Jeff Allen is a researcher in the computational sciences group at the National Renewable Energy Lab. He got his Ph.D. in applied mathematics in 2017 from the University of Colorado Boulder. His professional aspirations are simply to write efficient code and create pretty pictures. He is happiest when there is a complex algorithm to implement or a massive amount of data that needs to be visualized. His work at NREL exemplifies these passions by providing him the opportunity to write a novel Li-ion battery electrochemistry model and develop a wind-farm optimization python package. These sort of real-world applications are a particular favorite as they naturally lead to easily understandable visualizations.
One of the main goals in modeling lithium-ion batteries is to improve/predict longevity and resilience of new chemistries. To that end, this talk investigates the formation of stress-induced fracture within polycrystalline cathode particles and the impact on capacity loss. The model captures anisotropic Li diffusion within a single polycrystalline particle comprised of hundreds to thousands of randomly oriented grains. Fracture is primarily due to non-ideal grain interactions with slight dependence on high-rate charge demands. Essentially, when neighboring grains are misaligned, they expand a different rates relative to one another leading to high stresses and ultimately the formation of intraparticle cracks. A previous study showed that small particle with large or single grain geometry tend to crack less and retain the most capacity. The goal of this talk is to give an overview of chemo-mechanical modeling and show off some neat results.