An Electrochemical Sensor Based on 3D Graphene‐Cyclodextrin Nanohybrid for Enhanced Sensitivity Detection of Nitroaromatic Compounds
Year: 2024
Type: article
Abstract: This study presents an electrochemical sensor for sensitive detection of nitroaromatic compounds using a three‐dimensional (3D) porous graphene with polyoxypropylene supported reduced graphene oxide (PEA‐RGO) and embedded β‐cyclodextrins (β‐CD). First, PEA‐RGO was synthesized by the condensation reaction between graphene oxide (GO) and amino‐terminated polyoxypropylene (PEA), followed by hydrazine hydrate reduction. Then, β‐CD was embedded into the porous of the above 3D graphene to obtain PEA‐RGO/β‐CD nanohybrid. Various characterization techniques, such as microscopy imaging, infrared spectrometry, thermal analysis and electrochemical measurements, were employed to confirm the successful synthesis and unique 3D architecture structure of PEA‐RGO/β‐CD. Afterwards, the glassy carbon electrode (GCE) was modified by PEA‐RGO/β‐CD, and its electrochemical detection performances were investigated for detecting nitroaromatic compounds, including nitrobenzene (NB), 2‐nitroaniline (2‐NA), 2‐chloronitrobenzene (2‐NCB), and 2‐nitrophenol (2‐NP). The results of electrochemical measurements exhibited relative higher sensitivities (1.88 μA/μM/cm2 for NB, 2.13 μA/μM/cm2 for 2‐NA, 2.35 μA/μM/cm2 for 2‐NP, 0.83 μA/μM/cm2 for 2‐NCB, respectively) and lower limits of detection (LOD) (39.4 nM for NB, 44.6 nM for 2‐NA, 75.6 nM for 2‐NP, 69.6 nM for 2‐NCB, respectively). Additionally, the proposed sensor was also applied in detection in real samples with recovery range of 88.13%–109.52 %. The enhanced detecting performances can be attributed to the synergistic effect of the high conductivity from RGO, recognition capabilities from β‐CD, and excellent properties from 3D structure. The present work would provide a robust tool for environmental monitoring and the detection of nitroaromatic pollutants.
Source: Electroanalysis
Authors: Ziao Di, Yu Zhang, Zuhang Ding, Jiayu Huang, Lujia Mao, Hongjun Wei, Jin Zhao
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: bronze
Awards: G1637224667, G558992103, G7634251451
OpenAlex ID: W4401931247
