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Degradation behavior of ionomer in the cathode catalyst layer of polymer electrolyte fuel cells

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  • Xiao, Yan
  • Zheng, Weibo
  • Wang, Jue
  • Li, Bing
  • Ming, Pingwen
  • Zhang, Cunman

Abstract

Ensuring the durability of proton exchange membrane fuel cell (PEMFC) stacks is crucial for their commercial viability. Dynamic loading conditions can significantly accelerate the aging of the fuel cell's catalyst layer (CL), and ionomers play a pivotal role in maintaining both proton transport performance and the durability of this layer. A 1 kW PEMFC stack was subjected to a rigorous 3000-h New European Driving Cycle accelerated stress test to assess the relationship between the evolution of ionomer characteristics and the loss of proton transport performance of the cell. Extensive analyses revealed that degradation within the CL occurs in both in-plane and through-plane directions. The rapid deterioration of ionomers is closely linked to the decline in performance of the membrane electrode assembly. Following degradation, we observed a reduction in the mechanical strength of the ionomers and deterioration of their chemical structure, with side chains degrading more significantly than the main chains. Moreover, the average thickness of the ionomer layer on the catalyst surface decreased, leading to reduced coverage of the catalyst. This study reveals how ionomer degradation contributes to the loss of proton transport networks and pore structures within the CL. These insights will provide a theoretical foundation for the design of more durable CL.

Suggested Citation

  • Xiao, Yan & Zheng, Weibo & Wang, Jue & Li, Bing & Ming, Pingwen & Zhang, Cunman, 2025. "Degradation behavior of ionomer in the cathode catalyst layer of polymer electrolyte fuel cells," Applied Energy, Elsevier, vol. 389(C).
  • Handle: RePEc:eee:appene:v:389:y:2025:i:c:s0306261925004891
    DOI: 10.1016/j.apenergy.2025.125759
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    References listed on IDEAS

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    1. Liu, Hao & Chen, Jian & Hissel, Daniel & Lu, Jianguo & Hou, Ming & Shao, Zhigang, 2020. "Prognostics methods and degradation indexes of proton exchange membrane fuel cells: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 123(C).
    2. Yang, Yange & Li, Xiang & Chu, Tiankuo & Li, Bing & Zhang, Cunman, 2022. "Property evolution of gas diffusion layer and performance shrink of fuel cell during operation," Renewable Energy, Elsevier, vol. 194(C), pages 596-603.
    3. Jouin, Marine & Gouriveau, Rafael & Hissel, Daniel & Péra, Marie-Cécile & Zerhouni, Noureddine, 2016. "Degradations analysis and aging modeling for health assessment and prognostics of PEMFC," Reliability Engineering and System Safety, Elsevier, vol. 148(C), pages 78-95.
    4. Chu, Tiankuo & Xie, Meng & Yu, Yue & Wang, Baoyun & Yang, Daijun & Li, Bing & Ming, Pingwen & Zhang, Cunman, 2022. "Experimental study of the influence of dynamic load cycle and operating parameters on the durability of PEMFC," Energy, Elsevier, vol. 239(PD).
    5. David A. Cullen & K. C. Neyerlin & Rajesh K. Ahluwalia & Rangachary Mukundan & Karren L. More & Rodney L. Borup & Adam Z. Weber & Deborah J. Myers & Ahmet Kusoglu, 2021. "New roads and challenges for fuel cells in heavy-duty transportation," Nature Energy, Nature, vol. 6(5), pages 462-474, May.
    6. Li, Bing & Wan, Kechuang & Xie, Meng & Chu, Tiankuo & Wang, Xiaolei & Li, Xiang & Yang, Daijun & Ming, Pingwen & Zhang, Cunman, 2022. "Durability degradation mechanism and consistency analysis for proton exchange membrane fuel cell stack," Applied Energy, Elsevier, vol. 314(C).
    7. Pei, Pucheng & Chen, Dongfang & Wu, Ziyao & Ren, Peng, 2019. "Nonlinear methods for evaluating and online predicting the lifetime of fuel cells," Applied Energy, Elsevier, vol. 254(C).
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