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Proceedings Paper

3D geometrical characterization and modelling of solid oxide cells electrodes microstructure by image analysis
Author(s): H. Moussaoui; J. Debayle; Y. Gavet; G. Delette; M. Hubert; P. Cloetens; J. Laurencin
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Paper Abstract

A strong correlation exists between the performance of Solid Oxide Cells (SOCs), working either in fuel cell or electrolysis mode, and their electrodes microstructure. However, the basic relationships between the three-dimensional characteristics of the microstructure and the electrode properties are not still precisely understood. Thus, several studies have been recently proposed in an attempt to improve the knowledge of such relations, which are essential before optimizing the microstructure, and hence, designing more efficient SOC electrodes. In that frame, an original model has been adapted to generate virtual 3D microstructures of typical SOCs electrodes. Both the oxygen electrode, which is made of porous LSCF, and the hydrogen electrodes, made of porous Ni-YSZ, have been studied. In this work, the synthetic microstructures are generated by the so-called 3D Gaussian ‘Random Field model’. The morphological representativeness of the virtual porous media have been validated on real 3D electrode microstructures of a commercial cell, obtained by X-ray nano-tomography at the European Synchrotron Radiation Facility (ESRF). This validation step includes the comparison of the morphological parameters like the phase covariance function and granulometry as well as the physical parameters like the ‘apparent tortuosity’. Finally, this validated tool will be used, in forthcoming studies, to identify the optimal microstructure of SOCs.

Paper Details

Date Published: 14 May 2017
PDF: 8 pages
Proc. SPIE 10338, Thirteenth International Conference on Quality Control by Artificial Vision 2017, 1033804 (14 May 2017); doi: 10.1117/12.2264376
Show Author Affiliations
H. Moussaoui, Univ. Grenoble Alpes (France)
LITEN-CEA, Grenoble (France)
École des Mines de Saint-Etienne, SPIN, LGF, CNRS (France)
J. Debayle, École des Mines de Saint-Etienne, SPIN, LGF, CNRS (France)
Y. Gavet, École des Mines de Saint-Etienne, SPIN, LGF, CNRS (France)
G. Delette, LITEN-CEA, Grenoble (France)
M. Hubert, Univ. Grenoble Alpes (France)
LITEN-CEA, Grenoble (France)
ESRF - The Eurpoean Synchrotron (France)
P. Cloetens, ESRF - The European Synchrotron (France)
J. Laurencin, LITEN-CEA, Grenoble (France)

Published in SPIE Proceedings Vol. 10338:
Thirteenth International Conference on Quality Control by Artificial Vision 2017
Hajime Nagahara; Kazunori Umeda; Atsushi Yamashita, Editor(s)

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