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ZnO hollow spheres arrayed molecularly-printed-polymer based selective electrochemical sensor for methyl-parathion pesticide detection

Title
ZnO hollow spheres arrayed molecularly-printed-polymer based selective electrochemical sensor for methyl-parathion pesticide detection
Author(s)
Daizy, M.Ali, M.R.Bacchu, M.S.Aly, Mohamed Aly SaadKhan, M.Z.H.
Issued Date
2021-11
Citation
Environmental Technology and Innovation, v.24, no.101847
Type
Article
Author Keywords
L-ArgMethyl-parathionMolecularly imprinted polymerZnO hollow spheresElectrochemical sensorGlassy carbon electrode
Keywords
ELectrochemical detectionElectrochemical sensingGlassy carbon electrodesMethyl-parathion pesticidesMolecularly imprintedMolecularly Imprinted PolymerOptimal conditionsElectrochemical sensorsArginineChemical detectionCyclic voltammetryElectropolymerizationGlass membrane electrodesII-VI semiconductorsOxide mineralsSynthesis (chemical)Zinc oxideDifferential pulse voltammetry
ISSN
2352-1864
Abstract
A highly sensitive electrochemical-based detector was fabricated to selectively sense methyl-parathion (MP). A Glassy carbon electrode (GCE) was functionalized with zinc oxide (ZnO) hollow spheres (ZnOHS) and a molecularly imprinted polymer (MIP) to form the developed sensor. Cyclic voltammetry (CV) was performed to synthesize a molecularly imprinted polymeric film on the ZnOHS modified GCE (GCE/ZnOHS) by electropolymerization of functional monomer, l-arginine (L-Arg), and template molecule, MP. The differential pulse voltammetry (DPV) was utilized to evaluate the efficiency of the electrochemical detection of MP under optimal conditions by the proposed sensor. The developed sensor recorded a good performance for detecting MP in the linear range of 5 × 10−9 to 0.1 × 10−4 mol L−1 (R2=0.985) with a detection limit (S/N = 3) of 0.5 × 10−9 mol L−1 and sensitivity of 571 nA/μmolL −1 cm −2. This electrochemical sensing system effectively detects MP in real samples with satisfactory recoveries of 90.4%, 91.9%, 118%, and 96.3% for fresh green beans, strawberry, tomato, and cabbage, respectively. © 2021 Elsevier B.V.
URI
http://hdl.handle.net/20.500.11750/15577
DOI
10.1016/j.eti.2021.101847
Publisher
Elsevier BV
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Appears in Collections:
ETC 1. Journal Articles

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