Electrocatalytic reduction of nitrofurantoin in biological sample based on assembly of ScMo anchored f-MCNNcs modified GCE

被引:14
作者
Sudha, Karuppaiah [1 ]
Elangovan, Arumugam [1 ]
Senthilkumar, Samuthirarajan [2 ]
Jeevika, Alagan [1 ]
Arivazhagan, Ganesh [3 ]
机构
[1] Thiagarajar Coll, PG & Res Dept Chem, Madurai 625009, Tamil Nadu, India
[2] Jiaxing Univ, Coll Biol Chem Sci & Engn, Nanchang, Jiangxi, Peoples R China
[3] Thiagarajar Coll, PG & Res Dept Phys, Madurai 625009, Tamil Nadu, India
关键词
NFT; ScMo@f-MCNNcs; Selective detection; Coriander leaves; Biological fluids; VOLTAMMETRIC DETERMINATION; CARBON NANOFIBER; ANTIBIOTIC DRUG; WATER; BIOSENSOR; ELECTRODE; OXIDE;
D O I
10.1016/j.microc.2021.106943
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Nitrofurantoin (NFT) is an antibiotic drug, used for urinary infection. Excess intake of NFT drugs may cause severe threats to both animal and human health. Hence, it is very important to develop a hybrid sensor for highly selective identification of NFT in biological samples. Herein, we developed a novel, highly stable hybrid nano structure composite, consists of Sc2Mo3O12 (ScMo) (coriander leaves like structure) decorated functionalized multiwalled carbon nanotubes (f-MCN) by using a simple ultrasonic method (100 W power with 70 kHz). The resulting ScMo@f-MCNNcs (Ncs = Nanocomposite) has an outstanding surface area and high surface to volume ratio, which leads to the sensitive and selective detection of Nitrofurantoin than f-MCN and ScMo. Electrochemical studies of ScMo@f-MCNNcs were carried out by cyclic Voltammetry and Difference Pulse Voltammetry methods. The modified ScMo@f-MCN Ncs/GCE exhibits the wide range of 0.01-180 mu M with the low detection limit of 9.3 nM towards the NFT detection. The synergistic electrocatalytic activity of ScMo@f-MCNNcs modified GCE demonstrates the sensitivity of 0.5136 mu A mu M(-1)cm(-2). In order to explore the realistic applications, synthesized ScMo@f-MCNNcs has also been used to study selectivity, repeatability, reproducibility, and storage stability. In the selectivity, interfering molecules like cationic, anionic, and biological molecules were tested, except NFT, other analytes have not displayed any change in the reduction peak current response, confirms an excellent selectivity of NFT. Additionally, the practical probability was experienced in real samples like, lake water and biological samples, which exhibited good recovery results. The deduced results substantiate that the suggested sensor ScMo@f-MCNNcs/GCE shows outstanding electrochemical performance used for recognition towards the reduction of antibiotic drug NFT.
引用
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页数:11
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