4.7 Article

Optimization of a porous carbon nanofiber layer for the membrane electrode assembly in DMFC

Journal

ENERGY CONVERSION AND MANAGEMENT
Volume 101, Issue -, Pages 525-531

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.enconman.2015.06.014

Keywords

Electrode; Direct methanol fuel cell; Response surface methodology; Optimization

Funding

  1. Universiti Kebangsaan Malaysia (UKM) [DIP-2012-04, GUP-2014-071]

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The performance of direct methanol fuel cells (DMFCs) is strongly influenced by the components in the membrane electrode assembly (MEA), which include a membrane, anode and cathode. The use of nano-materials to improve the performance of fuel cells has attracted the interest of researchers. The incorporation of nano-materials into these carbon-based electrodes is able to improve the performance of the electrodes. The aim of this study is to determine and optimize the parameter effecting the preparation of a nano-structured anode for high power density DMFCs. The two parameters investigated in this study were the Nafion content and the carbon loading. Both the traditional one-factor-at-a-time (OFAT) and the response surface methodology (RSM) optimization techniques were used to determine the optimum parameters. The results from the OFAT study indicated that the possible optimum levels for the Nafion content and carbon nanofiber (CNF) loading range from 2.7 to 3.5 mg cm(-2) and 2.5 to 3.5 mg cm(-2), respectively. A quadratic model was developed based on the RSM results, and an analysis of variance (ANOVA) showed that the model provides a good fit to the experimental data. This result indicated that the developed model successfully predicted the response with good accuracy. The maximum power density (response) was predicted-and experimentally validated using the optimum composition of a 3.04 mg cm(-2) Nafion content and 2.91 mg cm(-2) carbon loading. The model validation revealed that the experimental value obtained under the optimum conditions (21.90 mW cm(-2)) was in good agreement with the values predicted by the model (22.64 mW cm(-2)). (C) 2015 Elsevier Ltd. All rights reserved.

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