Optimizing the water management in proton exchange membrane fuel cells (PEMFCs) is paramount to improving their performance at high current densities. Numerical models describing the physical processes in the PEMFC are an important tool to analyze and understand experimental results and optimize the performance with respect to material properties and operating conditions. Macro-scale models of PEMFCs describing two-phase flow have previously been developed (1, 2). These models rely on effective transport properties and morphological information of the porous layers, such as pore size distribution (PSD), to accurately describe the physical processes. These properties are often estimated using empirical correlations (1). Microstructural modeling provides a feasible alternative to estimate the required transport properties based on the morphology of the porous layers.

Microstructural models describing gas transport and liquid water intrusion have previously been developed for gas diffusion layers (GDLs) (3) and micro-porous layers (MPLs) (4). For catalyst layers (CLs), microstructural models describing the transport and electrochemical reactions under dry conditions are available in literature (5, 6). However, very few studies (7, 8) have accounted for liquid water intrusion in the CLs and the corresponding effect on the transport properties and electrochemical performance. The aim of this work is to develop numerical models to simulate liquid water intrusion in the fuel cell CLs and study the corresponding effect on the transport properties and performance.

A focused ion beam-scanning electron microscopy (FIBSEM) CL reconstruction is used to study gas and charge transport and liquid water intrusion in the CL. Liquid water intrusion in the CL is simulated using a full morphology based model. In-situ μ-CT data was used to validate the liquid water intrusion model. The validated model will be used to simulate liquid water intrusion in CLs with different modes of injection such as nucleation (8), PSD based (7) and boundary based (9). The obtained saturation distributions in the CLs would be used as meshes for continuum simulations to study the changes in the effective diffusivity and electrochemical performance of the CLs.

For the electrochemical simulations, charge transport is simulated in an ionomer film and oxygen transport is simulated in the ionomer, pores and liquid water. Figure 1a shows a schematic of a single pore with ionomer film and the reaction boundary. Since FIBSEM does not provide any information about the ionomer, carbon or platinum, it is assumed that the ionomer forms a thin film at pore-solid interface. This film is digitally reconstructed based on the composition of the CL. The reaction is simulated at the ionomer-solid interface assuming that the solid interface corresponds to platinum particles. The numerical framework for the microscale simulations has been developed in the open-source package OpenFCST (10). The current results show that the different modes of water injection result in different threshold saturations, i.e., the saturation at which percolating pore volume for gas transport is lost. The effective diffusivity of oxygen reduces with an increase in saturation. Electrochemical simulations on partially saturated CLs are underway.

References

1. J. Zhou, A. Putz and M. Secanell, J. The Electrochem. Soc., 164(6), F530 (2017).

2. A. Z. Weber, R. M. Darling and J. Newman, J. Electrochem. Soc., 151(10), A1715 (2004).

3. J. T. Gostick, M. A. Ioannidis, M. W. Fowler and M. D. Pritzker, J. Power Sources, 173(1), 277 (2007).

4. R. Wu, X. Zhu, Q. Liao, H. Wang, Y.-d. Ding, J. Li and D.-d. Ye, International Journal Hydrogen Energy, 35(14), 7588 (2010).

5. M. Sabharwal, L. Pant, A. Putz, D. Susac, J. Jankovic and M. Secanell, Fuel Cells, 16(6), 734 (2016).

6. K. J. Lange, P.-C. Sui and N. Djilali, J. Electrochem. Soc., 157(10), B1434 (2010).

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8. M. El Hannach, J. Pauchet and M. Prat, Electrochimica Acta, 56(28), 10796 (2011).

9. M. Sabharwal, J. T. Gostick and M. Secanell, J. The Electrochem. Soc. (under review) (2018).

10. M. Secanell, A. Putz, P. Wardlaw, V. Zingan, M. Bhaiya, M. Moore, J. Zhou, C. Balen and K. Domican, ECS Transactions, 64(3), 655 (2014).