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Exploiting the pH-responsive behavior of zinc-dithizone complex for fluorometric urea sensing utilizing red-emission carbon dots

Research Authors
Khalid Alhazzani, Ahmed Z. Alanazi , Aya M. Mostafa , James Barker, Hossieny Ibrahim, Mohamed M. El-Wekil , Al-Montaser Bellah H. Ali
Research Date
Research File
Research Journal
Microchemical Journal
Research Publisher
ElSevier
Research Vol
204
Research Website
https://www.sciencedirect.com/science/article/pii/S0026265X24012414
Research Year
2024
Research Abstract

This study develops a novel fluorometric method for the sensitive and selective determination of urea, based on unique system comprising nitrogen doped red-emissive carbon dots (NRECDs), zinc-dithizone complex, and the urease enzyme. The underlying principle of this method relies on the pH increase resulting from the enzymatic breakdown of urea by urease. Initially, the fluorescence of the NRECDs is quenched by the red-colored zinc-dithizone complex. However, upon the addition of urea, the subsequent release of ammonia and the consequent rise in pH lead to the dissociation of the zinc-dithizone complex, causing a color change from red to yellow. This spectral shift eliminates the quenching effect, resulting in the restoration of the CDs’ fluorescence. The prepared NRECDs were comprehensively characterized using various spectroscopic techniques, including fluorometry, X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), UV–visible spectroscopy, and transmission electron microscopy (TEM) imaging. The proposed fluorometric method exhibits excellent sensitivity (Limit of detection = 0.0012 mM) and linearity (R2 = 0.9951) in the determination of urea. Notably, this approach addresses the selectivity limitations of previous pH-sensitive CDs-based methods, which relied solely on the intrinsic response of CDs, lacking specificity in either quenching or fluorescence enhancement. Furthermore, the developed method demonstrates remarkable selectivity, as evidenced by negligible interference from various potentially interfering substances, ensuring reliable and accurate urea quantification. When applied to human serum samples, the method showcased excellent recovery with low relative standard deviations, highlighting its practical applicability in biomedical and clinical applications.