Fabrication non-enzymatic electrochemical sensor based on methyl red and graphene oxide nanocomposite modified carbon paste electrode for determination of nitrite in food samples
The purpose of this work was to create a non-enzymatic electrochemical sensor based on methyl red and modified carbon paste electrodes (MR/GO/CPE) that can measure nitrite in food samples. FE-SEM images showed that the assembly of MR on the surface of GO nanosheets caused the combination of GO nanos...
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Published in | International journal of electrochemical science Vol. 18; no. 6; p. 100097 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
Elsevier B.V
01.06.2023
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Subjects | |
Online Access | Get full text |
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Summary: | The purpose of this work was to create a non-enzymatic electrochemical sensor based on methyl red and modified carbon paste electrodes (MR/GO/CPE) that can measure nitrite in food samples. FE-SEM images showed that the assembly of MR on the surface of GO nanosheets caused the combination of GO nanosheets and MR particles to form a MR/GO nanocomposite with a high density of holes and crevasses. Amperometry, CV, and DPV techniques were used to study the electrochemical responses of MR/GO/CPE to the determination of nitrite. The results revealed that the MR/GO/CPE demonstrated sensitive, selective, and stable responses to determination nitrite. According to amplitude studies, the proposed nitrite sensor should have a sensitivity value of 0.12735 μA/μM, a large linear range of 0–7000 μM, and a low detection limit value of 0.011 μM. In the current study, the accuracy and applicability of the proposed nitrite electrochemical sensor for the determination of nitrite in prepared meat specimens were examined. The results showed good recovery values (more than 96.00 %) and appropriate precision (RSD less than 5.10 %), as well as good agreement between the amperometric measurements and the Test Kit for Nitrate assays. These findings demonstrated that MR/GO/CPE can be used as trustworthy nitrite sensors for tracking nitrite levels in food specimens. |
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ISSN: | 1452-3981 1452-3981 |
DOI: | 10.1016/j.ijoes.2023.100097 |