Inhomogeneous Distribution of Platinum and Ionomer in the Porous Cathode to Maximize the Performance of a PEM Fuel Cell Lei Xing Institute of Green Chemistry and Chemical Technology, School of Chemistry and Chemical Engineering, Jiangsu University, Zhenjiang 212013, China Weidong Shi School of Chemistry and Chemical Engineering, Jiangsu University, Zhenjiang 212013, China Prodip K. Das Fluid Dynamics and Thermal Systems Division, School of Mechanical and Systems Engineering, Newcastle University, Newcastle NE1 7RU, UK Keith Scott School of Chemical Engineering and Advanced Materials, Newcastle University, Newcastle NE1 7RU, UK DOI 10.1002/aic.15826 Published online June 25, 2017 in Wiley Online Library (wileyonlinelibrary.com) A proton exchange membrane (PEM) fuel cell model, accounting for the combined water transport mechanism, ionomer swelling, water phase-transfer, two-phase flow and transport processes, is developed. The inhomogeneous distributions of Pt and ionomer inside the catalyst layer (CL) are numerically studied to achieve an optimal cell performance for two types of oxygen reduction reaction catalysts at different loadings. Results indicate that the optimal variation in loading through the thickness of the electrode (slopes) of Pt catalyst and ionomer vary with conditions of operation. An optimal platinum slope increases the agglomerate effectiveness factor and decreases the second Damk € ohler number near the CL-membrane interface. An optimal ionomer slope increases the CL porosity near the GDL-CL interface and decreases the mass transport resistance of reactant through the ionomer film. Their interaction shows that the optimal platinum slope is a tradeoff between the electrochemical active surface area and porosity at high current densities. V C 2017 American Institute of Chemical Engineers AIChE J, 63: 4895–4910, 2017 Keywords: PEM fuel cell, inhomogeneous distribution, graded catalyst layer, platinum and ionomer loading, mathemati- cal modeling Introduction Due to high efficiency and low environmental impact, pro- ton exchange membrane fuel cells (PEMFCs) are one of the most promising energy conversion devices for portable power sources and alternative to combustion engines in vehicles. 1,2 However, the high cost and insufficient utilization of platinum as the sluggish oxygen reduction reaction (ORR) catalysts at the cathode hamper the widespread use of PEMFCs. 3 It is reported that the acceptable cost for the application of the automotive fuel cell system should below $30/kW. 4 As plati- num is dispersed within a complex porous carbon matrix and combines with ionomer (typically Nafion V R ) and void space to build up triple-phase-boundaries (TSBs) for effective electro- chemical reaction in an operating condition, 5 the architectural design and size of the catalyst layer (CL), especially the rational distributions of platinum and ionomer inside the CL, is critically important to reduce the cost and improve the cell performance. 6–9 Moreover, a good water removal ability is another vital consideration for improved cell performance at high current densities, as the liquid water inside the cathode CL and the GDL strongly influence the cell performance and durability. 10–14 Prior research has experimentally improved the cell perfor- mance using the electrode design with a graded distribution of platinum, ionomer, and pores through the electrode thick- ness. 15–17 However, experimental studies are very expensive and time-consuming in which the trial-and-error procedures only allow a small portion of design parameters being explored. Computational modeling therefore provides an alter- native to address this issue. A few modeling activities are available in the open literature on CL optimization considering the inhomogeneous spatial distributions of CL compositions. Wang et al. 18 investigated the nonuniform Nafion V R distribution across the entire thickness of a three-sublayer structure and found that significant enhancement of cell performance was Correspondence concerning this article should be addressed to L. Xing at xin- glei1314@gmail.com or W. Shi at swd1978@ujs.edu.cn. V C 2017 American Institute of Chemical Engineers AIChE Journal 4895 November 2017 Vol. 63, No. 11