(322k) Multiphase Behavior and Hierarchical Pore Structures — Key to Predict Porous Electrodes Performance

Reliably controlling lithium-ion batteries is crucial for ensuring their efficient and safe operation. Porous electrodes are essential components of these batteries, and there have been extensive efforts in the past decades to model their performance accurately. Although these models facilitate battery design, they often cannot track internal reaction progress with high accuracy. Battery characterization techniques such as Electrochemical Impedance Spectroscopy (EIS) are commonly used to monitor cells by extracting specific features empirically using equivalent circuits. However, to interpret these electrochemical data more accurately, the models need to go beyond the Newman model and simple circuits.

The challenge of modeling realistic porous electrodes, such as graphite and lithium iron phosphate, lies in their time-varying spatial distributions of reaction resistance and transport resistance. These materials are commonly used in batteries and are known for their phase-separation phenomena during operation. The morphology of their particles, including size distribution and particle porosity, has been extensively studied and optimized in the past decades to balance power and lifetime. To track the time-varying spatial distribution of reactions and transport, a model must account for two critical features: phase separation and hierarchical pore structures.

In this study, we propose a hierarchical multiphase porous electrode theory that deals with phase separation and reactions on all surface areas, including the outer surface of particles and inner surfaces of particles due to micropores/cracks. By coupling transport resistance and reaction resistance changes resulting from phase separation, this model can accurately track internal reaction progress in porous electrodes across a broad range of operating conditions. We demonstrate the model's capabilities by comparing two sets of experimental results using the same graphites with known morphology. Furthermore, we extend the model to a full cell consisting of NMC/Graphite and use it for the optimization of fast charging. Lastly, we linearize the hierarchical multiphase porous electrode theory and derive the impedance to interpret EIS more confidently, making it a useful tool for monitoring cell cycling and degradation with confidence.