Dynamic modelling of platinum degradation in polymer electrolyte fuel cells

Platinum stability in the catalyst layer is vital to the lifetime of polymer electrolyte fuel cells. This thesis uses physical-mathematical modelling to provide a deeper under- standing of platinum degradation. Dissolution, a dominant degradation mechanism under fuel cell operating conditions, is shown to be strongly linked to oxide formation, growth, and reduction. However, since a consistent model that explains this link does not exist, the goal is to understand the platinum oxide processes and relate these to platinum degradation. In the first part, a physical-statistical model of Pt degradation is presented that encompasses the main particle-level degradation pathways namely dissolution, rede- position, coagulation, and detachment. A systematic algorithm is developed to pro- cess experimental inputs and generate outputs on kinetic rate parameters. Once the complete parameter space is explored using Monte Carlo techniques, an optimization routine is run to refine the results. In this way, unique, unambiguous rate parameters pertinent to different degradation mechanisms under various operating protocols have been extracted. It is shown that dissolution/redeposition increase with increasing up- per potential cycling limit; particle detachment increases with increasing surface area of the carbon support, whereas dissolution is independent of the carbon support type. Then a platinum oxide growth and reduction model is developed that implements in- terfacial exchange processes between platinum and oxygen atoms, as well as transport mechanism of oxygen vacancies through diffusion and field migration. A quasi-steady state model of oxide formation, growth, and reduction is developed. Oxide growth is seen to be sensitive to oxygen ion vacancy at the metal-oxide interface and the rate of platinum ion extraction across the interface. The tools this thesis presents provide better understanding to the underlying relations of platinum degradation that can be used to enhance the lifetime of fuel cells. For example, reliable assessments of the prominent degradation mechanism under various operating conditions can be evaluated to set priorities for materials research.