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Title: Mesoscale Effects of Composition and Calendering in Lithium-Ion Battery Composite Electrodes

Abstract

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.more » 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.« less

Authors:
 [1];  [1];  [1];  [1]
  1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Transportation Office. Vehicle Technologies Office
OSTI Identifier:
1605730
Report Number(s):
SAND-2020-2279J
Journal ID: ISSN 2381-6872; 684142
Grant/Contract Number:  
AC04-94AL85000
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Electrochemical Energy Conversion and Storage
Additional Journal Information:
Journal Volume: 17; Journal Issue: 4; Journal ID: ISSN 2381-6872
Publisher:
ASME
Country of Publication:
United States
Language:
English
Subject:
25 ENERGY STORAGE; batteries; novel numerical and analytical simulations; Electrodes; Particulate matter; Electrical conductivity; Simulation

Citation Formats

Trembacki, Bradley L., Noble, David R., Ferraro, Mark E., and Roberts, Scott A. Mesoscale Effects of Composition and Calendering in Lithium-Ion Battery Composite Electrodes. United States: N. p., 2020. Web. doi:10.1115/1.4045973.
Trembacki, Bradley L., Noble, David R., Ferraro, Mark E., & Roberts, Scott A. Mesoscale Effects of Composition and Calendering in Lithium-Ion Battery Composite Electrodes. United States. doi:https://doi.org/10.1115/1.4045973
Trembacki, Bradley L., Noble, David R., Ferraro, Mark E., and Roberts, Scott A. Tue . "Mesoscale Effects of Composition and Calendering in Lithium-Ion Battery Composite Electrodes". United States. doi:https://doi.org/10.1115/1.4045973. https://www.osti.gov/servlets/purl/1605730.
@article{osti_1605730,
title = {Mesoscale Effects of Composition and Calendering in Lithium-Ion Battery Composite Electrodes},
author = {Trembacki, Bradley L. and Noble, David R. and Ferraro, Mark E. and Roberts, Scott A.},
abstractNote = {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},
journal = {Journal of Electrochemical Energy Conversion and Storage},
number = 4,
volume = 17,
place = {United States},
year = {2020},
month = {3}
}

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