Algorithmic structural segmentation of defective particle systems: a lithium‐ion battery study

Algorithmic structural segmentation of defective particle systems: a lithium‐ion battery study We describe a segmentation algorithm that is able to identify defects (cracks, holes and breakages) in particle systems. This information is used to segment image data into individual particles, where each particle and its defects are identified accordingly. We apply the method to particle systems that appear in Li‐ion battery electrodes. First, the algorithm is validated using simulated data from a stochastic 3D microstructure model, where we have full information about defects. This allows us to quantify the accuracy of the segmentation result. Then we show that the algorithm can successfully be applied to tomographic image data from real battery anodes and cathodes, which are composed of particle systems with very different morpohological properties. Finally, we show how the results of the segmentation algorithm can be used for structural analysis. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Microscopy Wiley

Algorithmic structural segmentation of defective particle systems: a lithium‐ion battery study

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Publisher
Wiley Subscription Services, Inc., A Wiley Company
Copyright
Journal compilation © 2018 Royal Microscopical Society
ISSN
0022-2720
eISSN
1365-2818
D.O.I.
10.1111/jmi.12653
Publisher site
See Article on Publisher Site

Abstract

We describe a segmentation algorithm that is able to identify defects (cracks, holes and breakages) in particle systems. This information is used to segment image data into individual particles, where each particle and its defects are identified accordingly. We apply the method to particle systems that appear in Li‐ion battery electrodes. First, the algorithm is validated using simulated data from a stochastic 3D microstructure model, where we have full information about defects. This allows us to quantify the accuracy of the segmentation result. Then we show that the algorithm can successfully be applied to tomographic image data from real battery anodes and cathodes, which are composed of particle systems with very different morpohological properties. Finally, we show how the results of the segmentation algorithm can be used for structural analysis.

Journal

Journal of MicroscopyWiley

Published: Jan 1, 2018

Keywords: ; ; ; ;

References

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