Compression Effects on Mass Transport Phenomena in digitally generated PEFC Gas Diffusion Layers by using OpenPNM

Computational resources to model transport phenomena is a useful pre-step in experimental characterization for materials, especially porous materials. Due to their characteristics, lab experiments represent the consumption of physical resources, high equipment costs, and time. Therefore, computer modeling rises as an efficient alternative to emulate the behavior and properties of materials with lower costs. The purpose of this study is to show the impact of the compression rate on mass transport phenomena in digitally created porous media. The analyzed porous media have characteristics of gas diffusion layers (GDLs), an important layer in polymer electrolyte fuel cells (PEFCs). The framework implementation has been carried out by using OpenPNM, a useful open-source pore network modeling tool, which has the ability to compute several transport phenomena and mechanical properties in porous media applications. Several samples have been generated in order to compress the medium with a specific compression factor while the mass transport phenomena are analyzed through the computation of the mass diffusion coefficient. Several correlations between the mass diffusion coefficient and compression rate are proposed from which the best with an R-square around 99% is selected with 95% confidence bounds.