Macrohomogeneous battery models are widely used to predict battery performance, necessarily relying on effective electrode properties, such as specific surface area, tortuosity, and electrical conductivity. While these properties are typically estimated using ideal effective medium theories, in practice they exhibit highly non-ideal behaviors arising from their complex mesostructures. In this paper, we computationally reconstruct electrodes from X-ray computed tomography of 16 nickel–manganese–cobalt-oxide electrodes, manufactured using various material recipes and calendering pressures. Due to imaging limitations, a synthetic conductive binder domain (CBD) consisting of binder and conductive carbon is added to the reconstructions using a binder bridge algorithm. Reconstructed particle surface areas are significantly smaller than standard approximations predicted, as the majority of the particle surface area is covered by CBD, affecting electrochemical reaction availability. Finite element effective property simulations are performed on 320 large electrode subdomains to analyze trends and heterogeneity across the electrodes. Significant anisotropy of up to 27% in tortuosity and 47% in effective conductivity is observed. Electrical conductivity increases up to 7.5× with particle lithiation. We compare the results to traditional Bruggeman approximations and offer improved alternatives for use in cell-scale modeling, with Bruggeman exponents ranging from 1.62 to 1.72 rather than the theoretical value of 1.5. We also conclude that the CBD phase alone, rather than the entire solid phase, should be used to estimate effective electronic conductivity. This study provides insight into mesoscale transport phenomena and results in improved effective property approximations founded on realistic, image-based morphologies.
Trembacki, Bradley L., et al. "Mesoscale Effects of Composition and Calendering in Lithium-Ion Battery Composite Electrodes." Journal of Electrochemical Energy Conversion and Storage, vol. 17, no. 4, Mar. 2020. https://doi.org/10.1115/1.4045973
Trembacki, Bradley L., Noble, David R., Ferraro, Mark E., & Roberts, Scott A. (2020). Mesoscale Effects of Composition and Calendering in Lithium-Ion Battery Composite Electrodes. Journal of Electrochemical Energy Conversion and Storage, 17(4). https://doi.org/10.1115/1.4045973
Trembacki, Bradley L., Noble, David R., Ferraro, Mark E., et al., "Mesoscale Effects of Composition and Calendering in Lithium-Ion Battery Composite Electrodes," Journal of Electrochemical Energy Conversion and Storage 17, no. 4 (2020), https://doi.org/10.1115/1.4045973
@article{osti_1605730,
author = {Trembacki, Bradley L. and Noble, David R. and Ferraro, Mark E. and Roberts, Scott A.},
title = {Mesoscale Effects of Composition and Calendering in Lithium-Ion Battery Composite Electrodes},
annote = {Macrohomogeneous battery models are widely used to predict battery performance, necessarily relying on effective electrode properties, such as specific surface area, tortuosity, and electrical conductivity. While these properties are typically estimated using ideal effective medium theories, in practice they exhibit highly non-ideal behaviors arising from their complex mesostructures. In this paper, we computationally reconstruct electrodes from X-ray computed tomography of 16 nickel–manganese–cobalt-oxide electrodes, manufactured using various material recipes and calendering pressures. Due to imaging limitations, a synthetic conductive binder domain (CBD) consisting of binder and conductive carbon is added to the reconstructions using a binder bridge algorithm. Reconstructed particle surface areas are significantly smaller than standard approximations predicted, as the majority of the particle surface area is covered by CBD, affecting electrochemical reaction availability. Finite element effective property simulations are performed on 320 large electrode subdomains to analyze trends and heterogeneity across the electrodes. Significant anisotropy of up to 27% in tortuosity and 47% in effective conductivity is observed. Electrical conductivity increases up to 7.5× with particle lithiation. We compare the results to traditional Bruggeman approximations and offer improved alternatives for use in cell-scale modeling, with Bruggeman exponents ranging from 1.62 to 1.72 rather than the theoretical value of 1.5. We also conclude that the CBD phase alone, rather than the entire solid phase, should be used to estimate effective electronic conductivity. This study provides insight into mesoscale transport phenomena and results in improved effective property approximations founded on realistic, image-based morphologies.},
doi = {10.1115/1.4045973},
url = {https://www.osti.gov/biblio/1605730},
journal = {Journal of Electrochemical Energy Conversion and Storage},
issn = {ISSN 2381-6872},
number = {4},
volume = {17},
place = {United States},
publisher = {ASME},
year = {2020},
month = {03}}
Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
Sponsoring Organization:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Vehicle Technologies Program (EE-2G)
Grant/Contract Number:
AC04-94AL85000
OSTI ID:
1605730
Report Number(s):
SAND--2020-2279J; 684142
Journal Information:
Journal of Electrochemical Energy Conversion and Storage, Journal Name: Journal of Electrochemical Energy Conversion and Storage Journal Issue: 4 Vol. 17; ISSN 2381-6872