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基于微流控芯片的液-液萃取及采用亚纳升级液滴捕获技术的预富集

Microfluidic chip-based liquid-liquid extraction and preconcentration using a subnanoliter-droplet trapping technique.

作者信息

Chen Hong, Fang Qun, Yin Xue-Feng, Fang Zhao-Lun

机构信息

Chemistry Department, Zhejiang University (Xixi Campus), 310028 Hangzhou, China.

出版信息

Lab Chip. 2005 Jul;5(7):719-25. doi: 10.1039/b416964f. Epub 2005 Apr 26.

Abstract

A robust and simple approach for microfluidic liquid-liquid (L-L) extraction at the subnanoliter-scale was developed for on-chip sample pretreatment. Organic solvent droplets of a few hundred pL were trapped within micro recesses fabricated in the channel walls of a microfabricated glass chip. L-L extraction was performed by delivering aqueous samples through the channel, with the sample stream continuously flowing adjacent to the droplets. The analytes in aqueous streams were enriched within the droplet with high preconcentration factors owing to both phase transfer and dissolution of organic solvent into the bypassing aqueous sample. An aqueous solution of butyl rhodamine B (BRB) and 1-hexanol were used, respectively, as sample and extractant to demonstrate the performance of the system. The fluorescence intensity of the dye extracted into the droplet was monitored in situ by LIF. The system proved to be an efficient means for achieving high enrichment factors of over 1000, with sample consumption of a few microL. Quantitative measurement of the extracted analyte was achieved with a linear response in the range 1 x 10(-9)-8 x 10(-7) M BRB. The precision of the measured fluorescence values for a 10(-7) M BRB standard with a 12.5 min preconcentration period was 6.6% RSD (n = 5).

摘要

我们开发了一种用于芯片上样品预处理的、在亚纳升规模下进行微流控液-液(L-L)萃取的强大且简单的方法。几百皮升的有机溶剂液滴被困在微加工玻璃芯片通道壁上制造的微凹槽内。通过将水性样品输送通过通道来进行L-L萃取,样品流在液滴附近持续流动。由于相转移以及有机溶剂溶解到旁路水性样品中,水性流中的分析物在液滴内以高预浓缩因子得以富集。分别使用丁基罗丹明B(BRB)水溶液和1-己醇作为样品和萃取剂来证明该系统的性能。通过激光诱导荧光(LIF)原位监测萃取到液滴中的染料的荧光强度。该系统被证明是一种实现超过1000的高富集因子的有效手段,样品消耗量为几微升。在1×10⁻⁹ - 8×10⁻⁷ M BRB范围内实现了对萃取分析物的线性响应定量测量。对于在12.5分钟预浓缩期的10⁻⁷ M BRB标准品,测量的荧光值的精密度为6.6%相对标准偏差(n = 5)。

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