Suppr超能文献

使用多壁碳纳米管/4-氨基苯磺酸膜修饰玻碳电极灵敏伏安法测定酪氨酸

Sensitive voltammetric determination of tyrosine using multi-walled carbon nanotubes/4-aminobenzeresulfonic acid film-coated glassy carbon electrode.

作者信息

Huang Ke-Jing, Luo Ding-Fa, Xie Wan-Zhen, Yu Yong-Sheng

机构信息

College of Chemistry and Chemical Engineering, Xinyang Normal University, Xinyang 464000, PR China.

出版信息

Colloids Surf B Biointerfaces. 2008 Feb 15;61(2):176-81. doi: 10.1016/j.colsurfb.2007.08.003. Epub 2007 Aug 9.

Abstract

A chemically modified electrode is constructed based on the multi-walled carbon nanotubes (MWNTs)/4-aminobenzeresulfonic acid (4-ABSA) film-coated glassy carbon electrode. The electrocatalytic oxidation of tyrosine (Tyr) is investigated on the surface of the MWNTs/4-ABSA-modified electrode using cyclic voltammetry (CV) and differential pulse voltammetry (DPV). The prepared modified electrode shows voltammetric responses with high sensitivity and selectivity for Tyr in optimal conditions, which makes it very suitable for sub-micromolar detection of Tyr. A sensitive oxidation peak at +0.64 V is employed to determine Tyr. Good linear relationship between the oxidation peak current and the Tyr concentration in the range of 1x10(-7) to 5x10(-5) mol/L is obtained in phosphate buffer solution with pH 7.0. By use of modified electrode, the voltammetric detection limit for Tyr in DPV measurements is 8x10(-8) mol/L (S/N=3). Good sensitivity, selectivity and stability of the low-cost modified electrode make it very suitable for the determination of trace amounts of Tyr in pharmaceutical and clinical preparations.

摘要

基于多壁碳纳米管(MWNTs)/4-氨基苯磺酸(4-ABSA)膜修饰玻碳电极构建了一种化学修饰电极。采用循环伏安法(CV)和差分脉冲伏安法(DPV)研究了酪氨酸(Tyr)在MWNTs/4-ABSA修饰电极表面的电催化氧化。制备的修饰电极在最佳条件下对Tyr呈现出具有高灵敏度和选择性的伏安响应,这使其非常适合于亚微摩尔级Tyr的检测。利用+0.64 V处的灵敏氧化峰来测定Tyr。在pH 7.0的磷酸盐缓冲溶液中,氧化峰电流与Tyr浓度在1×10⁻⁷至5×10⁻⁵ mol/L范围内呈现良好的线性关系。使用修饰电极时,DPV测量中Tyr的伏安检测限为8×10⁻⁸ mol/L(S/N = 3)。这种低成本修饰电极具有良好的灵敏度、选择性和稳定性,使其非常适合用于药物制剂和临床制剂中痕量Tyr的测定。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验