Modeling Nickel Microstructural Evolution in Ni-YSZ Electrodes Using a Mathematical Morphology Approach

Abstract

Microstructural evolution of Nickel in Ni-YSZ fuel electrodes is one of the main limiting degradation mechanisms in solid oxide cells [1]. The redistribution of Nickel is ascribed to its high mobility and low wettability with YSZ, related to interfacial surface tensions. Practically, the degradation manifests as the agglomeration of Ni, potentially accompanied by its migration, mainly reported in electrolysis mode.Extensive efforts have been made to understand Ni agglomeration and relocation. In this frame, advanced imaging techniques have been employed to characterize the microstructure of electrodes after aging in a wide range of conditions. In order to support these observations and gain fundamental insights, a number of computer simulations methods such as: multistate kinetic Potts-Monte Carlo models, cellular automata, phase field, and topological boundary dynamics have been successfully employed in modelling grain growth and recrystallization phenomena. Nevertheless, questions still remain on the exact underlying mechanisms of Ni migration.In the shadow of this lack of clear understanding, a morphological modelling approach aiming at mimicking Ni depletion based on the most fundamental definition of chemical potential and surface curvature minimization would be very helpful to guide researchers into gaining clearer insights of this phenomenon. Moreover, the morphological simulations are very fast compared to the physically based models. Therefore, they can offer the possibility to emulate large database of numerical microstructures in order to study the impact of Ni evolution on the microstructural properties [2].The current work falls within this framework and aims at modelling the two main Ni degradation phenomena, namely coarsening and migration. For this purpose, a novel model based on morphological operations from mathematical morphology [3] has been developed and adapted to the Ni-YSZ specificities. The considered driving force for Ni evolution is the minimization of its surface curvature, and implicitly its chemical potential, which strongly depends on the local operating conditions. After calibration, the model showed a capability to predict, starting from an initial 3-D microstructure as input data, Ni relocation that was in agreement with that observed in a large dataset of 3-D reconstructions from pristine and aged cells. This helps understanding the associated microstructural evolutions which are linked to the cell Area Specific Resistance (ASR) through an adapted in-house model. This coupling of microstructural and electrochemical models allows giving clearer insights and practical recommendations for the design of fuel electrodes with improved stability and electro-catalytic activity.[1] M. Hubert, J. Laurencin, P. Cloetens, B. Morel, D. Montinaro, F. Lefebvre-Joud, Journal of Power Sources, 397 (2018) 240-251.[2] H. Moussaoui, R.K. Sharma, J. Debayle, Y. Gavet, G. Delette, J. Laurencin, Journal of Power Sources, 412 (2019) 736-748.[3] J. Serra, Image Analysis and Mathematical Morphology: Theoretical Advances, Academic Press, Cornell University (1988). Figure 1