Improved electroanalytical characteristics for the determination of pesticide metobromuron in the presence of nanomaterials

In the present work, bare ultra trace graphite electrode (UTGE), UTGE modified with multi-walled carbon nanotubes (UTGE-MWCNTs), and UTGE modified with graphene nanoplatelets (UTGE-GNPs) were considered as working electrodes. For the first time, the UTGEs were modified with MWCNTs and GNPs by simple and fast drop-casting approach (the whole procedures take no more times than ca. 30 min). The comprehensive microscopic and electrochemical characterization of the unmodified and the modified UTGEs was conducted by means of atomic force microscopy (AFM), electrochemical impedance spectroscopy (EIS), and cyclic voltammetry (CV) techniques. The prepared electrodes were further applied for the analytical purposes, and the procedures for the square-wave voltammetric (SWV) determination of pesticide metobromuron (Mbn) using the bare UTGE, the UTGE-MWCNTs, and the UTGEe-NPs were developed. For the first time, this compound was electrochemically investigated. The SWV measurements were performed in Britton-Robinson buffer (B-R) solution at pH 2.0 as a supporting electrolyte. SWV parameters, i.e. amplitude, frequency, and step potential, were optimized. The linear relationships between peak current vs. increasing concentrations of Mbn were defined using the bare UTGE, the UTGE-MWCNTs, and the UTGE-GNPs, and the limits of detection were calculated (0.13, 0.11, 0.048 mmol L-1, respectively). The analytical parameters determined from calibration curves indicate similar sensitivity on all tested electrodes, however, the widest linearity range as well as the lowest LOD and LOQ values were achieved on the UTGE modified with GNPs. The utility of the proposed method with the UTGE-GNPs was verified by the quantitative analysis of Mbn in soil samples with satisfactory results (recovery of 99.1%). Furthermore, the impact of possible interferences was tested and evaluated, and obtained results proved good selectivity of the proposed method. (C) 2018 Elsevier B.V. All rights reserved.