Detection of Individual Conducting Graphene Nanoplatelet by Electro-catalytic Depression

We report a strategy to electrochemically detect individual conducting particles colliding with an ultra-microelectrode (UME). This method, called "electro-catalytic depression" (ECD), enables the detection of particles that are electrically conducting but catalytically inert, such as carbonaceous particles. The ECD method takes advantage of the intrinsic difference in heterogeneous kinetics of electron transfer for a given inner-sphere reaction to block the current at the surface of a particle made of a material having poor catalytic properties compared to the material of the electrode. We showcase this method with the detection of individual graphene nanoplatelets (GNPs) of few µm long and 15 nm thick. GNPs block the oxidation of hydrazine on a 5 µm radius Pt UME. We studied the influence of the potential on the current transient produced by individual GNP stochastically colliding on the UME. We evidence that, under 0.1 V vs AgAgCl 3.4 M KCl, electrically conducting GNPs produce discrete stair-shaped drops of current (negative steps) similar to the signal obtained with insulating particles like polystyrene beads. We show how the analysis of a "blocking-type" signal originally developed for insulating beads can be extended to the detection of conducting particles. However, at high potentials (> 0.1 V), where hydrazine oxidation occurs on the GNP, the kinetic difference between GNP and Pt decreases, leading to the decrease of both average and median current step size and the appearance of positive steps. The frequency of collision versus the concentration of GNP and the bias potential are discussed.