Catalyst Layer Composition Optimization

Optimization of the catalyst layer composition and thickness in PEFCs for maximum catalyst utilization in operation on air and on impure hydrogen feed streams [Wilson, 1993 Springer et al., 1993]. 

The most recent improvements in Pt catalyst utilization U by optimization of catalyst layer composition and stmcture have led to catalyst utilizations as high as 80%, or more, determined as the ratio between measured ORR current per geometric square centimeter of electrode area and the current expected from the total measured Pt surface area per geometric square centimeter of the electrode, i.e.,... 

The properties and composition of the CL in PEM fuel cells play a key role in determining the electrochemical reaction rate and power output of the system. Other factors, such as the preparation and treatment methods, can also affect catalyst layer performance. Therefore, optimization of the catalyst layer with respect to all these factors is a major goal in fuel cell development. For example, an optimal catalyst layer design is required to improve catalyst... 

The macrohomogeneous model was exploited in optimization studies of the catalyst layer composition. The theory of composifion-dependent performance reproduces experimental findings very well. - The value of the mass fraction of ionomer that gives the highest voltage efficiency for a CCL with uniform composition depends on the current density range. At intermediate current densities, 0.5 A cm < jo < 1.2 A cm , the best performance is obtained with 35 wt%. The effect of fhe Nation weight fraction on performance predicted by the model is consistent with the experimental trends observed by Passalacqua et al. ... 

Friedmann R, Nguyena TV. Optimization of the cathode catalyst layer composition using a novel 2-step preparation method. ECS Trans 2008 16(2) 2021-9. 

Optimization of HT-PEMFC catalyst and catalyst layer composition and structure through iimovative design, evaluation, as well as fundamental understanding. 

Zhang and Shi [36] found that the dual-bound composite catalyst layer exhibited higher performance than either a PTFE-bound CL or a thin-film CL, as shown in Figure 2.9. Optimization of the dual-bound CL showed that impregnation of Nation between the two layers could lead to decreased cell performance [37]. Thus, the optimal structure for a dual-bound CL was a separate hydrophilic layer on top of a hydrophobic layer. 

Wang, Mukherjee, and Wang [124] investigated the effects of catalyst layer electrolyte and void phase fractions on fuel cell performance using a random microstructure. The model predicted volume fractions of 0.4 and 0.26 for void and electrolyte phases, respectively, as the optimal CL compositions. 

The microstructure of a catalyst layer is mainly determined by its composition and the fabrication method. Many attempts have been made to optimize pore size, pore distribution, and pore structure for better mass transport. Liu and Wang [141] found that a CL structure with a higher porosity near the GDL was beneficial for O2 transport and water removal. A CL with a stepwise porosity distribution, a higher porosity near the GDL, and a lower porosity near the membrane could perform better than one with a uniform porosity distribution. This pore structure led to better O2 distribution in the GL and extended the reaction zone toward the GDL side. The position of macropores also played an important role in proton conduction and oxygen transport within the CL, due to favorable proton and oxygen concentration conduction profiles. 

In order to make catalyst layers with high platinum utilization and better performance, we need to determine how various factors affect Pt utilization. Although this objective has been receiving more attention, we have not achieved a fundamental understanding of the relationships of composition, structure, effective properties, and fuel cell performance—a fact that may limit the optimal design and fabrication of CLs. 

Over the past 10 years a multitude of new techniques has been developed to permit characterization of catalyst surfaces on the atomic scale. Low-energy electron diffraction (LEED) can determine the atomic surface structure of the topmost layer of the clean catalyst or of the adsorbed intermediate (7). Auger electron spectroscopy (2) (AES) and other electron spectroscopy techniques (X-ray photoelectron, ultraviolet photoelectron, electron loss spectroscopies, etc.) can be used to determine the chemical composition of the surface with the sensitivity of 1% of a monolayer (approximately 1013 atoms/cm2). In addition to qualitative and quantitative chemical analysis of the surface layer, electron spectroscopy can also be utilized to determine the valency of surface atoms and the nature of the surface chemical bond. These are static techniques, but by using a suitable apparatus, which will be described later, one can monitor the atomic structure and composition during catalytic reactions at low pressures (< 10-4 Torr). As a result, we can determine reaction rates and product distributions in catalytic surface reactions as a function of surface structure and surface chemical composition. These relations permit the exploration of the mechanistic details of catalysis on the molecular level to optimize catalyst preparation and to build new catalyst systems by employing the knowledge gained. 

Separation of the individual contributors can provide useful information about performance optimization for fuel cells, helping to optimize MEA components, including catalyst layers (e.g., catalyst loading, Nafion content, and PTFE content), gas diffusion layers, and membranes. It assists in the down-selection of catalysts, composite structure, and MEA fabrication methods. It also helps in selecting the most appropriate operating conditions, including humidification, temperature, back-pressure, and reactant flow rates. 

Fuel cell performance is affected by MEA composition, including catalyst loading, PTFE content in the gas diffusion layer, and Nafion content in the catalyst layer and membrane, each of which affects the performance in different ways, yielding distinct characteristics in the electrochemical impedance spectra. Even different fabrication methods may influence a cell s performance and electrochemical impedance spectra. With the help of the model described above, impedance spectra can provide us with a useful tool to probe structure-performance relationships and thereby optimize MEA structure and fabrication methods. 

Figure 6.8. Polarization curves of fuel cells with electrodes made of catalyst layers containing various amounts of Nation ( ) 0.2 ( ) 0.8 (A) 2.0 mg/cm2 [5], (Reprinted from Journal of Power Sources, 94(1), Song JM, Cha SY, Lee WM. Optimal composition of polymer electrolyte fuel cell electrodes determined by the AC impedance method, 78-84, 2001, with permission from Elsevier and the authors.)...

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