Westhoff, D;
Finegan, DP;
Shearing, PR;
Schmidt, V;
(2018)
Algorithmic structural segmentation of defective particle systems: A lithium-ion battery study.
Journal of Microscopy
, 270
(1)
pp. 71-82.
10.1111/jmi.12653.
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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.
| Type: | Article |
|---|---|
| Title: | Algorithmic structural segmentation of defective particle systems: A lithium-ion battery study |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1111/jmi.12653 |
| Publisher version: | http://dx.doi.org/10.1111/jmi.12653 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Breakages; cracks; particles; segmentation; thermal runaway |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Chemical Engineering |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10040897 |
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