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采用基于离子液体胶束的三步堆积在线浓缩技术,使痕量阴离子化合物在毛细管电泳中的在线预浓缩提高了 1000 多倍。

Over 1000-fold improvement in an online preconcentration of trace anionic compounds by capillary electrophoresis with ionic liquid micelle-based three-step stacking.

机构信息

College of Pharmaceutical Science, Zhejiang University of Technology, Hangzhou, PR China.

College of Material Chemistry and Chemical Engineering, Hangzhou Normal University, Hangzhou, PR China.

出版信息

Anal Chim Acta. 2018 Dec 31;1044:191-197. doi: 10.1016/j.aca.2018.08.027. Epub 2018 Aug 16.

Abstract

A sensitive, simple, and environmentally friendly online three-step stacking strategy combining field-enhanced sample injection, sweeping and micelle to solvent stacking has been developed to determine trace amounts of organic anionic analytes in complex biological samples. A green ionic liquid, 1-dodecyl-3-methylimidazolium hydrogen sulfate, was first introduced as a micellar solution and used for electroosmotic flow reversal in this stacking strategy. The mechanism of stacking has been discussed, and parameters affecting three-step stacking preconcentration efficiency have been optimized. The capillary coated with an ionic liquid was easy to prepare, regenerable and repeatable (RSD<2.16%) and yielded a high efficiency. Under optimal conditions, the sensitivity improvement increased up to 2424-fold when compared with the normal capillary zone electrophoresis mode. The peak shape and separation efficiency of the model basic organic acids showed a significant enhancement when compared to traditional capillary zone electrophoresis. The optimized method showed great potential for quantitative analysis of trace concentration analytes in complex matrices.

摘要

一种灵敏、简单且环保的在线三步堆积策略,结合场增强样品注入、扫集和胶束到溶剂堆积,已被开发用于测定复杂生物样品中痕量有机阴离子分析物。首次将绿色离子液体 1-十二烷基-3-甲基咪唑硫酸氢盐作为胶束溶液引入该堆积策略中,用于电渗流反转。讨论了堆积的机制,并优化了影响三步堆积浓缩效率的参数。涂有离子液体的毛细管易于制备、可重复使用(RSD<2.16%),且具有高效性。在最佳条件下,与常规毛细管区带电泳模式相比,灵敏度提高了 2424 倍。与传统毛细管区带电泳相比,模型基本有机酸的峰形和分离效率得到了显著改善。该优化方法在复杂基质中痕量浓度分析物的定量分析方面具有很大的潜力。

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