电池(电)
编码(内存)
计算机科学
材料科学
热力学
物理
功率(物理)
人工智能
作者
Zhe-Tao Sun,Shiwei Chen,Teng Zhao,Yunlong Guo,Zhenli Xu,Shenggao Zhou,Shou-Hang Bo
摘要
The propagation of physicochemical heterogeneity from particles to electrodes under galvanostatic cycling conditions largely determines battery performance but is often computationally unreachable. We formulate a Real 2D (R2D) full-battery model via an electrode-adaptive mathematical framework that addresses the electrochemically correlated nonlinear current-potential responses of the electrodes. This allows us to quantify the impact of multiphysics coupling on cycling performance in emerging solid-state batteries. R2D advances the modeling efficiency and can be generally applied to heterogeneous battery systems, providing a new pathway for accurate full battery simulations.
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