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基于时间和空间分辨表面增强拉曼光谱映射策略用于农药检测。

Based on time and spatial-resolved SERS mapping strategies for detection of pesticides.

作者信息

Ma Bingbing, Li Pan, Yang Liangbao, Liu Jinhuai

机构信息

Department of Chemistry, University of Science & Technology of China, Hefei, Anhui, 230026, China; Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei 230031, China.

Department of Chemistry, University of Science & Technology of China, Hefei, Anhui, 230026, China; Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei 230031, China.

出版信息

Talanta. 2015 Aug 15;141:1-7. doi: 10.1016/j.talanta.2015.03.053. Epub 2015 Apr 1.

Abstract

For the sensitive and convenient detection of pesticides, several sensing methods and materials have been widely explored. However, it is still a challenge to obtain sensitive, simple detection techniques for pesticides. Here, the simple and sensitive Time-resolved SERS mapping (T-SERS) and Spatial-resolved SERS mapping (S-SERS) are presented for detection of pesticides by using Au@Ag NPs as SERS substrate. The Time-resolved SERS mapping (T-SERS) is based on state translation nanoparticles from the wet state to the dry state to realize SERS measurements. During the SERS measurement, adhesive force drives the particles closer together and then average interparticle gap becomes smaller. Following, air then begins to intersperse into the liquid network and the particles are held together by adhesive forces at the solid-liquid-air interface. In the late stage of water evaporation, all particles are uniformly distributed. Thus, so called hotspots matrix that can hold hotspots between every two adjacent particles in efficient space with minimal polydispersity of particle size are achieved, accompanying the red-shift of surface plasmon peak and appearance of an optimal SPR resonated sharply with excitation wavelength. Here, we found that the T-SERS method exhibits the detection limits of 1-2 orders of magnitude higher than that of S-SERS. On the other hand, the T-SERS is very simple method with high detection sensitivity, better reproducibility (RSD=10.8%) and is beneficial to construction of a calibration curve in comparison with that of Spatial-resolved SERS mapping (S-SERS). Most importantly, as a result of its remarkable sensitivity, T-SERS mapping strategies have been applied to detection of several pesticides and the detect limit can down to 1nM for paraoxon, 0.5nM for sumithion. In short, T-SERS mapping measurement promises to open a market for SERS practical detection with prominent advantages.

摘要

为了实现对农药的灵敏且便捷的检测,人们已广泛探索了多种传感方法和材料。然而,获取灵敏、简便的农药检测技术仍是一项挑战。在此,本文提出了一种简单且灵敏的时间分辨表面增强拉曼光谱映射(T-SERS)和空间分辨表面增强拉曼光谱映射(S-SERS)方法,用于以金@银纳米粒子作为表面增强拉曼光谱(SERS)基底来检测农药。时间分辨表面增强拉曼光谱映射(T-SERS)基于纳米粒子从湿态到干态的状态转变来实现表面增强拉曼光谱测量。在表面增强拉曼光谱测量过程中,粘附力促使粒子相互靠近,进而平均粒子间间隙变小。随后,空气开始散布到液体网络中,粒子在固-液-气界面处通过粘附力聚集在一起。在水蒸发的后期,所有粒子均匀分布。这样,就形成了所谓的热点矩阵,能够在有效空间内每两个相邻粒子之间保持热点,且粒径的多分散性最小,同时伴随表面等离子体峰的红移以及与激发波长产生强烈共振的最佳表面等离子体共振(SPR)的出现。在此,我们发现T-SERS方法的检测限比S-SERS方法高1 - 2个数量级。另一方面,T-SERS是一种非常简单的方法,具有高检测灵敏度、更好的重现性(相对标准偏差RSD = 10.8%),并且与空间分辨表面增强拉曼光谱映射(S-SERS)相比,有利于构建校准曲线。最重要的是,由于其显著的灵敏度,T-SERS映射策略已应用于多种农药的检测,对甲基对硫磷的检测限可低至1 nM,对杀螟松的检测限可低至0.5 nM。简而言之,T-SERS映射测量有望凭借其突出优势为表面增强拉曼光谱的实际检测开拓市场。

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