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Modelling and analysis of the volume change behaviors of Li-ion batteries with silicon-graphene composite electrodes

材料科学 电极 复合材料 多孔性 电化学 体积热力学 复合数 光电子学 化学 热力学 物理 物理化学
作者
Xueyan Li,Zhiyuan Zhang,Lili Gong,Kang Fu,Haosong Yang,Chenyang Wang,Peng Tan
出处
期刊:Chemical Engineering Journal [Elsevier BV]
卷期号:470: 144188-144188 被引量:23
标识
DOI:10.1016/j.cej.2023.144188
摘要

Silicon-based composites are recognized as one of the most promising negative electrode materials owing to their high theoretical capacity. However, during (dis)charging, the silicon particles undergo significant volume changes, resulting in electrode thickness variation over the cycle. This maps to the cell scale as a change in cell thickness, which translates into outward pressure. To demonstrate the impact of swelling on the cell thickness variation, a model is developed using the moving boundary approach. The ratios of the composites are classified in detail to accurately analyse the contribution of two materials to the capacity. The impacts of the electrode design, such as the thickness of the active layer and the porosity of the negative electrode, as well as the operating conditions on the electrochemical performance and thickness variation of the cell are also investigated. The capacity contribution increases from 85% to 92% when the silicon content increases, and then changing the electrode structure. When the porosity raises from 40% to 60% and the thickness of the negative active layer increases from 55 μm to 85 μm, the capacity utilization varies from 58% to 79% and from 68% to 59%, respectively. In the rate test, the cell thickness variation reduces from 2.49 μm to 1.56 μm when the rate changes from 0.5 C to 2 C. The expansion/contraction behaviour of the active particles during the lithiation/delithiation process is utilized to investigate the variation of cell thickness under different conditions. The optimized simulation is applied to establish the stress variation model to provide insight into the stress evolution during cycling, which can be employed to more accurately assess the performance and potential risk.
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