Publikationstyp: Beitrag in wissenschaftlicher Zeitschrift
Art der Begutachtung: Peer review (Publikation)
Titel: Stochastic 3D modeling of La0.6Sr0.4CoO3−δ cathodes based on structural segmentation of FIB–SEM images
Autor/-in: Gaiselmann, Gerd
Neumann, Matthias
Holzer, Lorenz
Hocker, Thomas
Prestat, Michel René
Schmidt, Volker
DOI: 10.1016/j.commatsci.2012.08.030
Erschienen in: Computational Materials Science
Band(Heft): 67
Seite(n): 48
Seiten bis: 62
Erscheinungsdatum: Feb-2013
Verlag / Hrsg. Institution: Elsevier
ISSN: 0927-0256
Sprache: Englisch
Schlagwörter: Fuel cell; Model; Map; Microstructure
Fachgebiet (DDC): 530: Physik
621.3: Elektro-, Kommunikations-, Steuerungs- und Regelungstechnik
Zusammenfassung: A stochastic microstructure model is developed in order to describe and simulate the 3D geometry of two-phase microstructures (solid and pore phase), where the solid phase consists of spherical particles being completely connected with each other. Such materials appear e.g. in La0.6Sr0.4CoO3−δ (LSC) cathodes of solid oxide fuel cells, which are produced by screen printing and sintering of a paste consisting of LSC powder manufactured by flame spray synthesis. Thus, as a model type, we consider (fully parameterized) random sphere systems which are based on ideas from stochastic geometry and graph theory. In particular, the midpoints of spheres are modeled by random point processes. In order to assure the complete connectivity of the spheres, a modified version of the relative neighborhood graph is introduced. This graph controls the radii of spheres such that a completely connected sphere system is obtained. The model parameters are exemplarily fitted to three different materials for LSC cathodes, produced with sintering temperatures of 750, 850 and 950°C, respectively. Finally, the goodness of fit is validated by comparing structural characteristics of real and simulated image data.
URI: https://digitalcollection.zhaw.ch/handle/11475/1639
Volltext Version: Publizierte Version
Lizenz (gemäss Verlagsvertrag): Lizenz gemäss Verlagsvertrag
Departement: School of Engineering
Organisationseinheit: Institute of Computational Physics (ICP)
Enthalten in den Sammlungen:Publikationen School of Engineering

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Gaiselmann, G., Neumann, M., Holzer, L., Hocker, T., Prestat, M. R., & Schmidt, V. (2013). Stochastic 3D modeling of La0.6Sr0.4CoO3−δ cathodes based on structural segmentation of FIB–SEM images. Computational Materials Science, 67, 48–62. https://doi.org/10.1016/j.commatsci.2012.08.030
Gaiselmann, G. et al. (2013) ‘Stochastic 3D modeling of La0.6Sr0.4CoO3−δ cathodes based on structural segmentation of FIB–SEM images’, Computational Materials Science, 67, pp. 48–62. Available at: https://doi.org/10.1016/j.commatsci.2012.08.030.
G. Gaiselmann, M. Neumann, L. Holzer, T. Hocker, M. R. Prestat, and V. Schmidt, “Stochastic 3D modeling of La0.6Sr0.4CoO3−δ cathodes based on structural segmentation of FIB–SEM images,” Computational Materials Science, vol. 67, pp. 48–62, Feb. 2013, doi: 10.1016/j.commatsci.2012.08.030.
GAISELMANN, Gerd, Matthias NEUMANN, Lorenz HOLZER, Thomas HOCKER, Michel René PRESTAT und Volker SCHMIDT, 2013. Stochastic 3D modeling of La0.6Sr0.4CoO3−δ cathodes based on structural segmentation of FIB–SEM images. Computational Materials Science. Februar 2013. Bd. 67, S. 48–62. DOI 10.1016/j.commatsci.2012.08.030
Gaiselmann, Gerd, Matthias Neumann, Lorenz Holzer, Thomas Hocker, Michel René Prestat, and Volker Schmidt. 2013. “Stochastic 3D Modeling of La0.6Sr0.4CoO3−δ Cathodes Based on Structural Segmentation of FIB–SEM Images.” Computational Materials Science 67 (February): 48–62. https://doi.org/10.1016/j.commatsci.2012.08.030.
Gaiselmann, Gerd, et al. “Stochastic 3D Modeling of La0.6Sr0.4CoO3−δ Cathodes Based on Structural Segmentation of FIB–SEM Images.” Computational Materials Science, vol. 67, Feb. 2013, pp. 48–62, https://doi.org/10.1016/j.commatsci.2012.08.030.


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