Modeling of Solid Oxide Fuel Cell functionally graded electrodes and a feasibility study of fabrication techniques for functionally graded electrodes
With the large energy demands, finite natural resources, and concern about carbon emissions, a more efficient method to produce energy for the electrical power grid is needed. Solid Oxide Fuel Cells (SOFC) have demonstrated nearly 70% efficiency in full scale trials. Much time has been spent reducing the cost of SOFCs, but little investigative focus has been put on optimal power output based on electrode microstructure. Moreover, it appears that no modeling has investigated optimization behavior of functionally graded SOFC electrodes. Also, nonlinear functional grading of SOFC electrodes has not been explored.
In this work, a complete SOFC electrode model from literature was adapted for use in analyzing and comparing the losses between homogeneous, linearly, and nonlinearly graded electrodes. The model is based on a coupled differential equation system that was iteratively solved for three dependent variables: voltage, electronic current, and reactant gas pressure.
It was found that particle size and porosity functional grading reduce diffusion losses near the electrode’s free surface, while decreasing activation loss levels near the electrolyte interface. A range of particle sizes was identified around the optimal homogenous electrode particles size, where particle size grading is beneficial. Outside of this range, homogeneous structured electrodes show better performance. Nonlinear porosity grading shows an improvement over linear grading in voltage losses at small particle diameters (300 nm); little to no benefit is seen for larger particle diameters (3 μm).
This work discusses (1) relative loss contribution in a SOFC electrode, (2) particle size and porosity grading ranges and their associated grading profiles for optimal performance, and (3) design criteria for the efficacy of particle size graded verses homogeneous electrodes. This work can be used to further explore the contribution of individual losses in a SOFC electrode. This information can then be used to further understand how to optimize SOFCs.