Royal C. Ihuaenyi

Understanding and predicting the electro-chemo-mechanical behavior of energy materials is essential for the design, manufacturing, and management of advanced devices. These systems inherently involve two or more interacting physical fields, and the resulting complexity arises not only from the individual fields but also from their deep, bidirectional coupling. Since Onsager’s foundational work on coupled thermodynamics and kinetics^1,2, extensive research has enriched our understanding of such multi-field interactions across materials systems. In battery science, these theories have been widely applied to interpret the behavior of nanoparticles, porous electrodes, and full cells^3,4.

Electrochemical methods such as voltammetry and impedance spectroscopy have long provided indispensable insight into charge-transfer kinetics, ion transport, and degradation mechanisms in batteries and related electrochemical systems. However, these canonical techniques treat electrodes largely as electrochemically active but mechanically passive media, even though ion insertion, phase transformations, and structural rearrangements inherently couple chemical potentials with stress and strain. This electro-chemo-mechanical coupling governs not only particle-level transformations but also porous-electrode transport, active material utilization, and long-term reversibility. In this talk, I will present recent advances that revisit classical electrochemical techniques through the lens of electro-chemo-mechanical interactions with technical assistance of AI, thereby expanding their diagnostic reach and physical interpretability.