3D pore-scale simulation of the fluid flow through the electrodes of High Temperature Polymeric Electrolyte Fuel Cell

Fuel cells and hydrogen are two key components for building a competitive, secure, and sustainable clean energy economy, due to possibility to convert diverse fuels directly into electrical power without combustion and a carbon-free fuel that can be produced from renewable resources. However, to become competitive in a market, fuel cells should overcome the issues by improvements in durability and performance as well as reductions in manufacturing cost. Recent advances in fuel cell technology has been made by development of the high temperature (HT) polymeric electrolyte membrane (PEM) fuel cells (FC). Owing to combination of the advantages of two types of fuel cells, namely polymeric electrolyte membrane and phosphoric acid, it is considered as one of the best technological solutions. Further improvements cannot be done without deep understanding of the major causes and underlying physico-chemical phenomena for specific degradation mechanisms of different compartments of HT-PEMFC, especially porous electrodes, which are the most vulnerable part prone to degradation processes, and predicting the impact of these degradation effects. Modeling can provide insight into the mechanisms that lead to irreversible or reversible performance loss and the relation between these mechanisms and the operating conditions, based on the changes in materials properties that can be observed. Moreover, another important issue of modeling is understanding the interaction between different specific membrane degradation mechanisms and their complex and mixed effects due to their simultaneously occurrence in real fuel cell operation, which requires multi-scale analysis of undergoing phenomena. This work represents a step towards reliable algorithms for reconstructing micro-morphology of electrode materials of high-temperature proton-exchange membrane fuel cells and for performing pore-scale simulations of fluid flow (including rarefaction effects). In particular, we developed a deterministic model for a woven gas diffusion layer (GDL) and the stochastic model for a non-woven GDL and a carbon- supported catalyst layer (CL) based on clusterization of carbon particles. We verified that both developed models accurately recover the experimental values of permeability, without any special ad-hoc tuning. Moreover, we investigated the effect of catalyst particle distributions inside the CL on the degree of clusterization and on the microscopic fluid flow, which is relevant for degradation modeling (e.g. loss of phosphoric acid). The three-dimensional pore-scale simulations of fluid flow for the direct numerical calculation of macroscopic transport parameters, like permeability, were performed by the Lattice Boltzmann Method (LBM). Within framework of this thesis, we investigate how distribution of catalyst (Pt) particles can affect gas dynamics, electro-chemistry and consequently performance in high temperature proton exchange membrane fuel cells. Optimal distribution of catalyst can be used as a mitigation strategy for phosphoric acid loss and crossover of reagents through membrane. The main idea is that one of the reasons of degradation is the gas dynamic pulling stress at the interface between the catalyst and the membrane. This stress can be highly reduced by tuning the main morphological parameters of the catalyst layer, like distribution of catalyst particles and clusterization. We have performed direct numerical pore-scale simulations of the gas flow through catalyst layer for different distributions of catalyst particles, in order to minimize this stress and hence to improve durability. The results of pore-scale simulation for exponential decay distribution show more than one order of magnitude reduction of the pulling stress, compared to the homogeneous (conventional) distribution. Moreover, a simplified three-dimensional macroscopic model of the membrane electrode assembly (MEA) with catalyst layer comprised of three sublayers with different catalyst loadings, has been developed to analyze how the proposed mitigation strategy affects the polarization curve and hence the performance. This macroscopic model presents 67% reduction in pulling stress for feasible mitigation strategy, at the price of only 9.3% reduction in efficiency at high current densities.