Unveiling the Role of PTFE Surface Coverage on Controlling Gas Diffusion Layer Water Content

Gas diffusion layers (GDLs) are usually coated with a hydrophobic agent to achieve a delicate balance between liquid and gas phases to maximize mass transport. Yet, most GDL numerical models to date have assumed an average contact angle for all materials, thereby eliminating the possibility of studying the role of the polytetrafluoroethylene (PTFE) content. This study introduces two mixed wettability algorithms to predict the mixed wetting behavior of GDLs composed of multiple materials. The algorithms employ contact angle and distance to solid materials to determine the critical capillary pressure for each pore voxel. The application of the algorithms to the estimation of capillary pressure vs saturation curves for two GDLs, namely, a micro-computed tomography (μ-CT) reconstructed SGL 39BA GDL and a stochastically reconstructed Toray 120C GDL, showed that, in agreement with experimental data, the addition of PTFE resulted in a decrease in saturation at a given capillary pressure. For Toray-120C, the mixed wettability model was capable of reproducing experimentally observed features in the intrusion curve at low saturation that could not be reproduced with a single wettability model, providing a clear link between PTFE coverage and intrusion at low saturation. Numerical results also predicted an increased breakthrough pressure and a decrease in saturation with increasing PTFE, in agreement with experimental observations. The decreased saturation at breakthrough improves gas transport through the layer while maintaining the layer's ability to remove water. Diffusivity simulations confirm the increase in diffusivity at breakthrough with increasing PTFE, thereby providing a rationale for the addition of PTFE, as well as for the optimal amount. This study emphasizes the importance of multimaterial wetting models and calls for more detailed investigations into PTFE and ionomer distributions in GDLs and catalyst layers, respectively.