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Access Right: info:eu-repo/semantics/closedAccessSubject: fuel cell

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    Article
    Citation - WoS: 44
    Citation - Scopus: 52
    Graphene-Supported Platinum Catalyst-Based Membrane Electrode Assembly for Pem Fuel Cell
    (Springer, 2016) Devrim, Yilser; Albostan, Ayhan
    The aim of this study is the preparation and characterization of a graphene-supported platinum (Pt) catalyst for proton exchange membrane fuel cell (PEMFC) applications. The graphene-supported Pt catalysts were prepared by chemical reduction of graphene and chloroplatinic acid (H2PtCl6) in ethylene glycol. X-ray powder diffraction, thermogravimetric analysis (TGA) and scanning electron microscopy have been used to analyze structure and surface morphology of the graphene-supported catalyst. The TGA results showed that the Pt loading of the graphene-supported catalyst was 31%. The proof of the Pt particles on the support surfaces was also verified by energy-dispersive x-ray spectroscopy analysis. The commercial carbon-supported catalyst and prepared Pt/graphene catalysts were used as both anode and cathode electrodes for PEMFC at ambient pressure and 70 degrees C. The maximum power density was obtained for the Pt/graphene-based membrane electrode assembly (MEA) with H-2/O-2 reactant gases as 0.925 W cm(2). The maximum current density of the Pt/graphene-based MEA can reach 1.267 and 0.43 A/cm(2) at 0.6 V with H-2/O-2 and H-2/air, respectively. The MEA prepared by the Pt/graphene catalyst shows good stability in long-term PEMFC durability tests. The PEMFC cell voltage was maintained at 0.6 V without apparent voltage drop when operated at 0.43 A/cm(2) constant current density and 70 degrees C for 400 h. As a result, PEMFC performance was found to be superlative for the graphene-supported Pt catalyst compared with the Pt/C commercial catalyst. The results indicate the graphene-supported Pt catalyst could be utilized as the electrocatalyst for PEMFC applications.
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    Conference Object
    Optimization of modeling parameters of of a direct dimethyl ether fuel cell (DDMEFC)
    (Ieee, 2019) Alpaydin, Guvenc Umur; Colpan, C. Ozgur; Devrim, Yilser
    Direct alcohol fuel cells are one of the suitable candidates for sustainable power generation in portable applications. Among the different alcohol types that can be used in these fuel cells, DME, which is almost non-toxic at room temperature and easy to liquefy, and has a molecular structure similar to methanol, is one of the suitable options. For this reason, many studies have been carried out to develop direct dimethyl ether fuel cell (DDMEFC). Mathematical modeling studies also play an important role in the development of DDMEFC since they enable the understanding of the performance of the fuel cells more thoroughly. In this study, a model has been developed by using the principles of conservation chemical species and electrochemistry. A modeling study was performed using MATLAB. The values of some modeling parameters were estimated using the genetic algorithm optimization technique.
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    Conference Object
    Optimization of modeling parameters of of a direct dimethyl ether fuel cell (DDMEFC)
    (Institute of Electrical and Electronics Engineers Inc., 2019) Alpaydin,G.U.; Ozgur Colpan,C.; Devrim,Y.
    Direct alcohol fuel cells are one of the suitable candidates for sustainable power generation in portable applications. Among the different alcohol types that can be used in these fuel cells, DME, which is almost non-Toxic at room temperature and easy to liquefy, and has a molecular structure similar to methanol, is one of the suitable options. For this reason, many studies have been carried out to develop direct dimethyl ether fuel cell (DDMEFC). Mathematical modeling studies also play an important role in the development of DDMEFC since they enable the understanding of the performance of the fuel cells more thoroughly. In this study, a model has been developed by using the principles of conservation chemical species and electrochemistry. A modeling study was performed using MATLAB. The values of some modeling parameters were estimated using the genetic algorithm optimization technique. © 2019 University of Split, FESB.