Computational modeling of materials in polymer electrolyte membrane fuel cells
MetadataShow full item record
Fuel cells have the potential to change the energy paradigm by allowing more efficient use of energy. In particular, Polymer Electrolyte Membrane Fuel Cells (PEMFC) are interesting because they are low temperature devices. However, there are still numerous challenges limiting their widespread use including operating temperature, types of permissible fuels and optimal use of expensive catalysts. The first two problems are related mainly to the ionomer electrolyte, which largely determines the operating temperature and fuel type. While new ionomer membranes have been proposed to address some of these issues, there is still a lack of fundamental knowledge to guide ionomer design for PEMFC. This work is a computational study of the effect of temperature and water content on sulfonated poly(ether ether ketone) and the effect of acidity on sulfonated polystyrene to better understand how ionomer material properties differ. In particular we found that increased water content preferentially solvates the sulfonate groups and improves water and hydronium transport. However, we found that increasing an ionomer’s acid strength causes similar effects to increasing the water content. Finally, we used Density Functional Theory (DFT) to study platinum nano-clusters as used in PEMFCs. We developed a model using the atom’s coordination number to quickly compute the energy of a cluster and therefore predict which platinum atoms are most loosely held. Our model correctly predicted the energy of various clusters compared to DFT. Also, we studied the interaction between the various moieties of the electrolyte including the catalyst particle and developed a force field. The coordination model can be used in a molecular dynamics simulation of the three phase region of a PEMFC to generate unbiased initial clusters. The force field developed can be used to describe the interaction between this generated cluster and the electrolyte.