Imprinted polymer/reduced graphene oxide-modified glassy carbon electrode-based highly sensitive potentiometric sensing module for imidacloprid detection

被引:7
|
作者
Kamel, Ayman H. [1 ,2 ]
Abd-Rabboh, Hisham S. M. [3 ]
机构
[1] Ain Shams Univ, Fac Sci, Chem Dept, POB, Cairo 11655, Egypt
[2] Univ Bahrain, Coll Sci, Chem Dept, Sakhir 32038, Bahrain
[3] King Khalid Univ, Fac Sci, Chem Dept, Abha 62529, Saudi Arabia
关键词
Imidacloprid; Potentiometric sensors; Imprinted polymer; Agro-industrial analyses; Method validation; ELECTROCHEMICAL DETERMINATION; SELECTIVE ELECTRODES; ION; SAMPLES; NEONICOTINOIDS; FLUORESCENCE; MEMBRANES; SENSOR;
D O I
10.1016/j.microc.2023.109789
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
A sensitive and highly selective potentiometric sensor for imidacloprid detection (IMD) is presented. Reduced graphene oxide (rGO) was used to modify a glassy carbon electrode in the fabrication of this sensor. The rGO is coated with IMD molecularly imprinted polymer (MIP), which serves as a sensing compound for herbicide recognition. Under ideal circumstances, a linear range of 0.5 mu M-1.0 mM was measured, with a detection limit of 0.2 mu M IMD. The method exhibits great selectivity towards the IMD's determination, according to the examination of the effects of potentially interfering species. For the direct potentiometric detection of IMD in several pesticide formulation samples, the assay method has been validated and shown to be adequate. The obtained recovery ranges from 94.5 to 106.4 % of the nominal or spiked concentration, with a mean relative standard deviation of 1.3 %. The applicability outcomes of using the presented sensor were contrasted with those attained by high-performance liquid chromatography (HPLC). There was no discernible difference between the suggested and HPLC procedures. Due to the sensitive membrane's and the liquid junction's proximity, this module's use permits applications with a small sample volume. The proposed sensor's effectiveness in a complicated matrix points to applications for rapid detection and tests for quality assurance and control in the agro-industry.
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页数:9
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