4.7 Article

Graphitic carbon nitride nanosheets modified multi-walled carbon nanotubes as 3D high efficient sensor for simultaneous determination of dopamine, uric acid and tryptophan

Journal

JOURNAL OF ELECTROANALYTICAL CHEMISTRY
Volume 780, Issue -, Pages 147-152

Publisher

ELSEVIER SCIENCE SA
DOI: 10.1016/j.jelechem.2016.09.004

Keywords

Multi-walled carbon nanotubes; Graphitic carbon nitride; Dopamine; Uric acid; Tryptophan

Funding

  1. Chongqing Municipal Education Commission [KJ1501404]
  2. Chongqing Engineering Research Center [cstc2015yfpt_gcjsyjzx0027]
  3. Program for Innovative Research Team in Chongqing University of Education [KYC-cxtd03-20141002]

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Graphitic carbon nitride (g-C3N4) nanosheets, as graphene-like ultrathin semiconductor material, have strong covalent bonds between carbon and nitride atoms. The nitrogen atoms doping in the carbon architecture that greatly enhancing electrical properties and accelerating the electrontransfer rate, which can improve the electrical properties of g-C3N4 nanosheets. Herein, a novel electrochemical sensor was developed by immobilizing a three-dimensional (3D) hybrid nanocomposite which consisted of one-dimensional (1D) multi-walled carbon nanotubes (MWNTs) and two-dimensional (2D) g-C3N4 nanosheets on a glassy carbon electrode (g-C3N4/MWNTs/GCE). The g-C3N4/MWNTs/GCE exhibited excellent response toward the oxidation reactions of dopamine (DA), uric acid (UA) and tryptophan (Trp). Under the optimum conditions, the electrochemical sensor was used in the detection of DA, UA and Trp, and achieved wide ranges of 2.0-43.5 mu M, 5.0-189.0 mu M and 65.0-1815.0 mu M with low detection limits (S/N = 3) of 5.0 x 10(-8) M, 5.0 x 10(-7) M and 1.0 x 10(-6) M, respectively. In addition, the coexistence of ascorbic acid (AA) has no obvious interference toward the detection of DA, UA and Trp. Thus, the modified electrodes were successfully applied for the determination of DA, UA and Trp in urine and serum samples using the standard adding method with satisfactory results. (C) 2016 Elsevier B.V. All rights reserved.

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