Polypyrrole-MXene supported gold nanoparticles for the trace-level detection of nitrofurantoin

聚吡咯 材料科学 玻璃碳 介电谱 聚合 纳米颗粒 化学工程 胶体金 电化学 电极 循环伏安法 纳米技术 化学 聚合物 复合材料 物理化学 工程类
作者
A.T. Ezhil Vilian,Seung‐Kyu Hwang,Gokul Bhaskaran,Munirah Alhammadi,Suheon Kim,Jitendra N. Tiwari,Yun Suk Huh,Young‐Kyu Han
出处
期刊:Chemical Engineering Journal [Elsevier]
卷期号:454: 139980-139980 被引量:34
标识
DOI:10.1016/j.cej.2022.139980
摘要

High usage of nitrofurantoin (NFT) has resulted in unacceptable levels in water and foods with negative impacts on animals, humans, and surrounding ecosystems. The accurate and ultra-low sensing of NFT in waterways presents a significant societal challenge. To address this issue, gold nanoparticles (AuNPs) were integrated into polypyrrole (PPy) on Titanium carbide MXene (Ti3C2Tx) using a simple sonochemical route involving the in-situ, oxidant-free polymerization of pyrrole monomer in the presence of HAuCl4. The AuNP-PPy-MXene composite produced was used to modify a glassy carbon electrode (GCE) to construct an ultrasensitive electrochemical sensor for the direct and on-site sensing of NFT in complex samples. Electrochemical impedance spectroscopy (EIS) investigations showed Au-PPy-MXene-GCEs had a heterogeneous electron transfer rate constant (k°) of 1.03 × 10-2 cm s−1 and a lower charge-transfer resistance (Rct = 73 Ω) than Au-MXene, Au-PPy, and PPy-MXene GCEs. In addition, Au-PPy-MXene-GCE exhibited better electrocatalytic reduction performance at a higher cathodic signal intensity and a lower reduction overpotential of −0.38 V (vs Ag/AgCl) for NFT than Au-MXene, Au-PPy, and PPy-MXene GCEs. The fabricated sensor had a wide linear range from 6 to 172 nM (measured at −0.38 V vs Ag/AgCl), an ultra-low detection limit (LOD) of 0.26 nM (at S/N = 3), and an excellent sensitivity of 6.4121 μA nM−1 cm−2 for the electroreduction of NFT. Au-PPy-MXene-GCE also provided specific and accurate amperometric analysis for NFT in the presence of cationic, anionic, and other potentially interfering pesticides. The practicality of the sensor was tested to quantify NFT at trace levels in complex matrices (honey, pond water, and hospital wastewater samples), and achieved recoveries ranging between 97.6 % and 113.2 % and a relative standard deviation of<3.6 %.
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