0.5C to 4C reduces stress by limiting the SoC level, thereby mitigating mechanical degradation and enhancing cycling stability. This digital twin framework enables quantitative diagnostics of stress‐driven failure and offers design guidelines for the development of mechanically robust, high‐performance silicon‐based anodes.