Eva Allen (1) (2), Linda Y. Lim (3) (4), Xianghui Xiao (2) (5), Albert Liu (3) (6), Michael F. Toney (7) (8), Jordi Cabana (1), Johanna Nelson Weker (8)
ACS Applied Energy Materials. (26 September 2022). DOI: https://doi.org/10.1021/acsaem.2c02397

Keywords

Lithium-ion battery, operando, microcomputed tomography, fast charge, deep learning, electrode dilation

Abstract

Fast charging at rates above 1C aggressively accelerates structural degradation induced by increases in local temperature and inhomogeneous transport of charge. At the micron scale, the first indication of damage is irreversible expansion of the electrode layers. Electrode damage often involves void formation between the active material and conductive binder matrix. Quantification of this evolution must be carried out in real time and, thus, nondestructively. We report operando X-ray microtomography of cylindrical cells under fast-charge cycling. Two 18650 batteries were measured during cycling after antecedent fast charging cycles to track morphological damage at different points of battery life. A method of deep learning segmentation was used to objectively quantify the electrode degradation. Using Euclidean distance mapping, electrode dilation and voids were spatially resolved. Highly reversible trends in dilation were quantified during charge/discharge in the anode layers with irreversible increases in electrode voids. Anode voids showed clear localization within the first 10 μm near the current collectors, indicating delamination that spread upon further cycling. The cathode dilation trended opposite to the anode with higher fluctuations and an overall decrease in cathode voids. Insight into how fast charging induces structural damage better informs research into fast-charge protocols and battery chemistries.

How Our Software Was Used

All segmentations were accomplished through Dragonfly.

Author Affiliation

(1) Department of Chemistry, University of Illinois at Chicago, Chicago, Illinois 60608, United States
(2) Argonne National Laboratory, Lemont, Illinois 60439, United States
(3) Lucid Motors, Newark, California 94025, United States
(4) School of Computer Science, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
(5) Brookhaven National Laboratory, National Synchrotron Light Souce II, Upton, New York 11973-5000, United States
(6) Ample Inc, San Francisco, California 94124, United States
(7) Department of Chemical Engineering, University of Colorado, Boulder, Colorado 80309, United States
(8) Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Laboratory, Menlo Park, California 94025, United States