Pore-Network Reconstruction and Simulation of the Fuel Cell Catalyst Layer
Authors: Sadeghi Mohammadamin , Barralet Jake , Gostick Jeff T. 
Published: February 2020

Fuel cell technology is widely considered as a promising green alternative to the current internal combustion engines. Nevertheless, they are still expensive and therefore not economically viable for the majority. Among others, platinum underutilization in the catalyst layer is known problem that if tackled leads to a significant price reduction. The difficulty of this task stems from the very small size of the catalyst layer which makes it extremely difficult to probe experimentally. Consequently, modeling has been proven useful to give insights about the influencing factors in the catalyst layer and how they affect the overall performance of the fuel cell. Recently, pore-scale modeling has been employed to better understand transport phenomena at microscopic level. Nevertheless, because of the exponential computing requirements, most studies had to limit their scope either in domain size or resolution, which has two direct consequences: (a) the results may not be representative, and (b) they are not truly predictive.
We propose a pore-scale model for the catalyst layer in the nanometer scale. Resolving the catalyst layer at this scale is unprecedented to the best of our knowledge. The model is based on pore-networks, i.e. mapping the porous structure onto an intricate network of pores connected through arbitrary throats. The underlying assumption in pore network models is that intensive properties are constant throughout each pore. Given the extremely small scale of pores in the catalyst layer, i.e. ~100 um, this assumption is reasonable. While pore network models inevitably introduce a small error, they reduce the computing requirement by 4 orders of magnitude or more. This feature allows for studying much larger domains with the same computing power.
First, we digitally reconstruct the microstructure of the catalyst layer based on a process-based technique introduced by [1]. The reconstructed geometry is in the form of a 3d image and consists of 4 distinct phases: carbon support, platinum, nafion, and void. Using a network extraction algorithm [2], the equivalent networks corresponding to the void and carbon phases are extracted. We propose a simple algorithm to couple the two extracted networks with the remainder of the original 3d image, which now only consists of nafion and platinum. Finally, the diffusive transport of oxygen coupled with conductive transport of protons and electrons with the electrochemistry at the interface of nafion and platinum is solved through an iterative scheme. The results are reported in terms of effective properties and polarization curves. The effect of microstructural features such as nafion content and platinum loading on such properties are studied. All the geometric reconstructions and transport simulations were done with the open-source code OpenPNM [3].
The present study is a major step towards better understanding the multiphysics involved in the catalyst layer at true pore scale. The pore network methodology used in this study was key to significantly reducing the computing requirements that otherwise have hindered studying the catalyst layer at higher resolutions. We hope that this study will become a cornerstone for many future studies.

References

[1] Siddique, N. A., and Fuqiang Liu. Electrochimica Acta 55.19 (2010): 5357-5366.
[2] Gostick, Jeff T. Physical Review E 96.2 (2017): 023307.
[3] Gostick, Jeff, et al. Computing in Science & Engineering 18.4 (2016): 60-74.

Figure 1