Suppr超能文献

基于希夫碱荧光团荧光猝灭的铜离子选择性化学传感器。

Selective chemosensor for copper ions based on fluorescence quenching of a Schiff-base fluorophore.

机构信息

Department of Analytical Chemistry, Faculty of Sciences, University of Cádiz, P.O. Box 11510, Campus Río S. Pedro, Puerto Real, Cádiz 11510, Spain.

出版信息

Appl Spectrosc. 2010 Jul;64(7):727-32. doi: 10.1366/000370210791666282.

Abstract

A Schiff base-based fluorescent chemosensor has been studied for divalent copper detection. The formation of 2-hydroxybenzaldehyde benzoylhydrazone-Cu(2+) complex induced a fluorescence quenching of this compound in a medium of water/ethanol (53% v/v) and 0.05 M phosphate buffer (pH 7.0). The continuous variations and mole-ratio plots of absorbance suggested a complex formation with a 1:1 metal-ligand stoichiometry. The conditional stability constant for the complex was evaluated to be 6 x 10(6) M(-1). A modified Stern-Volmer relationship was employed to obtain a linear calibration plot, obtaining a dynamic working range up to 157.4 microM. The detection limit of this system was found to be 5.6 microM and the relative standard deviation for five measurements of 78.7 microM concentration was 5.2%. This fluorescent chemosensor also showed a high selectivity for copper ions over other metal ions, such as Al(3+), Ca(2+), Cd(2+), Fe(2+), K(+), Mg(2+), Na(+), Pb(2+), or Zn(2+). The results of this investigation show a simple, rapid, low-cost, and selective method that can operate in neutral solutions and is useful for biological and environmental applications.

摘要

一种基于席夫碱的荧光化学传感器已被研究用于检测二价铜。在水/乙醇(53%v/v)和 0.05 M 磷酸盐缓冲液(pH 7.0)的介质中,2-羟基苯甲醛苯甲酰腙-Cu(2+) 配合物的形成导致该化合物的荧光猝灭。连续变化和摩尔比图谱表明,配合物的形成具有 1:1 的金属-配体化学计量比。该配合物的条件稳定常数评估为 6 x 10(6) M(-1)。采用改进的 Stern-Volmer 关系得到线性校准曲线,获得了高达 157.4 microM 的动态工作范围。该系统的检测限被发现为 5.6 microM,而对于 78.7 microM 浓度的五次测量的相对标准偏差为 5.2%。这种荧光化学传感器还表现出对铜离子的高选择性,超过其他金属离子,如 Al(3+)、Ca(2+)、Cd(2+)、Fe(2+)、K(+)、Mg(2+)、Na(+)、Pb(2+)或 Zn(2+)。该研究的结果表明,这是一种简单、快速、低成本和选择性的方法,可以在中性溶液中操作,可用于生物和环境应用。

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