On the Importance of Incorporating Structural Heterogeneity of Porous Electrodes in LI-ION Battery Models: Pore Network Modelling a Way to MOVE Forward

Abstract

Image processing of 3D tomographic images to extract structural information of porous materials has become extremely important in porous media research with the commoditization of x-ray tomography equipment to the lab scale. Extracted pore networks from image analysis techniques enable transport properties calculation for bigger domains at a very low computational cost, allowing substantial investigation of porous media. Consequently, they are being increasingly used to model Multiphysics transport processes in various energy storage devices like fuel cells and batteries, where the geometrical structure plays a vital role in electrochemical performance, but true pore-scale modeling is computationally infeasible.Traditionally, pore network modelling has been used to find electrochemical performance of Li Ion batteries by investigating pore phase interconnectivity in carbon electrodes. The actual lithium ion electrode, however, consists of active material, carbon binder and electrolyte filled pore phase. The interconnectivity of these phases influences the effective transport properties and hence electrochemical performance of cathode material. The presence of carbon binder phase not only reduces the SEI layer between active material and electrolyte phase but also influences tortuosity and effective electronic conductivity in the pore and solid phase respectively. The present work uses a pore network modelling frame work to investigate the effect of carbon binder phase on Lithium Ion battery cathode. We used actual three phase, X-ray tomography image of NMC-811 cathode material and studied its electrochemical performance with and without binder phase. Unlike previous models which compensate the importance of carbon binder as electrical conductor by assuming high electronic conductivity of active material, this study considers actual values of conductivities in all phases. Moreover, the impact of nanoporosity in the carbon binder phase was also explored and found to enhance the reaction rate compared to solid binder. The reduction in computational time achieved using the pore-network approach was so significant that adding additional physics and transient conditions could conceivably be included to increase the accuracy of the model, thereby providing more realistic simulations and point to the true limiting processes. The developed pore network model opens a new avenue for modelling complex electrochemical systems with less computational cost, enabling simulation of bigger electrode domains while keeping structural heterogeneities of material.