Deep‐Learning‐Enabled Crack Detection and Analysis in Commercial Lithium‐Ion Battery Cathodes. (19th June 2022)

• Record Type: Journal Article
• Authors: Fu, Tianyu; Monaco, Federico; Li, Jizhou; Zhang, Kai; Yuan, Qingxi; Cloetens, Peter; Pianetta, Piero; Liu, Yijin
• Is Part Of: Advanced functional materials. Volume 32:Number 39(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-06-19
• Subjects: crack detection -- deep learning -- Li‐ion batteries -- phase contrast -- X‐ray holo‐tomography; Materials -- Periodicals; Chemical vapor deposition -- Periodicals; 620.11
• DOI: 10.1002/adfm.202203070
• Languages: English
• ISSNs: 1616-301X

Abstract

Abstract: In Li‐ion batteries, the mechanical degradation initiated by micro cracks is one of the bottlenecks for enhancing the performance. Quantifying the crack formation and evolution in complex composite electrodes can provide important insights into electrochemical behaviors under prolonged and/or aggressive cycling. However, observation and interpretation of the complicated crack patterns in battery electrodes through imaging experiments are often time‐consuming, labor intensive, and subjective. Herein, a deep learning‐based approach is developed to extract the crack patterns from nanoscale hard X‐ray holo‐tomography data of a commercial 18650‐type battery cathode. Efficient and effective quantification of the damage heterogeneity with automation and statistical significance is demonstrated. The crack characteristics are further associated with the active particles' packing densities and a potentially viable architectural design is discussed for suppressing the structural degradation in an industry‐relevant battery configuration. Abstract : A deep learning‐based approach is developed to extract the crack patterns from nanoscale hard X‐ray holo‐tomography data of a commercial 18650‐type battery cathode. The crack characteristics are quantified and further associated with the active particles' packing densities. A potentially viable architectural design is discussed for suppressing the structural degradation in an industry‐relevant battery configuration.