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Simultaneous Determination of Dihydroxybenzene Isomers at Nitrogen-Doped Graphene Surface Using Fast Fourier Transform Square Wave Voltammetry and Multivariate Calibration Publisher



Moghaddam MR1, 2 ; Ghasemi JB2 ; Norouzi P1, 3 ; Salehnia F2, 4
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Authors Affiliations
  1. 1. Center of Excellence in Electrochemistry, University of Tehran, Tehran, Iran
  2. 2. Faculty of Chemistry, University of Tehran, Tehran, Iran
  3. 3. Endocrinology & Metabolism Research Center, Tehran University of Medical Sciences, Tehran, Iran
  4. 4. SivanCell, Alborz University of Medical Sciences, Alborz, Iran

Source: Microchemical Journal Published:2019


Abstract

In this paper, a highly sensitive electrochemical method, which is based on the combination of fast Fourier transform square wave voltammetry and multivariate calibration techniques, was developed for simultaneous determination of dihydroxybenzene positional isomers, including catechol, hydroquinone, and resorcinol, in environmental samples. An electrochemical sensor was constructed by the deposition of nitrogen-doped graphene on a glassy carbon electrode to apply as a new approach for the multicomponent analysis. Partial least squares was applied, as a multivariate calibration method, to deconvolute the highly overlapping electrochemical signals from the analytes. Using the simplex experimental design with the degree of 4, 19 ternary mixture solutions of the cited analytes were prepared in the established linear ranges of the analytes. The developed multivariate model was validated by predicting the concentration of 8 independent solutions. The root mean square error values of validation values were between 0.04230 and 0.06549 μM, respectively. The applicability of the proposed method was checked using water samples (collected from both the surface and waste water) and human urine, and the obtained recovery values were between 89.3 and 107.1%. The limits of detection and relative standard deviations for catechol, hydroquinone, and resorcinol were 0.046, 0.046, and 0.045 μM, and 3.6, 3.4 and 3% (N = 5), respectively. © 2018 Elsevier B.V.
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