Deep‐Learning‐Enabled Crack Detection and Analysis in Commercial Lithium‐Ion Battery Cathodes (Adv. Funct. Mater. 39/2022)-Reference-Cited by-同舟云学术

Deep‐Learning‐Enabled Crack Detection and Analysis in Commercial Lithium‐Ion Battery Cathodes (Adv. Funct. Mater. 39/2022)

Published:2022-09 Issue:39 Volume:32 Page:2270218
ISSN:1616-301X
Container-title:Advanced Functional Materials
language:en
Short-container-title:Adv Funct Materials

Author:

Fu Tianyu¹²,Monaco Federico³,Li Jizhou⁴,Zhang Kai¹,Yuan Qingxi¹,Cloetens Peter³,Pianetta Piero⁴,Liu Yijin⁴

Affiliation:

1. Beijing Synchrotron Radiation Facility X‐ray Optics and Technology Laboratory Institute of High Energy Physics Chinese Academy of Sciences Yuquan Road, Shijingshan District Beijing 100043 China

2. University of Chinese Academy of Sciences Yuquan Road, Shijingshan District Beijing 100043 China

3. European Synchrotron Radiation Facility 38000 Grenoble France

4. Stanford Synchrotron Radiation Lightsource SLAC National Accelerator Laboratory Menlo Park CA 94025 USA

Publisher

Wiley

Subject

Electrochemistry,Condensed Matter Physics,Biomaterials,Electronic, Optical and Magnetic Materials

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/adfm.202270218

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