Synthesis and Characterization of 3D Graphene Nanosheet Supports for use in Fuel Cells

The depletion of fossil fuels along with the increasing demand for energy has given rise to the development of sustainable energy technologies. Fuel cells are one of the more popular options for sustainable energy due to its high efficiency, zero emission and low temperature needed for operation. Fuel cells require catalysts in order to have the reaction move forward and catalysts require supports at both the cathode and anode of the fuel cell. Due to its high stability, surface area, and electrical conductivity we will consider using 3D graphene nanosheets (GNS) as a support for our catalysts and what creates an optimal support. Using the Sacrificial Support Method (SSM) we were able to control the morphology of the nanosheets such as: the pore size distribution, pores modality and surface area. This was done by altering three factors: the weight ratio of SiO₂ to GNS, the Si based sacrificial compound used, and the reduction method for turning graphene oxide into GNS. After changing these factors for different samples, Palladium (Pd) nanoparticles were doped on the surface of each sample and tested for electrochemical activity. Energy dispersive spectroscopy (EDS) was used to confirm that all the graphene oxide was reduced to GNS and that no Si based compound remain. After looking at the Brunauer-Emmett-Teller (BET) analysis of each sample it was shown that the chemical reduction method with the SiO₂ sacrificial support yielded the highest surface area. Altering the weight ratio of SiO₂ to GNS was shown to have little effect. Scanning Electron Microscope (SEM) images show multiple anchoring sites for the catalysts on the surface of all samples besides the thermally reduced tetraethyl othrosilicate (TeOS) samples which had a more two dimensional morphology. Raman spectroscopy showed that the chemically reduced SiO₂ sample had the most defects and that all samples had multilayers of GNS. A final characterization test involving cyclic voltammetry was done to test the electrochemical activity of the samples. Although the chemically reduced SiO₂ had a higher surface area than the thermally reduced sample, the thermally reduced SiO₂ sample had higher electrochemical activity and therefore serves as a better electrocatalyst support. This shows that the highest surface area and greatest amount of defects does not necessarily translate to the best electrocatalyst support. The GNS supports need to be optimized for the Pd nanoparticle electrocatalysts because they need to sit on the surface well in order to carry out the oxidation and reduction reactions.