Nguyen Thi Kim Ngan, Doan Tien Dat, Luu Huy Hieu, Nguyen Hoang Anh, Vu Thi Thu Ha, Tran Quang Hai, Nguyen Ha Tran, Dang Thanh Binh, Pham Thi Hai Yen, Hoang Mai Ha
Graduate University of Science and Technology, Viet Nam Academy of Science and Technology, Ha Noi, Vietnam.
Faculty of Chemistry, TNU-University of Sciences, Tan Thinh Ward, Thai Nguyen City, Vietnam.
Beilstein J Nanotechnol. 2024 Nov 28;15:1522-1535. doi: 10.3762/bjnano.15.120. eCollection 2024.
A novel electrochemical sensor for the detection of enrofloxacin (ENR) in aqueous solutions has been developed using a carbon paste electrode modified with a mixture of metal-organic frameworks (MOFs) of CuBTC and FeBTC. These MOFs were successfully synthesized via a solvothermal method and characterized using various techniques, including X-ray diffraction, Fourier-transform infrared spectroscopy, Brunauer-Emmett-Teller analysis, and X-ray photoelectron spectroscopy. The MOF mixture exhibited a particle size ranging from 40 to 100 nm, a high surface area of 1147 m/g, a pore volume of 0.544 cm/g, and a capillary diameter of 1.50 nm. Additionally, energy-dispersive X-ray mapping demonstrated the uniform distribution of the two MOFs within the electrode composition. The synergistic effect of the electrocatalytic properties of CuBTC and the high conductivity of FeBTC significantly enhanced the electrochemical response of ENR, increasing the signal by more than ten times compared to the unmodified electrode. Under optimal analytical conditions, the sensor exhibited three dynamic ranges for ENR detection, that is, 0.005 to 0.100 µM, 0.1 to 1.0 µM, and 1 to 13 µM, with coefficients of determination of 0.9990, 0.9954, and 0.9992, respectively, depending on the accumulation duration. The sensor achieved a low detection limit of 3 nM and demonstrated good reproducibility, with a relative standard deviation of 3.83%. Furthermore, the sensor demonstrated effective performance in analysing tap and lake water samples, with recovery rates ranging from 90.2% to 121.3%.
一种用于检测水溶液中恩诺沙星(ENR)的新型电化学传感器已被开发出来,该传感器使用了由CuBTC和FeBTC的金属有机框架(MOF)混合物修饰的碳糊电极。这些MOF通过溶剂热法成功合成,并使用包括X射线衍射、傅里叶变换红外光谱、布鲁诺尔-埃米特-泰勒分析和X射线光电子能谱等各种技术进行了表征。该MOF混合物的粒径范围为40至100 nm,具有1147 m/g的高比表面积、0.544 cm/g的孔体积和1.50 nm的毛细管直径。此外,能量色散X射线映射表明两种MOF在电极组成中均匀分布。CuBTC的电催化性能与FeBTC的高导电性之间的协同效应显著增强了ENR的电化学响应,与未修饰电极相比,信号增加了十多倍。在最佳分析条件下,该传感器对ENR检测呈现三个动态范围,即0.005至0.100 µM、0.1至1.0 µM和1至13 µM,根据累积持续时间,测定系数分别为0.9990、0.9954和0.9992。该传感器实现了3 nM的低检测限,并表现出良好的重现性,相对标准偏差为3.83%。此外,该传感器在分析自来水和湖水样品时表现出有效性能,回收率范围为90.2%至121.3%。