Résumé
The production of fuel cells is bottle-necked by the prohibitive cost of one component – the catalyst layer. The goal of manufacturers has been to minimise Pt loading and maximise the electrochemical efficiency, at scale. A mesoscale model is sought-after, to describe the influence of common manufacturing parameters on the microstructure of fuel cell catalyst layers. In this work we propose a novel end-to-end mesoscale modeling workflow to capture the spatial aggregation of carbon support particles against an ionomer-based binder. We use the Discrete Element Method (DEM) to capture the co-aggregation of the carbon-support and binder, as a function of their inter-particle Derjaguin–Landau–Verwey–Overbeek (DLVO) interactions. This model provides insights in the variance in ionomer aggregation as a function of solvent composition. We observe a decrease in ionomer secondary aggregation with decreasing water content. This variance in the local catalyst – ionomer distribution was studied using various micro-structural descriptors.