Quantitative Relationships Between Pore Tortuosity, Pore Topology, and Solid Particle Morphology Using a Novel Discrete Particle Size Algorithm. Issue 10 (3rd June 2020)

• Record Type: Journal Article
• Authors: Usseglio-Viretta, Francois L. E.; Finegan, Donal P.; Colclasure, Andrew; Heenan, Thomas M. M.; Abraham, Daniel; Shearing, Paul; Smith, Kandler
• Is Part Of: Journal of the Electrochemical Society. Volume 167:Issue 10(2020)
• Publication Date: 2020-06-03
• Subjects: Batteries - Lithium -- Tortuosity factor -- discrete particle size algorithm -- particle identification -- pore network -- nickel-cobalt-manganese -- graphite; Electrochemistry -- Periodicals; 541.3705
• DOI: 10.1149/1945-7111/ab913b
• Languages: English
• ISSNs: 0013-4651

Abstract

Abstract : To sustain the continuous high-rate charge current required for fast charging of electric vehicle batteries, the ionic effective diffusion coefficient of the electrodes must be high enough to avoid the electrode being transport limited. Tortuosity factor and porosity are the two microstructure parameters that control this effective diffusion coefficient. While different methods exist to experimentally measure or calculate the tortuosity factor, no generic relationship between tortuosity and microstructure presently exists that is applicable across a large variety of electrode microstructures and porosities. Indeed, most relationships are microstructure specific. In this work, generic relationships are established using only geometrically defined metrics that can thus be used to design thick electrodes suitable for fast charging. To achieve this objective, an original, discrete particle-size algorithm is introduced and used to identify and segment particles across a set of 19 various electrode microstructures (nickel-manganese-cobalt [NMC] and graphite) obtained from X-ray computed tomography (CT) to quantify parameters such as porosity, particle elongation, sinuosity, and constriction, which influence the effective diffusion coefficient. Compared to the widely used watershed method, the new algorithm shows less over-segmentation. Particle size obtained with different numerical methods is also compared. Lastly, microstructure-tortuosity relationship and particle size and morphology analysis methods are reviewed.