A direct numerical simulation (DNS) model of species and charge transport in the cathode catalyst layer of a polymer electrolyte fuel cell has been developed. The 3D porous microstructure of the catalyst layer has been reconstructed based on a stochastic technique using the low-order statistical information (porosity, two-point correlation function) as obtained from 2D transmission electron microscopy (TEM) micrographs of a real catalyst layer. In this microscopically complex structure, the DNS model solves point-wise accurate conservation equations, thereby obtaining a pore-scale description of concentration and potential fields. DNS predictions are further compared with the one-dimensional macrohomogeneous results to establish appropriate correlations for effective transport properties as input into macroscopic computational fuel cell models. Finally, the utility of the stochastic reconstruction technique coupled with the DNS model is demonstrated through addressing the influence of microstructural inhomogeneity on the fuel cell performance.
All Science Journal Classification (ASJC) codes
- Electronic, Optical and Magnetic Materials
- Renewable Energy, Sustainability and the Environment
- Surfaces, Coatings and Films
- Materials Chemistry