• 文献标题:   A novel flow injection amperometric sensor based on carbon black and graphene oxide modified screen-printed carbon electrode for highly sensitive determination of uric acid
  • 文献类型:   Review
  • 作  者:   REANPANG P, MOOLAMKHA P, UPAN J, JAKMUNEE J
  • 作者关键词:   carbon black, graphene oxide, screenprinted carbon electrode, flow injection, amperometry, uric acid
  • 出版物名称:   TALANTA
  • ISSN:   0039-9140 EI 1873-3573
  • 通讯作者地址:  
  • 被引频次:   12
  • DOI:   10.1016/j.talanta.2021.122493 EA MAY 2021
  • 出版年:   2021

▎ 摘  要

A simple, rapid, and cost-effective flow injection amperometric (FI-Amp) sensor for sensitive determination of uric acid (UA) was developed based on a new combination of carbon black (CB) and graphene oxide (GO) modified screen-printed carbon electrode (SPCE). The CB-GO nanocomposites were simply synthesized and modified on the working electrode surface to increase electrode conductivity and enhance the sensitivity of UA determination via the electrocatalytic activity toward UA oxidation. The morphologies and electrochemical properties of the synthesized nanomaterials were investigated through scanning electron microscopy (SEM), transmission electron microscopy (TEM), electrochemical impedance spectroscopy (EIS), and cyclic voltammetry (CV). The modified electrode was incorporated with FI-Amp to improve UA detection's sensitivity, stability, and automation. Some parameters affecting sensitivity were optimized, including pH of the electrolyte solution, applied potential, amount of CB-GO suspension, flow rate, injection volume, and reaction coil length. Using an applied potential of +0.35 V (vs Ag/AgCl), the anodic current was linearly proportional to UA concentration over the range of 0.05-2000 mu M with a detection limit of 0.01 mu M (3 S/N). Besides, the developed method provides a sample throughput of 25 injections h 1, excellent sensitivity (0.0191 mu A/mu M), selectivity, repeatability (RSD 3.1%, n = 7), and stability (RSD 1.08%, n = 50). The proposed system can tolerate potential interferences commonly found in human urine. Furthermore, a good correlation coefficient between the results obtained from the FI-Amp sensor and a hospital laboratory implies that the proposed system is accurate and can be utilized for UA detection in urine samples.