Electrochemical nanostructured CuBTC/FeBTC MOF composite sensor for enrofloxacin detection

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 characte...

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Veröffentlicht in:Beilstein journal of nanotechnology 2024-11, Vol.15 (1), p.1522-1535
Hauptverfasser: 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
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Sprache:eng
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Zusammenfassung: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%.
ISSN:2190-4286
2190-4286
DOI:10.3762/bjnano.15.120