Determination of uric acid in clinical samples using screen-printed carbon electrode assemblies modified with graphene/ZrO2/GQDs polymeric film

A novel electrochemical sensor was developed for the determination of uric acid (UA) by modifying a screen-printed carbon electrode (SPCE) with a graphene/zirconium dioxide/graphene quantum dots (graphene/ZrO2/GQDs) nanocomposite. The physicochemical properties of the synthesized nanocomposite were...

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Bibliographic Details
Published in:Results in Chemistry
Main Authors: Qiang Zhou, Dong Chang, Hongzhi Pan
Format: Article
Language:English
Published: Elsevier 2025-09-01
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Online Access:http://www.sciencedirect.com/science/article/pii/S2211715625005107
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Summary:A novel electrochemical sensor was developed for the determination of uric acid (UA) by modifying a screen-printed carbon electrode (SPCE) with a graphene/zirconium dioxide/graphene quantum dots (graphene/ZrO2/GQDs) nanocomposite. The physicochemical properties of the synthesized nanocomposite were systematically characterized using transmission electron microscopy (TEM), X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FT-IR), and electrochemical impedance spectroscopy (EIS). The sensor's electrocatalytic performance was optimized, revealing that a graphene:ZrO2:GQDs ratio of 1:1:1 yielded the highest activity towards UA oxidation. The optimal voltammetric response was achieved in a 0.1 M phosphate buffer solution (PBS) at pH 6.5. Under these optimized conditions, the sensor exhibited a wide linear detection range for UA from 20 to 500 μM with a high correlation coefficient (R2 = 0.997). The limits of detection (LOD) and quantification (LOQ) were calculated to be 1.07 μM and 3.55 μM, respectively. Interference studies confirmed the sensor's excellent selectivity against common co-existing species. The practical applicability of the sensor was successfully demonstrated by quantifying UA in human serum samples, yielding satisfactory recovery rates. This work presents a robust and sensitive platform for UA analysis with significant potential for clinical applications.
ISSN:2211-7156