1. Stochastic geometrical modeling of SOC electrode microstructures
- Author
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Debayle, Johan, Théodon, Léo, Laurencin, Jérôme, Centre Sciences des Processus Industriels et Naturels (SPIN-ENSMSE), École des Mines de Saint-Étienne (Mines Saint-Étienne MSE), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Laboratoire Georges Friedel (LGF-ENSMSE), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), CEA- Saclay (CEA), Commissariat à l'énergie atomique et aux énergies alternatives (CEA), and Université Grenoble Alpes (UGA)
- Subjects
[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing ,image analysis ,stochastic geometry ,[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV] ,[SPI.GPROC]Engineering Sciences [physics]/Chemical and Process Engineering ,fuel cells ,[INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation ,image processing - Abstract
International audience; During the last decades, advances in 3D characterization have been achieved to image the Solid Oxide Cells (SOC) electrode microstructure with a high spatial resolution by using different techniques (FIB-SEM, X-ray tomography…). These techniques enable to study the links between the electrode microstructural and physical properties. However, this approach is time consuming as it requires the manufacturing and the characterization of several cells. An alternative consists in generating representative synthetic microstructures by numerical means in order to increase the amount of data required to establish the correlations linking the electrode microstructure parameters. The proposed talk will then introduce different ways to model and simulate virtual SOC electrode microstructures, of both two-phase electrodes and three-phased composite electrodes, using stochastic geometry. The performance, representativeness and flexibility of such models will be demonstrated and validated on real 3D reconstructions. The author(s) acknowledge(s) the support of the French Agence Nationale de la Recherche (ANR), under grant ANR-18-CE05-0036 (project ECOREVE).
- Published
- 2022