| Issue |
EPJ Web Conf.
Volume 351, 2026
The 11th International Symposium on Hydrogen Energy, Renewable Energy, and Materials (HEREM 2025)
|
|
|---|---|---|
| Article Number | 01017 | |
| Number of page(s) | 7 | |
| DOI | https://doi.org/10.1051/epjconf/202635101017 | |
| Published online | 05 February 2026 | |
https://doi.org/10.1051/epjconf/202635101017
Numerical optimization of PEM fuel cell electrocatalytic layers via an agglomerate level model
National Research Center “Kurchatov Institute”, 123182 Moscow, Russia
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Published online: 5 February 2026
Abstract
The objective of developing the physicochemical model is to formulate recommendations for the fabrication of the membrane–electrode assembly and its components with parameters that meet the requirements imposed on fuel cells. The agglomerate model of the catalytic layers assumes that catalyst particles (platinum on carbon black) are grouped into small spherical agglomerates, each bounded and filled with a polymer electrolyte. Numerical analysis of the cathode catalytic layer shows that the optimal polymer electrolyte content depends on the catalytic layer porosity and air humidity. For porosities in the range of 30–60%, the optimal polymer electrolyte mass fraction lies between 20–30% and decreases with increasing porosity. Increasing air humidity shifts the optimal polymer electrolyte content from approximately 30–40 wt% to about 60 wt%. These results characterize the influence of key parameters on the composition of cathode catalytic layers in proton exchange membrane (PEM) fuel cells. The model-based optimization of cathode catalytic layer structure enhances platinum utilization and minimizes transport losses, enabling reduced noble-metal loading and higher electrochemical efficiency in support of the United Nations (UN) Sustainable Development Goals (SDG 7: Affordable and Clean Energy; SDG 13: Climate Action).
© The Authors, published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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