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Citation: LIU Hong-Ying, JIN Teng-Fei, DAI Da-Xiang, JIAO Ming-Ru, HUANG Cheng, ZHANG Ming-Zhen, GU Chun-Chuan. Determination of Uric Acid Based on Active Copper-Containing Carbon Nanodots-modified Electrochemical Biosensor[J]. Chinese Journal of Analytical Chemistry, ;2017, 45(8): 1103-1108. doi: 10.11895/j.issn.0253-3820.170201 shu

Determination of Uric Acid Based on Active Copper-Containing Carbon Nanodots-modified Electrochemical Biosensor

1.
College of Life Information Science & Instrument Engineering, Hangzhou Dianzi University, Hangzhou 310018, China;2 Key Laboratory of Medical Information and 3D Bioprinting of Zhejiang Province, Hangzhou Dianzi University, Hangzhou 310018, China;3 Department of Clinical Laboratory, Hangzhou Cancer Hospital, Hangzhou 310002, China

Received Date: 29 March 2017
Revised Date: 8 June 2017

Fund Project: This work was supported by the National Natural Science Foundation of China (No.21405029)

The active copper-containing carbon nanodots were prepared by hydrothermal method, and then characterized by fluorescence spectroscopy and UV-visible absorption spectroscopy. Subsequently, a highly sensitive and selective electrochemical biosensor was fabricated on the basis of this synthesized carbon nanodots with electro-deposition technique. The electrode behavior was investigated by cyclic voltammetry, electrochemical impedance spectroscopy, and differential pulse voltammetry. Furthermore, the catalysis mechanism was studied. The experimental results indicated that the biosensor exhibited a strong electrocatalytic activity toward the oxidation of uric acid (UA). What's more, the interference from ascorbic acid and dopamine was eliminated effectively. Under the optimum conditions, there were linear relationships between the anodic peak current and the concentration of UA (1.00-300.0 μmol/L), and the limit detection was 0.30 μmol/L (S/N=3). The prepared biosensor had advantages such as easy fabrication, strong anti-interference ability, high sensitivity, and wide detection range, and could be used for real sample detection.
- Active copper,
- Carbon nanodots,
- Electrochemistry,
- Biosensor,
- Uric acid
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