Morphological Modelling of a Metal Foam Supported SOFC Configuration

Thursday, 30 July 2015: 10:40
Alsh (Scottish Exhibition and Conference Centre)
D. Masson (Centre des Matériaux, Mines ParisTech, PSL), B. Abdallah, F. Willot, D. Jeulin (Centre de Morphologie Mathématique, Mines ParisTech, PSL), E. Mercadelli, A. Sanson (ISTEC-CNR), A. Chesnaud, and A. Thorel (Centre des Matériaux, Mines ParisTech, PSL)
The EVOLVE cell, named after a running FP7 project, is an innovative SOFC concept that integrates advanced materials, providing multiple functionalities (electrochemical activity, ion or/and electron conduction, gas diffusion…), and an inventive anode current collector made of a NiCrAl preoxidized foam impregnated with a conductive perovskite. Therefore, this anode combines the beneficial characteristics of MSC and ASC technologies, and strong improvements in terms of reliability and durability (inter-diffusion, Ni coarsening and agglomeration, sulphur tolerance, mechanical robustness and chemical stability under redox cycling in temperature) are expected.

In order to enhance the electrode efficiency, the 3D microstructure needs to be precisely described at the microscopic scale by a morphology model. An optimized microstructure (controlled pores size, morphology and connectivity, grains size distribution, 3D tortuosity and 3D percolation of phases, volume fraction of phases, final thickness of components …) is closely related to the starting parameters (nature and quantity of starting powder, binder, shaping aids…) and to the control of the shaping process parameters (sintering treatment and atmosphere). It should meet the best compromise between a good electrocatalytic activity and a low ohmic resistivity while ensuring a stisfactory long term thermomechanical stability on the life time of the device.

Based on a mathematical morphology approach applied on symmetrical LST/CGO anode layers, the present work aims at showing how a morphology model can be establised and 3D microstructural data relevant for shaping and performances can be derived from back-scattered electrons (BSE) SEM observations. For each sample, a series of images were used as input information for the microstructural modelling. All the original images were first filtered to remove the noise, thresholded and finally a series of morphological operators (openings, surface openings, closings and reconstruction with markers) were applied to remove artefacts. A 3D pluri-Gaussian model has been generated from 2D images, and then computed to predict volume fraction of the 3 phases, 3D tortuosity, gas permeation and ionic conductivities. These results were used for the optimization of the shaping process that includes the integration of the metal foam.