Phosphoric Acid Distribution Patterns in High Temperature PEM Fuel Cells

Thursday, 5 October 2017: 16:20
National Harbor 3 (Gaylord National Resort and Convention Center)
N. Bevilacqua (KIT, Helmholtz Institute Ulm), M. G. George, A. Bazylak (University of Toronto), and R. Zeis (Institute of Physical Chemistry, KIT, Helmholtz Institute Ulm)
As the proton conducting medium, phosphoric acid plays a vital role in high temperature PEM fuel cells (HT-PEMFC) operating in the temperature range from 140-200°C. The acid is introduced into the fuel cell by doping the polybenzimidazole (PBI) membrane, and it migrates into the catalyst layer (CL) when the cell is assembled. The acid distribution continues during the activation phase and is influenced by operating conditions such as the cell temperature, reactant flowrates, current density, and electrode potential. The electrochemical active surface area (ECSA), which is critical for the fuel cell performance, is determined by the triple-phase boundary (the common boundary of the catalyst particles, the reactant gases, and the phosphoric acid). Due to the liquid state of the phosphoric acid electrolyte, the triple-phase boundary of the HT-PEMFC may evolve continuously during the cell operation. For better control of this dynamic process, HT-PEMFCs are usually constructed with thick electrodes (≈ 100 µm) and a relatively high platinum loading (≈ 1 mgPt/cm2). A better understanding of the acid distribution patterns would help improve the electrode designs and lower the cost by reducing the Pt loading.

In this work, we investigate the distribution of phosphoric acid in gas diffusion electrodes (GDE). The study combines imaging techniques (micro-computed tomography or µCT, FIB-SEM) with modeling (Pore Network Modeling or PNM). To validate the application of PNM, phosphoric acid was injected into different GDEs and the invasion pattern was investigated. The samples were mounted in a sample holder emulating a rib and channel structure, and they were inspected using µCT. The reconstructed 3D image stacks were subsequently segmented into void-, carbon fiber-, MPL-, and CL-voxels1, and the segmented images were then reconstructed into a 3D pore network2. This pore network contains the real shapes of the pores and throats, and therefore the flow characteristics are still representative of the real sample3. The quality of the extracted network is solely limited by the quality of the µCT images. Invasion percolation simulations were performed using the open source package OpenPNM to predict the distribution of phosphoric acid inside GDEs, showing the effect of network parameters on the invasion pattern.

We found that the experimentally observed invasion patterns agree very well with the pore network simulation and that invasion percolation is a valid approach to investigate phosphoric acid distributions in GDEs4. The presence of an MPL restricts the intrusion of phosphoric acid into the carbon fiber substrate and significantly reduces the saturation. Figure 1 shows the simulated phosphoric acid invasion pattern into a densely woven carbon fiber layer. The pathway is tortuous and exhibits capillary fingering, and the acid is creeping alongside the bottom of the rib of the sample holder until it emerges into the channel. These observations are all consistent with experiments.


1. Banerjee, R. et al. Heterogeneous porosity distributions of polymer electrolyte membrane fuel cell gas diffusion layer materials with rib-channel compression. Int. J. Hydrog. Energy 41,14885–14896 (2016).

2. Hinebaugh, J. & Bazylak, A. Pore Network Modeling to Study the Effects of Common Assumptions in GDL Liquid Water Invasion Studies. ESFuelCell 201291466 (2012).

3. Gostick, J. et al. OpenPNM: A Pore Network Modeling Package. Comput. Sci. Eng. 18,60–74 (2016).

4. Chevalier, S. et al. Role of the microporous layer in the redistribution of phosphoric acid in high temperature PEM fuel cell gas diffusion electrodes. Electrochimica acta, 212, 187-194. (2016).