4.7 Article

Electrochemical sensor for dopamine based on imprinted silica matrix-poly(aniline boronic acid) hybrid as recognition element

Journal

TALANTA
Volume 159, Issue -, Pages 379-386

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.talanta.2016.06.048

Keywords

Molecularly imprinted polymer; Dopamine; 3-Aminophenylboronic acid; Silica matrix; Hybrid

Funding

  1. National Natural Science Foundation of China [21075098]
  2. Scientific Research Foundation of Shaanxi Provincial Key Laboratory [15JS098]
  3. State Key Laboratory of Analytical Chemistry for Life Science [SKLACLS1301]

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A novel imprinted silica matrix-poly(aniline boronic acid) hybrid for electrochemical detection of dopamine (DA) was developed. Boronic acid functionalized conducting polymer was electrochemically prepared on Au electrode. The number of covalent binding sites toward DA templates was controlled by potential cycles. A precursory sol solution of ammonium fluorosilicate (as cross-linking monomer) containing DA was spin-coated on the polymer modified electrode. Under NH3 atmosphere, the hydroxyl ions were generated in the solution and catalyzed the hydrolysis of fluorosilicate to form silica matrix. After this aqueous sol-gel process, an inorganic framework around the DA template was formed and the imprinted hybrid for DA was also produced. As revealed by scanning electron microscopy, UV-vis spectroscopy and cyclic voltammetry characterization, DA was embedded in the imprinted hybrid successfully. The affinity and selectivity of the imprinted hybrid were also characterized by cyclic voltammetry. The imprinted hybrid showed higher affinity for DA than that for epinephrine, and little or no affinity for ascorbic acid and uric acid due to the combined effects of covalent interaction, cavities matching and electrostatic repulsion. The imprinted hybrid sensor exhibited a quick response (within 5 min) to DA in the concentration range from 0.05 to 500 mu mol L-1 with a detection limit of 0.018 mu mol L-1. The prepared sensor was also applied to detect DA in real samples with a satisfactory result. (C) 2016 Elsevier B.V. All rights reserved.

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