Impact of Platinum Loading and Catalyst Layer Structure on PEMFC Performance

Abstract

Reducing Pt in proton exchange membrane fuel cells is the subject of intense research and development. Recently, researchers have observed significant performance loss due to a transport limitation at the Pt surface. This is investigated here with loading studies that fix electrode thickness and bulk properties. Within these layers, the impact of Pt dispersion is probed by varying the wt% of Pt/C while holding Pt loading and electrode thickness constant by diluting with carbon, effectively varying the average distance between Pt particles while maintaining gas phase loss in the catalyst layer. Results elucidate how the electrode structure impacts local transport loss. It is demonstrated that local transport loss is not fully captured with a normalized Pt area. Additional geometric considerations that account for ionomer surface area relative to the Pt particles are required to resolve performance loss at low Pt loading as electrode structure varies. Furthermore, within this ionomer layer an interfacial resistance at both the gas and Pt interfaces are necessary to account for performance trends observed. These results demonstrate that residual performance loss associated with low cathode Pt loading can be mitigated by electrode design, where oxygen flux through the gas/ionomer interface to the Pt surface is minimized.

Oxygen Reduction Reaction Measurements on Platinum Electrocatalysts Utilizing Rotating Disk Electrode Technique

“…Redistribution subject to ECS terms of use (see 54.245.55.244 Downloaded on 2018-05-11 to IP A critical and unresolved challenge in PEMFCs that has arisen with the attempts at reducing Pt loading and cost is the lower than projected peak power for cathodes incorporating ultra-low Pt loadings. The issue is being studied intensively and different groups 114,[121][122][123][124][125] have identified several possible routes including catalyst interaction with Nafion. In MEAs of PEMFCs, since it is not possible to carry out an investigation in the absence of ionomer (ionomer is indispensable for proton conduction), the contribution of the ionomer adsorption/blocking cannot be easily examined.…”

Polarization loss correction derived from hydrogen local-resistance measurement in low Pt-loaded polymer-electrolyte fuel cells

“…[1] Regrettably already for loadings below 0.10 mg Pt /cm² at the cathode side, the performance suffers quite drastically due to a poorly understood local resistance, which is thought to be related to an increased local mass-transport resistance (MTR), although other causes have been proposed as well. [2][3][4][5][6][7][8][9][10][11][12][13] In terms of physical interpretation, the MTR represents the local resistance of a reactant molecule towards reaching an active reaction site, which becomes more significant as the number of reaction sites decrease but the desired overall reaction rate remains the same.…”

Adjoint Method for the Optimization of the Catalyst Distribution in Proton Exchange Membrane Fuel Cells

“…3 Since the technical feasibility of PEMFCs has already been established, a significant amount of current research focuses on increasing the durability and decreasing the total manufacturing cost, which, at large manufacturing volumes, is mainly given by the cost of the catalyst layers (CLs), bipolar plates, and membrane. [4][5][6][7][8] (For instance, the US Department of Energy estimates that 45% of the cost of fuel cell stack fabricated at a volume of 500,000 systems/year is due to the cost of platinum, 27% to bipolar plates, 10% to the cost of membrane 9 ). In this article, we address the problem of decreasing the manufacturing cost of the CLs by presenting a large-scale optimization technique to optimize the platinum deposition in the CLs of PEMFCs.…”

“…The technique can also be applied to the optimization of other two-dimensional (2-D) and three-dimensional (3-D) field variables, such as porosity distribution and ionomer content, in which the number of optimization parameters is very large (e.g. more than 10 4 ). There is much work on the numerical optimization of catalyst layers in fuel cells.…”

“…the amounts of catalyst at each node of the finite element discretization are independent variables. In this way, the number of optimization variables is equal to the total number of nodes in the catalyst layers, which, in this work, is larger than 10 4 . In order to compute the optimum catalyst distribution in the CL, we define the catalyst sensitivity functions of the cell voltage and current density.…”