Electrochemical nitrate sensing based on reduced graphene oxide/conducting polyaniline nanocomposite in environmental water sources

Abstract

In this study, a novel non-enzymatic electrochemical sensor based on a nanocomposite of reduced graphene oxide and conducting polyaniline, denoted as reduced graphene oxide/polyaniline/glassy carbon electrode (rGO/PANI/GCE), was developed for detecting nitrate ions in environmental water sources. The reduced graphene oxide/polyaniline nanocomposite was synthesised by dispersing graphene oxide in water to form a homogeneous suspension, preparing polyaniline separately through chemical oxidative polymerisation, and subsequently combining them while reducing graphene oxide to reduced graphene oxide to produce a uniform composite material. The reduced graphene oxide/polyaniline nanocomposites were deposited on a glassy carbon electrode and applied as the working electrode. The nanocomposite was characterised using Fourier-transform infrared spectroscopy, field-emission scanning electron microscopy, energy-dispersive X-ray spectroscopy, and X-ray diffraction. Cyclic voltammetry, electrochemical impedance spectroscopy, and square wave voltammetry were employed to evaluate the electrochemical behaviour of the sensor. The reduced graphene oxide/polyaniline/glassy carbon electrode exhibited electrocatalytic oxidation performance that surpassed those of the polyaniline/glassy carbon electrode, the graphene oxide/glassy carbon electrode, and the bare glassy carbon electrode. Under optimal conditions, the recorded current showed a linear correlation with nitrate ion concentration in the range of 7 to 45 µM. The regression equation was I = 22.943 + 0.863 C (R2 = 0.982). The sensor demonstrated a sensitivity of 0.863 µA µM−1 with a detection limit of 1.74 µM. It also exhibited reproducibility with a relative standard deviation of 2.99% for nitrate ion detection. Recovery studies were conducted to assess the practical applicability of the sensor, yielding recovery rates between 95% and 105% for spiked samples. The sensor performed effectively with real water samples, demonstrating its suitability for reliable water quality monitoring.