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利用表面增强拉曼散射微滴传感器进行百草枯的痕量高灵敏度分析。

Highly sensitive trace analysis of paraquat using a surface-enhanced Raman scattering microdroplet sensor.

机构信息

Department of Bionano Engineering, Hanyang University, Ansan 426-791, South Korea.

出版信息

Anal Chim Acta. 2010 Nov 29;681(1-2):87-91. doi: 10.1016/j.aca.2010.09.036. Epub 2010 Sep 29.

Abstract

We report a rapid and highly sensitive trace analysis of paraquat (PQ) in water using a surface-enhanced Raman scattering (SERS)-based microdroplet sensor. Aqueous samples of PQ, silver nanoparticles, and NaCl as the aggregation agent were introduced into a microfluidic channel and were encapsulated by a continuous oil phase to form a microdroplet. PQ molecules were adsorbed onto particle surfaces in isolated droplets by passing through the winding part of the channel. Memory effects, caused by the precipitation of nanoparticle aggregates on channel walls, were removed because the aqueous droplets were completely isolated by a continuous oil phase. The limit of detection (LOD) of PQ in water, determined by the SERS-based microdroplet sensor, was estimated to be below 2×10(-9) M, and this low detection limit was enhanced by one to two orders of magnitude compared to conventional analytical methods.

摘要

我们报告了一种使用基于表面增强拉曼散射(SERS)的微滴传感器快速且高灵敏度地分析水中百草枯(PQ)的方法。将 PQ 的水溶液、银纳米粒子和 NaCl(作为聚集剂)引入微流道,并被连续的油相包裹以形成微滴。通过流经通道的蜿蜒部分,PQ 分子被吸附到孤立液滴中的颗粒表面上。由于纳米颗粒聚集物在通道壁上的沉淀而产生的记忆效应被消除了,因为连续的油相完全将水相液滴隔离开来。通过基于 SERS 的微滴传感器测定的水中 PQ 的检出限(LOD)估计低于 2×10(-9) M,与传统分析方法相比,这种低检测限提高了一到两个数量级。

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