A Magnetite Composite of Molecularly Imprinted Polymer and Reduced Graphene Oxide for Sensitive and Selective Electrochemical Detection of Catechol in Water and Milk Samples: An Artificial Neural Network (ANN) Application

Abstract

A stable and more selective electrochemical sensor for catechol (CC) detection at magnetic molecularly imprinted polymer modified with green reduced graphene oxide modified glassy carbon electrode (MIP/rGO@Fe3O4/GCE) was fabricated. Two steps have been applied to achieve the imprinting process: (1) adsorption of CC on the surface of the polypyrrole (Ppyr) during the polymerization of pyrrole and (2) the green extraction of the template (CC) from the mass produced. Hence, the present paper doesn’t present the first use of MIP technology for CC identification but rather a new extraction process. The MIP/rGO@Fe3O4/GCE was characterized by voltammetry techniques and exhibited a wide linear range from1 to 50 µM of CC while the detection limits were estimated to be around 4.18 nM CC and a limit of quantification in the range of 12.69 nM CC. Furthermore, the prepared MIP based sensor provided outstanding electroanalytical performance, including high selectivity, stability, repeatability, and reproducibility. For accurate estimation of CC concentrations, an artificial neural network was developed based on the findings. The MIP/rGO@Fe3O4/GCE exhibits excellent stability with a very important selectivity and sensitivity. The analytical testing of modified electrode has been analyzed in water and commercial milk samples and provided adequate recoveries.

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