This paper presents a novel electrochemical sensor fabricated with a nanoarchitecture composed of sphere-like samarium vanadate nanoparticles anchored onto graphene nanosheets (SmVO4 -GNSs or SVG). Accurate detection of nitrofurantoin (NFT), an effective antibiotic used for urinary tract infections, is critical due to its severe pulmonary toxicity and other adverse side effects at high levels in the human body. To achieve ultra-trace levels of detection, pristine SmVO4 nanoparticles synthesized via co-precipitation were combined with h ighly conductive graphene nanosheets. The optimized SVG-2 nanocomposite significantly amplifies the reduction signals of NFT, showcasing high sensitivity and reliability in complex matrices.

Graphical abstract.

Technology Overview
The sensor utilizes SmVO4 nanoparticles prepared through a facile co-precipitation method, sintered at 550 °C to optimize crystallinity and uniform sphere-like morphology. These nanoparticles are subsequent incorporated with carbon-based graphene nanosheets (GNSs) via an ultra-sonication dispersion method. The synergistic interaction between the conductive GNSs and the electrocatalytic SmVO4 drastically reduces charge transfer resistance Rct, enabling highly efficient electron mobility for the reduction of target biomolecules.

Applications & Benefits
The primary application lies in clinical diagnostics and environmental monitoring for real-time trace determination of antibiotics. Specifically, the fabricated SVG-2 sensor efficiently detects toxic NFT in biological fluids such as human blood serum and urine samples. Its ultimate benefits include an exceptional linear range (0.035-672.3 μM), ultra-low detection limits (0.0087 μM), high anti-interference capability against common biomolecules/ions, and cost-effective operational stability.

Abstract：
In recent times rare earth metal vanadate (REVO) has received a lot of attention in the research of electrocatalysts. Accordingly, we construct a novel fabrication strategy nanoarchitecture for an electrochemical sensor. In addition, the highly effective nitrofurantoin (NFT) antibiotic drug is mainly used for the treatment of urinary tract infections. However, when the level of NFT use in the human body increases, the pulmonary develops toxic and many side effects. Hence, the detection of NFT in biological fluids is much important. This electrochemical detection approach is a better way to detect the NFT precisely. Herein, the pristine samarium vanadate nanoparticles (SV NPs) synthesized were Co-precipitation method. The collected sample was sintered at 450, 550, and 650 °C (denoted as SV-1, SV-2, SV-3). The above-mentioned samples were incorporated with graphene nanosheets (GNSs) through an ultra-sonication method to obtained SmVO4-GNSs (SVG) nanocomposites namely (SVG-1, SVG-2, SVG-3), which were utilized for various analytical, spectroscopic and microscopic techniques. Interestingly, the as-prepared SVG-2/GCE was demonstrated an enhanced the electrochemical activity due to the synergetic effect between SV-2 and GNSs, which significantly enhanced the reduction signal of NFT. Thereby, SVG-2/GCE has exhibited a good linear range (0.035–672.3 μM), good sensitivity (0.875 μA μA−1 cm−2) with a limit of detection (0.0087 μM). The anti-interference ability, good sensitivity, and operational stability were performed in the proposed electrode. The SVG-2 modified RRD electrode was capable of detecting NFT in blood serum and human urine samples in real-time monitoring analysis. These electrochemical tests were revealed an entirely new perspective on the electrocatalytic activity as well as outstanding amplification results at ultra-trace levels.

Construction of sphere like samarium vanadate nanoparticles anchored graphene nanosheets for enhanced electrochemical detection of nitrofurantoin in biological fluids
Author：Babulal Sivakumar Musuvadhi, Koventhan Chelliah, Chen Shen Ming, Hung Weisen
Year：2022
Source publication： Composites Part B: Engineering, Volume 237, 15 May 2022, 109847
Subfield Highest percentage： 99% Industrial and Manufacturing Engineering #2/355

https://www.scopus.com/pages/publications/85128216951?origin=resultslist