Suitable porous electrode design may play a significant role in the performance enhancement of solid oxide fuel cells (SOFCs). In this paper a genetic algorithm optimization method is employed to design electrodes based on a 2D planar SOFC model development. The objective is to find suitable porosities and particle sizes distributions for both anode and cathode electrodes so that the cell performance can be maximized. The results indicate that the optimized heterogeneous morphology may better improve SOFC performance than the homogeneous counterpart, particularly under relatively high current density conditions. The optimization results are dependent on the operating conditions. The effects of inlet mass flow rates and fuel compositions are investigated. The proposed approach provides a systematical method for electrode microstructure designs of high performance SOFCs.

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