The electrochemical response of multilayer epitaxial graphene electrodes on silicon carbide substrates was studied for use as an electrochemical sensor for seawater samples spiked with environmental contaminants using cyclic square wave voltammetry. Results indicate that these graphene working electrodes are more robust and have lower background current than either screen-printed carbon or edge-plane graphite in seawater. Identification algorithms developed using machine learning techniques are described for several heavy metals, herbicides, pesticides, and industrial compounds. Dose-response curves provide a basis for quantitative analysis.
Keywords: cyclic square wave voltammetry; identification algorithms; machine learning; multilayer epitaxial graphene; seawater.