Improving SERS hot spots for on- site pesticide detection by combining silver nanoparticles with nanowires

Improving SERS hot spots for on- site pesticide detection by combining silver nanoparticles with nanowires
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通过将银纳米粒子与纳米线相结合来改善现场农药检测的 SERS 热点

DOI:
10.1039/c8tc01741g
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发表时间:
2018-08-28
影响因子:
6.4
通讯作者:
Gao, Yanfeng
Gao, Yanfeng
中科院分区:
材料科学2区
文献类型:
--
作者:
Wei, Wei;Du, Yixuan;Gao, Yanfeng

文献摘要

被引文献

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表面增强拉曼散射(Sers)是一种快速、有效的低浓度指纹结构识别方法。然而,Sers在具有灵活和鲁棒结构的现场检测中的应用具有挑战性。在这项工作中,我们开发了一种灵活的,鲁棒的和可重复使用的银功能化的Sers基板的农药残留检测。该Sers基底由嵌入聚二甲基硅氧烷中的银纳米颗粒@纳米线(AgNP@AgNW)网络组成。独特的网络结构提供了丰富的Sers热点,其中电磁场可以通过激发围绕AgNW的AgNP的局部表面等离子体共振而放大。嵌入结构提高了表面对目标分子的吸附能力,从而降低了拉曼荧光。此外,该基板在10次循环后保持原始拉曼强度的54.7%;因此,该基板显示出令人满意的可再循环性能。此外,Sers基底表现出可接受的检测再现性与4.22%的相对标准偏差和令人满意的拉伸性能。这些结果表明,我们的基板有潜力用于环境监督,食品安全,爆炸物检测和安全应用。
Surface-enhanced Raman scattering (SERS) is a rapid and effective method for identifying fingerprint structures at low concentrations. However, the application of SERS for on-site detection with flexible and robust structures is challenging. In this work, we have developed a flexible, robust and reusable silver-functionalized SERS substrate for pesticide residue detection. This SERS substrate is composed of a silver nanoparticle@nanowire (AgNP@AgNW) network that is embedded into polydimethylsiloxane. The unique network structure provides rich SERS hot spots, where the electromagnetic field can be magnified through the excitation of localized surface plasmon resonances of AgNPs that surround AgNWs. The embedded structure improves the adsorption ability of the surface for target molecules, thereby reducing Raman fluorescence. In addition, this substrate retains 54.7% of the original Raman intensity after ten cycles; hence, this substrate shows satisfactory recyclability performance. Moreover, the SERS substrate exhibits acceptable detection reproducibility with 4.22% relative standard deviation and satisfactory tensile properties. These results demonstrate that our substrate has the potential for use in environmental supervision, food safety, explosive detection and security applications.