In situ synthesis of polythiophene encapsulated 2D hexagonal boron nitride nanocomposite based electrochemical transducer for detection of 5-fluorouracil with high selectivity†
Abstract
It is difficult for the scientific community to develop a nonenzymatic sensing platform for extremely sensitive and selective detection of specific biomolecules, antibiotics, food adulterants, heavy metals, etc. One of the most significant chemotherapy drugs, 5-fluorouracil (5-Fu), which is used to treat solid malignancies, has a fluorine atom in the fifth position of the uracil molecule. Recognizing the secure and effective dosing of drugs for chemotherapy continues to be a critical concern in cancer disease management. The maintenance of the optimal 5-Fu concentration is dependent on the presence of 5-Fu in biofluids. Herein we reported a conducting polymer encapsulated 2D material, PTh/h-BN for the efficient electrochemical detection of anticancer drug 5-Fu. Furthermore, the synthesized PTh/h-BN nanocomposite was confirmed by the High-Resolution Transmission Electron Microscope (HR-TEM), High-Resolution Scanning Electron Microscope (HR-SEM), X-ray diffraction (XRD), and Fourier-Transform Infrared Spectroscopy (FT-IR). The electrical resistance of PTh/h-BN modified GCE and its sensing performance towards 5-Fu were tested using Electrochemical Impedance Spectroscopy (EIS) and Cyclic Voltammetry (CV) studies respectively. The analytical performance of our proposed catalyst was tested using Differential Pulse Voltammetry (DPV), and the amperometry (i–t curve) method. From the results, our proposed PTh/h-BN nanocomposite-modified GCE shows enhanced sensing performance due to higher redox peak currents, large active surface area, and high electrical conductivity. Moreover, the nanohybrid shows enhanced sensing performances with quick response time, wide linear range, the lowest limit of detection, high sensitivity, and high selectivity in the presence of various interferents. Finally, the practical applicability of the proposed sensor was tested with real-world samples with very good recovery percentages.