[Related publication] "Advanced multiscale modeling of potassium-ion batteries for interplay of electrochemical and mechanical behavior across scales", Small Structures (IF:13.9), 2025. [Link].

Potassium-ion batteries (PIBs) are a promising alternative to lithium-ion batteries, due to the high abundance and low cost of potassium. Despite these advantages, PIBs face challenges such as large ion size and significant volume expansion, which can degrade battery performance.

Our group addresses these issues through DFT-driven multiscale modeling, combining quantum-level calculations with 3D particle simulations. This approach helps us understand ion transport, stress evolution, and overall battery behavior across scales—leading to more reliable and efficient PIB designs.

Magnetic energy harvesters coupled to power lines enable energy capture from ambient electromagnetic fields, offering a sustainable power source for low-power sensing applications. Their performance depends heavily on the B-H characteristics of the magnetic core under realistic excitation conditions.

Our group develops a modeling framework to extract accurate B-H curves by analyzing the effects of core geometry and flux density in power-line environments. This foundation will be extended with machine learning and optimization methods to enable intelligent, simulation-based design of magnetic harvesters for varied operating scenarios.

[Related research] "B-H curve estimation and air gap optimization for high-performance split core", Materials (IF:3.1), 2025. [Link].

All-solid-state batteries (ASSBs) are emerging as next-generation energy storage systems due to their high energy density and enhanced safety features. Unlike liquid-based batteries, lithium ions in ASSBs migrate through contact areas between solid particles, making microstructural characteristics a critical factor in battery performance.

Our group investigates how internal microstructures—such as particle size and volume fraction—influence ion transport and electrochemical behavior. Using a combination of microstructure modeling and physics-based simulations, we analyze particle-to-particle contact areas and their impact on performance. We further develop an electrochemical model that explicitly incorporates contact area effects.