Acta Phys. -Chim. Sin. ›› 2013, Vol. 29 ›› Issue (11): 2361-2370.doi: 10.3866/PKU.WHXB201309032

• ELECTROCHEMISTRY AND NEW ENERGY • Previous Articles     Next Articles

Reconstruction of LiCoO2 Cathode Microstructure and Prediction of Effective Transport Coefficients

WU Wei1,2, JIANG Fang-Ming1, ZENG Jian-Bang1   

  1. 1 Laboratory of Advanced Energy Systems, CAS Key Laboratory of Renewable Energy, Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou 510640, P. R. China;
    2 University of Chinese Academy of Sciences, Beijing 100049, P. R. China
  • Received:2013-06-28 Revised:2013-09-02 Published:2013-10-30
  • Contact: JIANG Fang-Ming
  • Supported by:

    The project was supported by the National Natural Science Foundation of China (51206171) and CAS“100 Talents”Program.


Understanding the impact of microstructure of lithium-ion battery electrodes on performance is important for the development of relevant technologies. In the present work, the Monte Carlo Ising model was extended for the reconstruction of three-dimensional (3D) microstructure of a LiCoO2 lithium-ion battery cathode. The electrode is reconstructed with a resolution on the scale of 50 nanometers, which allows three individual phases to be evidently distinguished: LiCoO2 particles as the active material, pores or electrolyte and additives (polyvinylidene fluoride (PVDF) + carbon black). Characterization of the reconstructed cathode reveals some important structural and transport properties, including the geometrical connectivity and tortuosity of specific phases, the spatial distribution and volume fractions of specific phases, the specific surface area, and the pore size distribution. A D3Q15 lattice Boltzmann model (LBM) was developed and used to calculate the effective thermal conductivity and the effective transport coefficient of the electrolyte (or solid) phase. It is found that tortuosity values determined by LBMare more reliable than those predicted by the random walk simulation or the Bruggeman equation.

Key words: Pore-scale modeling to lithium-ion battery, Microstructure reconstruction, Monte Carlo approach, Characterization, Tortuosity, Effective transport coefficient, Lattice Boltzmann method, Random walk method


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