Computational prediction of nanoscale transport characteristics and catalyst utilization in fuel cell catalyst layers by the lattice Boltzmann method

Abstract

In the present study, a three-dimensional lattice Boltzmann model based on the quasi-random nanostructural model is proposed to evaluate the mass transport properties and catalyst utilization of fuel cell catalyst layers in pursuance of catalyst performance improvement. A series of catalyst layers is randomly generated with statistical significance at the 95% confidence level to reflect the heterogeneity of the catalyst layer nanostructures. The nanoscale gas transport phenomena inside the catalyst layers are simulated by the D3Q19 (i.e., three-dimensional, 19 velocities) lattice Boltzmann method, and the corresponding mass transport characteristics are mathematically modeled in terms of structural properties. Considering the nanoscale reactant transport phenomena, a transport-based effective catalyst utilization factor is defined and statistically analyzed to determine the structure-transport influence on catalyst utilization. The tortuosity estimation results clearly show that the classic Bruggeman equation underestimates the tortuosity of the catalyst layers and should be modified for PEFC applications. Subsequently, the effective mass diffusion coefficient is calculated by applying the tortuosity factors to the Knudsen diffusion coefficient in the catalyst layers, and it shows good agreement with published experimental data. These results indicate that Knudsen diffusion is the dominant mass transfer mechanism for fuel cell catalyst layers and that the pre-estimated tortuosity accurately reflects the mass transfer phenomena in the catalyst layers. Furthermore, catalyst utilization can be affected by excessive Pt/C catalyst loading due to the lack of pore interconnections, and it is significantly limited by the substantive reactant mass transport path inside the fuel cell catalyst layers.