Ultra-sensitive detection of 4-chloro-2-methylphenoxyacetic acid herbicide using a porous Co-1,4-benzenedicarboxylate /montmorillonite nanocomposite sensor

利用多孔Co-1,4-苯二甲酸/蒙脱石纳米复合传感器对4-氯-2-甲基苯氧乙酸除草剂进行超灵敏检测

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Abstract

The detection of 4-chloro-2-methylphenoxyacetic acid (CMPA) herbicide is crucial due to the potential health risks linked to exposure through drinking water, air, and food, which may adversely affect liver and kidney functions. To address this environmental concern and promote sustainable agriculture, a sensitive carbon paste sensor incorporating a composite material was developed. The composite sensor is based on porous cobalt-1,4-benzenedicarboxylate metal-organic framework and exfoliated montmorillonite nanolayers (Co-OF/MMt). This sensor enables the voltammetric detection of CMPA in real soil samples using linear sweep adsorptive anodic stripping voltammetry (LS-AdASV), facilitating early and accurate monitoring of herbicide levels. The Co-OF/MMt nanocomposite was synthesized via a hydrothermal method involving the precipitation of Co-OF in the presence of MMt. Comprehensive characterization of the synthesized materials was carried out using Fourier transform infrared spectroscopy (FT-IR), X-ray powder diffraction (XRD), scanning electron microscopy (SEM), SEM-Energy dispersive X-ray spectroscopy (SEM-EDX) and surface area analysis (BET). The resulting modified carbon paste sensor, utilizing 1.0% Co-OF/MMt nanocomposite, exhibited superior electrochemical properties compared with the bare carbon paste sensor, possessing an electroactive surface area of 1004.1 m(2)/g with a minimal resistivity (R(ct)) of 330 Ω. Under standard operating conditions, the developed sensor demonstrated detection limits of 0.03 nM and 0.1 nM across two broad linear ranges (0.03 to 0.10 nM - 0.10 to 1.0 nM) and (0.1 to 1.0 nM - 1.0 to 7.0 nM), respectively, for CMPA determination in both bulk and soil samples. These results pointed out the promising electrochemical modified sensor for the direct and simple detection of certain herbicides in environmental matrices, without the need for sample pretreatment steps. This capability supports sustainable development goals by enhancing effective environmental monitoring.

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