Effects of agglomerate structure and operating humidity on the catalyst layer performance of PEM fuel cells

Shaojun Dou, Liang Hao, Qianqian Wang and Hong Liu

Applied Energy, 2024, vol. 355, issue C, No S0306261923015751

Abstract: Understanding the transport mechanism in catalyst layer (CL) agglomerates is crucial to enhance Pt utilization and overall fuel cell performance. In this study, high-resolution porous agglomerates are stochastically reconstructed, and capillary condensation of water in agglomerates is directly simulated using a lattice Boltzmann pseudopotential model. On this basis, a pore-scale electrochemical model is developed to investigate the effects of agglomerate structure and operating humidity on local transport resistance and agglomerate effectiveness at different Pt loadings. The results reveal that liquid water formed above 70%RH improves the electrochemical surface area (ECSA) of agglomerates with low ionomer content. An optimum I/C of 0.4 in agglomerates is determined by balancing the activated ECSA and oxygen transport resistance. Through the comparison of local transport resistance with limiting current data, an additional oxygen dissolution resistance of 60–350 s m−1 at the pore/ionomer or ionomer/Pt interface is quantified. The lowest local transport resistance of the agglomerate is achieved at about 70%RH, while condensed water at higher humidities hampers oxygen diffusion within the agglomerate, leading to reduced Pt utilization. Agglomerate size significantly affects the local transport resistance only when excessive ionomer or liquid water severely blocks primary pores. Finally, a novel multiscale coupling strategy integrating the porous agglomerate sub-model with a continuous-scale CL model is proposed, offering innovative insights into comprehending the relationship between CL structure and the performance of proton exchange membrane fuel cells.

Keywords: Pore-scale simulation; Lattice Boltzmann method; Catalyst layer; Agglomerate (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (2)

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DOI: 10.1016/j.apenergy.2023.122211

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