Fermi level equilibration of Ag and Au plasmonic metal nanoparticles supported on graphene oxide

For the first time, the process of Fermi level equilibration has been studied and compared for plasmonic metal nanoparticles (PMNPs) supported on conducting substrates i.e. graphene oxide (GO) sheets. The extent of Fermi level equilibration has been monitored by recording the changes in the position and intensity of the surface plasmon resonance (SPR) band of Ag and Au PMNPs supported on reduced graphene oxide (rGO). Ag PMNPs supported on rGO show larger variation in the SPR band position and intensity as compared to rGO supported Au PMNPs. The average shift in the chemical potential has been determined through the changes in the SPR band position for Ag, Ag@rGO, Au, and Au@rGO, which are approximately -1812 +/- 70 mV, -171 +/- 20 mV, -96 +/- 8 mV and -29 +/- 4 mV, respectively. The calculated values of the shift in chemical potential suggest that Ag and its rGO composite are more prone to Fermi level equilibration as compared to the Au and Au@rGO composite. The electrochemical (galvanostatic) charging/discharging (GCD) measurements also brace the observations from the chemical charging/discharging method with minor variations due to the measurements under two different conditions; particulate films in the case of the former versus the dispersed phase in the case of the latter. Moreover, the average capacitance associated with single nanoparticles (Ag and Au) is estimated using the capacitance values determined from GCD curves and the approximate number of nanoparticles determined from the quantity of PMNPs used in the deposited films for GCD measurements. These values are in close agreement with the quantized double layer capacitance values of monolayer protected clusters reported in the literature. A similar inference is also drawn from the enzyme-less glucose sensing activity of these nanostructures, where Ag and Ag@rGO show better activity in terms of lower values of the limit of detection (LOD) and the limit of quantification (LOQ).