Optimization of a catalyst layer with a high-utilization gradient Pt distribution for polymer electrolyte membrane fuel cells

The optimal design of platinum (Pt) particles distribution within catalyst layer (CL) favors their utilization and the polymer electrolyte membrane fuel cell (PEMFC) performance. A stochastic algorithm is employed in this study to reconstruct the 2D microstructure of the CL by considering the random distribution of carbon carriers and ionomers and a novel double-gradient distribution of Pt particles. The double-gradient Pt-distributed CLs feature double dividend regions of equal and unequal lengths. Subsequently, the reaction transport process within these double-gradient CLs is numerically investigated by a lattice Boltzmann (LB) method. The numerical results indicate that the reaction transport process within the double-gradient CLs differs greatly from that within conventional CLs. With the total Pt particle number constant, increasing the Pt particle number within the inlet region of the CL initially improves and consequently degrades the oxygen reduce reaction (ORR), whereas a reverse design always leads to a reduced ORR. The optimal CL gradient for double dividend regions of equal length occurs when the ratio of Pt particle number in the inlet region to that in the outlet region (Pt_in:Pt_out) is 5:1, which leads to a 28.85 % increase in the ORR rate compared with that of the conventional CL. Moreover, for the gradient CL with double dividend regions of unequal length, we find that the optimal ratios of L_in:L_out and Pt_in:Pt_out are 1:4 and 6:1, respectively; this gradient CL yields a 58.65 % increase in the ORR compared with that of the conventional CL.