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Modeling Single-Crystal Electrodes as a Network of Primary Particles
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DOI：10.1039/D5EE04131G.png)
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Abstract
En 中文
Predicting lithium-ion battery behavior is critical for advancing next-generation energy storage. Conventional Doyle–Fuller–Newman models can simulate many materials; but they fail in phase-separating single-crystal systems; such as lithium iron phosphate (LiFePO4); where the electrical connectivity of primary particles limits charge transport. We redefine the electrode as a network of reactive primary particles; each governed by validated electrochemical kinetics and interconnected through tomographic-informed contact resistances. Without empirical tuning; the model predicts voltage responses of LiFePO4 electrodes across temperatures; rates; loadings; and dynamic load conditions using a single fitted physical parameter. It also captures and explains charge-discharge asymmetries and hysteresis. By bridging particle-scale physics up to cell-level performance; while retaining computational efficiency; this physics-based framework provides a foundation for the design; and control of single-crystal electrode systems.
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