Optimization of Transports in a PEMFC Catalyst Layer at High Current Densities: Coupled Modeling/Imaging Approach
Authors: Salvado Miguel Barreiros , Schott Pascal , Guetaz Laure , Gerard Mathias , Bultel Yann 
Published: May 2020

Decreasing the cost of proton exchange membrane fuel cells (PEMFC) is vital for the realization of the fuel cell vehicle market. For this challenge, it is essential not only to still reduce the electrode platinum loading but also to maintain a high performance at high current density. However, even for electrodes made with the most performant catalysts, a large performance loss is observed at high current density and this loss becomes larger as the Pt loading is lower. In operating conditions, recent work has shown that this performance loss was predominantly limited by oxygen [1] and proton transport to the catalytic surface. In order to quantify and link both effects to real active layer structural aspects a coupled modeling/imaging approach is performed. The microstructure of a real electrode is reconstructed in 3D using FIB-SEM (Fig.1a), STEM (Fig.1b) and HRTEM (Fig.1c). The first technique provides the carbon grain arrangement, whereas from the second one platinum nanoparticle size distribution is extracted. With HRTEM, an averaged-thickness is extracted for the ionomer thin layer. The raw imaging data acquired (Fig.1a) is then post-treated using a defined procedure. From the post-treated stack, certain portions that can be representative are selected according to [2]. An example is illustrated in Fig.1e with the respective raw portion in Fig.1d. From this portion, a statistically/imaging-based structure is then built in COMSOL ® Multiphysics software (Figs.1f-1h). The agglomerate 3D model is coupled with a 2D MEA model [3] – a model that allows computing local operating conditions. Studies on volume elements [2] of the catalyst layer are performed with physical input parameters as relative humidity, O2 concentration on the pore, among others, taken from the 2D MEA model.

The following set of physics are included in the 3D agglomerate model: the Fickian diffusion for oxygen transport in the ionomer film – accounting for deviations of ionomer’s thin layer behaviour from bulk [4] – and in the pore phase – accounting for Knudsen effects; the ionic transport, through charge conservation equation; a kinetic model assuming a 4-step ORR reaction [5].

From the studies performed, simulation results show that the catalyst layer performance is mainly limited by oxygen diffusion in the ionomer phase and ionic transport in the primary pores [6].

Figs. 1a to 1k – Process from a raw image to numerical modeling : raw image stack (Fig.1a), platinum particle distribution from STEM acquisition (Fig.1b), HRTEM where Nafion layer can be observed (Fig.1c), portion of the image stack (Fig.1d) and the respective segmented portion (Fig.1e) ; carbon phase (brown), platinum phase (yellow), ionomer and pore phase (green and gray respectively) (Figs.1f-1h). Simulated oxygen concentration profile on Nafion (Fig.1i) and pore (Fig.1j) phases, ionic potential distribution (Fig.1k).

References:

1. J.P. Owejan, J. E. Owejan, W. Gu, Journal of The Electrochemical Society, 160-(8): 824-833 (2013).

2. H.R. Sanei, R. S. Fertig III, Composites Science and Technology, 117 : 191-198 (2015).

3. B. Randrianarizafy, P. Schott, M. Chandesris, M. Gerard, Y. Bultel, International Journal Of Hydrogen Energy 43: 8907-8926 (2018).

4. Y. Kurihara, T. Mabuchi, T. Tokumasu, ECS Transactions, 75-(14): 129-137 (2016).

5. M. Moore, A. Putz, M. Secanell, Journal of the Electrochemical Society, 160-(6) : 670-681 (2013).

6. T. Mashio, K. Sato, A. Ohma, Electrochimica Acta, 140 : 238-249 (2014).

Figure 1