Quantitative Relationships Between Pore Tortuosity, Pore Topology, and Solid Particle Morphology Using a Novel Discrete Particle Size Algorithm

Usseglio-Viretta, Francois E.; Finegan, Donal P.; Colclasure, Andrew; Heenan, Thomas M.; Abraham, Daniel; Shearing, Paul; Smith, Kandler

doi:10.1149/1945-7111/ab913b

Title: Quantitative Relationships Between Pore Tortuosity, Pore Topology, and Solid Particle Morphology Using a Novel Discrete Particle Size Algorithm

Journal Article · 03 June 2020 · Journal of the Electrochemical Society (Online)

DOI: https://doi.org/10.1149/1945-7111/ab913b · OSTI ID:1631781

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National Renewable Energy Lab. (NREL), Golden, CO (United States). Center for Integrated Mobility Sciences
Univ. College London (United Kingdom); The Faraday Inst., Didcot (United Kingdom)
Argonne National Lab. (ANL), Argonne, IL (United States)

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.

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Research Organization:: National Renewable Energy Laboratory (NREL), Golden, CO (United States); Argonne National Laboratory (ANL), Argonne, IL (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Transportation Office. Vehicle Technologies Office; Faraday Institution; USDOE

Grant/Contract Number:: AC36-08GO28308; FIRG001; AC02-06CH11357

OSTI ID:: 1631781

Alternate ID(s):: OSTI ID: 1660059; OSTI ID: 1660757

Report Number(s):: NREL/JA-5400-75813; MainId:6693; UUID:9fffce88-fd33-ea11-9c2f-ac162d87dfe5; MainAdminID:13843

Journal Information:: Journal of the Electrochemical Society (Online), Vol. 167, Issue 10; ISSN 1945-7111

Publisher:: IOP PublishingCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 32 works

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Title: Quantitative Relationships Between Pore Tortuosity, Pore Topology, and Solid Particle Morphology Using a Novel Discrete Particle Size Algorithm

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