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Quantitative Comparison of Different Approaches for Reconstructing the Carbon‐Binder Domain from Tomographic Image Data of Cathodes in Lithium‐Ion Batteries and Its Influence on Electrochemical Properties
- Source :
- Energy Technology, Energy technology 11(5), 2200784 (2022). doi:10.1002/ente.202200784
- Publication Year :
- 2022
- Publisher :
- Wiley-VCH Verlag, 2022.
-
Abstract
- Energy technology 11(5), 2200784 (2022). doi:10.1002/ente.202200784<br />It is well known that the spatial distribution of the carbon-binder domain (CBD) offers a large potential to further optimize lithium-ion batteries. However, it is challenging to reconstruct the CBD from tomographic image data obtained by synchrotron tomography. Herein, several approaches are considered to segment 3D image data of two different cathodes into three phases, namely, active material, CBD, and pores. More precisely, it is focused on global thresholding, a local closing approach based on energy-dispersive X-ray spectroscopy data, a k-means clustering method, and a procedure based on a neural network that has been trained by correlative microscopy, i.e., based on data gained by synchrotron tomography and focused ion beam scanning electron microscopy data representing the same electrode. The impact of the considered segmentation approaches on morphological characteristics as well as on the resulting performance by spatially resolved transport simulations is quantified. Furthermore, experimentally determined electrochemical properties are used to identify an appropriate range for the effective transport parameter of the CBD. The developed methodology is applied to two differently manufactured cathodes, namely, an ultrathick unstructured cathode and a two-layer cathode with varying CBD content in both layers. This comparison elucidates the impact of a specific structuring concept on the 3D microstructure of cathodes.<br />Published by Wiley-VCH, Weinheim [u.a.]
- Subjects :
- FOS: Computer and information sciences
Condensed Matter - Materials Science
Technology
General Energy
Materials Science (cond-mat.mtrl-sci)
FOS: Physical sciences
Large scale facilities for research with photons neutrons and ions
Applications (stat.AP)
ddc:620
3D imaging Carbon-binder Domain Electrochemical performance Image segmentation Microstructure Modeling and simulation
Statistics - Applications
ddc:600
Subjects
Details
- Language :
- English
- ISSN :
- 21944288 and 21944296
- Database :
- OpenAIRE
- Journal :
- Energy Technology, Energy technology 11(5), 2200784 (2022). doi:10.1002/ente.202200784
- Accession number :
- edsair.doi.dedup.....1c69048d09ff681a87eb21fd91e2d279