Computational Model for Predicting Particle Fracture During Electrode Calendering

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Abstract

In the context of calling for low carbon emissions, lithium-ion batteries (LIBs) have been widely concerned as a power source for electric vehicles, so the fundamental science behind their manufacturing has attracted much attention in recent years. Calendering is an important step of the LIB electrode manufacturing process, and associated changes in the electrode microstructure and mechanical properties are worthy of study. In this work, we report the observed cracking of active material (AM) particles due to calendering pressure under ex situ X-ray nano tomography experiments. We developed an innovative 3D discrete element method (DEM) model with bonded connections to physically mimic the calendering process using real AM particle shapes derived from the tomography experiments. The DEM model can well predict the change of the morphology of the dry electrode under pressure, and the changes of the applied pressure and porosity are consistent with the experimental values. At the same time, the model is able to simulate the secondary AM particles cracking by the fracture of the bonds under force. Our model is the first of its kind that can predict the fracture of the secondary particles along the calendering process. This work provides a tool for guidance in the manufacturing of optimized LIB electrodes.

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Xu, J., Paredes-Goyes, B., Su, Z., Scheel, M., Weitkamp, T., Demortière, A., & Franco, A. A. (2023). Computational Model for Predicting Particle Fracture During Electrode Calendering. Batteries and Supercaps, 6(12). https://doi.org/10.1002/batt.202300371

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