Abstract
Electrode microstructure and processing can strongly influence lithium-ion battery performance such as capacity retention, power, and rate. Battery electrodes are multi-phase composite structures wherein conductive diluents and binder bond active material to a current collector. The structure and response of this composite network during repeated electrochemical cycling directly affects battery performance characteristics. We propose the fabric tensor formalism for describing the structure and evolution of the electrode microstructure. Fabric tensors are directional measures of particulate assemblies based on inter-particle connectivity, relating to the structural and transport properties of the electrode. Fabric tensor analysis is applied to experimental data-sets for positive electrode made of lithium nickel manganese cobalt oxide, captured by X-ray tomography for several compositions and consolidation pressures. We show that fabric tensors capture the evolution of inter-particle contact distribution and are therefore good measures for the internal state of and electronic transport within the electrode. The fabric tensor analysis is also applied to Discrete Element Method (DEM) simulations of electrode microstructures using spherical particles with size distributions from the tomography. These results do not follow the experimental trends, which indicates that the particle size distribution alone is not a sufficient measure for the electrode microstructures in DEM simulations.
Original language | English |
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Pages (from-to) | 540-550 |
Number of pages | 11 |
Journal | Journal of Power Sources |
Volume | 297 |
DOIs | |
State | Published - Nov 30 2015 |
Funding
Work performed contributing to the underlying research and publication was supported by Andrew Stershic's Department of Energy Computational Science Graduate Fellowship , under grant DE-FG02-97ER25308 . Dr. Nanda acknowledges support from the Vehicle Technologies Program, under Energy Efficiency and Renewable Energy (EERE) Office of the Department of Energy . The submitted manuscript has been authored by a contractor of the U.S. Government under Contract No. DE-AC05-00OR22725. Accordingly, the U.S. Government retains a non-exclusive, royalty-free license to publish or reproduce the published form of this contribution, or allow others to do so, for U.S. Government purposes.
Funders | Funder number |
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Andrew Stershic's Department of Energy Computational Science | DE-FG02-97ER25308 |
U.S. Government | DE-AC05-00OR22725 |
U.S. Department of Energy | |
Office of Energy Efficiency and Renewable Energy |
Keywords
- DEM
- Fabric tensor
- Lithium-ion battery
- NMC