Insight on electrolyte infiltration of lithium ion battery electrodes by means of a new three-dimensional-resolved lattice Boltzmann model

被引:86
作者
Shodiev, Abbos [1 ,2 ]
Primo, Emiliano [1 ,2 ]
Arcelus, Oier [1 ,2 ]
Chouchane, Mehdi [1 ,2 ]
Osenberg, Markus [3 ]
Hilger, Andre [3 ]
Manke, Ingo [3 ]
Li, Jianlin [4 ]
Franco, Alejandro A. [1 ,2 ,5 ,6 ]
机构
[1] Univ Picardie Jules Verne, CNRS, Lab React & Chim Solides LRCS, Hub Energie,UMR 7314, 15 Rue Baudelocque, F-80039 Amiens, France
[2] Federat Rech CNRS 3459, Reseau Stockage Electrochem Energie RS2E, Hub Energie, 15 Rue Baudelocque, F-80039 Amiens, France
[3] Helmholtz Zentrum Berlin Mat & Energie GmbH, Inst Appl Mat, Hahn Meitner Pl 1, D-14109 Berlin, Germany
[4] Oak Ridge Natl Lab, Electrificat & Energy Infrastruct Div, Oak Ridge, TN 37831 USA
[5] Federat Rech CNRS 3104, ALISTORE European Res Inst, Hub Energie, 15 Rue Baudelocque, F-80039 Amiens, France
[6] Inst Univ France, 103 Blvd St Michel, F-75005 Paris, France
关键词
Li-ion batteries; Manufacturing process; Electrolyte filling; Lattice Boltzmann modeling; Fluid dynamics; FILLING PROCESS; VISUALIZATION; WETTABILITY; TORTUOSITY; SIMULATION; TRANSPORT; IMPACT; FLOWS;
D O I
10.1016/j.ensm.2021.02.029
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
Electrolyte filling takes place between sealing and formation in Lithium Ion Battery (LIB) manufacturing process. This step is crucial as it is directly linked to LIB quality and affects the subsequent time consuming electrolyte wetting process. Although having fast, homogeneous and complete wetting is of paramount importance, this process has not been sufficiently examined and fully understood. For instance, experimentally available data is insufficient to fully capture the complex interplay upon filling between electrolyte and air inside the porous electrode. We report here for the first time a 3D-resolved Lattice Boltzmann Method (LBM) model able to simulate electrolyte filling upon applied pressure of LIB porous electrodes obtained both from experiments (micro X-ray tomography) and computations (stochastic generation, simulation of the manufacturing process using Coarse Grained Molecular Dynamics and Discrete Element Method). The model allows obtaining advanced insights about the impact of the electrode mesostructures on the speed of electrolyte impregnation and wetting, highlighting the importance of porosity, pore size distribution and pores interconnectivity on the filling dynamics. Furthermore, we identify scenarios where volumes with trapped air (dead zones) appear and evaluate the impact of those on the electrochemical behavior of the electrodes.
引用
收藏
页码:80 / 92
页数:13
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