Deep learning image segmentation for the reliable porosity measurement of high-capacity Ni-based oxide cathode secondary particles

Deep learning image segmentation for the reliable porosity measurement of high-capacity Ni-based oxide cathode secondary particles

Abstract The optimization of geometrical pore control in high-capacity Ni-based cathode materials is required to enhance the cyclic performance of lithium-ion batteries. Enhanced porosity improves lithium-ion mobility by increasing the electrode–electrolyte contact area and reducing the number of io...

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Bibliographic Details
Main Authors: Hee-Beom Lee, Min-Hyoung Jung, Young-Hoon Kim, Eun-Byeol Park, Woo-Sung Jang, Seon-Je Kim, Ki-ju Choi, Ji-young Park, Kee-bum Hwang, Jae-Hyun Shim, Songhun Yoon, Young-Min Kim
Format: Article
Language:English
Published: SpringerOpen 2023-11-01
Series:Journal of Analytical Science and Technology
Subjects:
Deep convolutional neural network
Porosity
SEM imaging
Cathode materials
Li-ion batteries
Online Access:https://doi.org/10.1186/s40543-023-00407-z

Internet

https://doi.org/10.1186/s40543-023-00407-z

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