NiO2 and Fe2O3 Surface Modified Glassy Carbon Electrodes for the Electrocatalytic Oxidation of Bioanalytes

Abstract

Electrochemical detection of analytes is desirable due to high sensitivity, vast portability, low cost, and rapid response. Clinically relevant amino acids such as arginine, alanine, serine, and valine may be used as biomarkers for the diagnosis of various diseases, such as obesity and major depressive disorder.1 Typically, changes in metabolite concentrations can be detected by liquid chromatography-mass spectrometry2 or nuclear magnetic resonance spectroscopy.3 These methods tend to be long, tedious, and complicated with low throughput. Using electrochemical sensors could provide a more simplistic approach. One of the challenges of detecting amino acids is that they are not typically electrochemically active. However, in the presence of metal oxide nanoparticles, such as ZnO, MnO2, NiO, and CuO, immobilized on the working electrode surface, electrocatalytic reactions of biomolecules occur.4,5 For example, a glassy carbon electrode modified with NiO nanoparticles was able to electrochemically activate serine, alanine, and glycine under basic aqueous conditions.4 Electrocatalytic activity was observed in both cyclic voltammetry and chronoamperometry experiments. Another example includes a report that metal electrocatalysts, particularly Ni compounds, are better at activating biomolecules containing alcohol functional groups at increased pH.5 Ideally, sensors that can detect biomolecules at physiological pH are preferred to minimize sample preparation in evaluating biofluids. Discussed herein are the surface modifications of a glassy carbon electrode with iron oxide and nickel(IV) oxide surfaces through electrodeposition and passivation. The sensors were tested through detection of arginine, alanine, serine, and valine at physiological pH by cyclic voltammetry in a flow cell. We will report on the found sensitivity towards arginine, alanine, serine, and valine. In addition, the stability of the surfaces was also investigated. The sensitivity and stability of both sensor modification, towards amino acid detection, will be compared. The authors would like to acknowledge supported by CIBBR (P20GM113131), an Institutional Development Award (IDeA) from the National Institute of General Medical Sciences of the National Institutes of Health.