Designing an optimal 3D microstructure for three-phase solid oxide fuel cell anodes with maximal active triple phase boundary length (TPBL)

Designing an optimum microstructure for solid oxide fuel cell (SOFC) anodes is a challenging task. In this study, a novel design paradigm is presented to approach this design optimality problem. Prior experimental investigations report an optimal volume fraction for Ni and Yttria-Stabilized Zirconia (YSZ) phases in the anode microstructure that achieves the highest level of triple phase boundary (TPB). The current study takes this another step by introducing a design paradigm for the microstructure of the anode to capture the largest triple phase boundary length (TPBL) within the constraints of optimal volume fractions for the phases reported by experiments. For this purpose, a series of virtual realizations for anodes' microstructure are generated using a special Monte Carlo methodology. The proposed Monte Carlo technique generates 3D virtual realizations using three coupled algorithms (translation, distribution and growth of cells), and it guarantees a wide variety of virtual microstructures through a series of control factors related to rotation, shrinkage, translation, distribution and growth rates of the cells. In the next step, a variety of microstructures (isotropic, anisotropic and virtual microstructures realized based on the Taguchi method) are generated. Finally, aiming to find a microstructure with maximum active TPBL, an artificial neural network algorithm and a genetic algorithm, are utilized in tandem to modulate control parameters of the presented Monte Carlo technique. The characteristics of the microstructure with optimal TPBL are finally discussed in detail.