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Multivariate cathodic square wave stripping voltammetry optimization for nitro group compounds determination using antimony film electrodes

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Abstract The main goal of this paper is the optimization of the square wave voltammetric response of antimony film electrode (SbFE) to determine reducible nitro groups using response surface methodology… Click to show full abstract

Abstract The main goal of this paper is the optimization of the square wave voltammetric response of antimony film electrode (SbFE) to determine reducible nitro groups using response surface methodology (RSM). The SbFE was prepared on a glassy carbon electrode (GCE) while cathodic stripping square wave voltammetry (CSSWV) was used as detection technique. In this study, the optimization process of solution pH and 4,6-dinitro-o-cresol (DNOC) accumulation time was carried out using a Central Composite Design (CCD) while a Box–Behnken Design for SWV instrumental variables optimization. The two reduction current peaks were used as dependent variable to evaluate the performance of the system. For solution pH and DNOC accumulation time the optimization process considered only reduction current peak, while for SWV instrumental parameters (step, amplitude and frequency) both the relationship between current peak and standard deviation with the different factors were analysed, finally both designs were quantitatively described by a multivariate regression model through the RSM. Furthermore, the optimal parameter combinations were obtained by maximizing the reduction current peak and minimizing standard deviation within the studied experimental range. Under the optimal parameter combination, a linear calibration curve ranged from (1.0 to 15) × 10−6 mol L−1 with a detection limit of 1.12 × 10−6 mol L−1 was obtained. The proposed analytical procedure was further applied to detect DNOC in natural water samples with satisfactory results.

Keywords: reduction current; antimony film; optimization; square wave; voltammetry

Journal Title: Microchemical Journal
Year Published: 2018

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