Cracking predictions of lithium-ion battery electrodes by X-ray computed tomography and modelling

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Cracking predictions of lithium-ion battery electrodes by X-ray computed tomography and modelling

Boyce, AM; Martínez-Pañeda, E; Wade, A; Zhang, YS; Bailey, JJ; Heenan, TMM; Brett, DJL; (2022) Cracking predictions of lithium-ion battery electrodes by X-ray computed tomography and modelling. Journal of Power Sources , 526 , Article 231119. 10.1016/j.jpowsour.2022.231119. Green open access

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Abstract

Fracture of lithium-ion battery electrodes is found to contribute to capacity fade and reduce the lifespan of a battery. Traditional fracture models for batteries are restricted to consideration of a single, idealised particle; here, advanced X-ray computed tomography (CT) imaging, an electro-chemo-mechanical model and a phase field fracture framework are combined to predict the void-driven fracture in the electrode particles of a realistic battery electrode microstructure. The electrode is shown to exhibit a highly heterogeneous electrochemical and fracture response that depends on the particle size and distance from the separator/current collector. The model enables prediction of increased cracking due to enlarged cycling voltage windows, cracking susceptibility as a function of electrode thickness, and damage sensitivity to discharge rate. This framework provides a platform that facilitates a deeper understanding of electrode fracture and enables the design of next-generation electrodes with higher capacities and improved degradation characteristics.

Type:	Article
Title:	Cracking predictions of lithium-ion battery electrodes by X-ray computed tomography and modelling
Open access status:	An open access version is available from UCL Discovery
DOI:	10.1016/j.jpowsour.2022.231119
Publisher version:	https://doi.org/10.1016/j.jpowsour.2022.231119
Language:	English
Additional information:	This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords:	Lithium-ion battery, Image-based model, Phase field, Fracture, Electrode, Microstructure
UCL classification:	UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Chemical Engineering UCL > Provost and Vice Provost Offices > UCL BEAMS UCL
URI:	https://discovery.ucl.ac.uk/id/eprint/10144367