ZnO/Co₃O₄/rGO nanocomposite-based electrochemical sensor for highly sensitive detection of L-cysteine in food matrices

Document Type

Article

Source of Publication

Journal of Food Composition and Analysis

Publication Date

12-1-2025

Abstract

L-cysteine has multiple essential functions in human health, while its detection is a vital requirement for medical practice and food quality control. Here, a ZnO/Co₃O₄/rGO nanocomposite was prepared using the hydrothermal-assisted coprecipitation method, and its application for the electrochemical detection of L-cysteine on a glassy carbon (GC) electrode was subsequently demonstrated. X-ray diffraction (XRD) analysis indicated that hexagonal and spinel ZnO and Co₃O₄ phases were formed, and that their crystallite size was 18.6 nm on average, and FTIR observed Zn–O, Co–O, and C[dbnd]C vibrations, confirming the presence of metal oxides and reduced graphene oxide. Scanning electron microscopy (SEM) showed that the zinc oxide (ZnO) and cobalt oxide (Co₃O₄) nanoparticles are uniformly distributed over the reduced graphene oxide (rGO) sheets, and the energy-dispersive X-ray spectroscopy (EDS) confirmed the presence of Zn, Co, O, and C. The ZnO/Co₃O₄/rGO-modified electrode was utilized for the electrochemical analysis of L-cysteine, yielding satisfactory results from cyclic voltammetry (CV), differential pulse voltammetry (DPV), and electrochemical impedance spectroscopy (EIS) studies. The sensor was found to respond accurately over a wide range of concentrations from 20 to 800 µM, with a detection limit of 0.01 µM, and it exhibited a high sensitivity of 26.2 µA µM¹ cm². Additionally, it operated at only 0.55 V and exhibited reduced charge transfer resistance; furthermore, it demonstrated exceptional selectivity in interference studies. The actual identification of L-cysteine in the food samples highlights the broader range of nanocomposite applications in clinical and food analysis.

ISSN

0889-1575

Publisher

Elsevier BV

Volume

148

Disciplines

Life Sciences

Keywords

Biomimetic, Biosensor, Electrochemical Sensor, Food Sample Analysis, L-Cysteine, Non-enzymatic

Scopus ID

105014017802

Indexed in Scopus

yes

Open Access

no

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