4.7 Article

Au nanoparticles @metal organic framework/polythionine loaded with molecularly imprinted polymer sensor: Preparation, characterization, and electrochemical detection of tyrosine

期刊

出版社

ELSEVIER SCIENCE SA
DOI: 10.1016/j.jelechem.2020.114052

关键词

Molecularly imprinted polymer; Dual-signal; ZIF-67; Polythionine; Tyr; Electrochemical sensor

资金

  1. Key Basic Research Program of the Sichuan Provincial Education Commission, P. R. China [10ZB034]
  2. Basic Research Program of the Science & Technology Department of Sichuan Province, P. R. China [2011ZR0067]
  3. National Natural Science Foundation of China, P. R. China [21607109]
  4. Sichuan science and technology plan project of International Cooperation, P. R. China [2016HH0081]
  5. Sichuan Agricultural University for talent, P. R. China [03120313]

向作者/读者索取更多资源

In this study, a new dual-signal electrochemical sensor using a glassy carbon electrode (GCE) modified with molecularly imprinted polyaniline/polythionine/gold nanoparticles@zeolitic imidazolate framework-67 composite (MIP/ pTH/Au@ZIF-67) is fabricated for the quantitative analysis of tyrosine (Tyr). Au@ZIF-67 is used as a matrix to improve the surface area and electron-transfer ability of the sensor. The pTH as a built-in probe provides a signal-off response, meanwhile the oxide current of Tyr acts as a signal-on response. TheMIP is prepared in the presence of aniline monomer and Tyr template by electro-polymerization for Tyr specific recognition. Under the optimized conditions, the sensor demonstrates a linear range from 1 x 10(-8) M to 4 x 10(-6) M for Tyr determination and a limit of detection (LOD) of 7.9 x 10(-10) M (S/N = 3). Furthermore, the sensor exhibits excellent selectivity, superior stability and good reproducibility toward Tyr. More importantly, the sensor is successfully employed to detect Tyr in human serum with satisfactory recoveries. (C) 2020 Elsevier B.V. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据