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利用驻波拉曼镊子稳定光学捕获和灵敏表征纳米结构。

Stable optical trapping and sensitive characterization of nanostructures using standing-wave Raman tweezers.

机构信息

School of Electronic Engineering, Dongguan University of Technology, Dongguan, Guangdong, P.R. China.

Department of Physics, East Carolina University, Greenville, North Carolina 27858-4353, USA.

出版信息

Sci Rep. 2017 Feb 17;7:42930. doi: 10.1038/srep42930.

Abstract

Optical manipulation and label-free characterization of nanoscale structures open up new possibilities for assembly and control of nanodevices and biomolecules. Optical tweezers integrated with Raman spectroscopy allows analyzing a single trapped particle, but is generally less effective for individual nanoparticles. The main challenge is the weak gradient force on nanoparticles that is insufficient to overcome the destabilizing effect of scattering force and Brownian motion. Here, we present standing-wave Raman tweezers for stable trapping and sensitive characterization of single isolated nanostructures with a low laser power by combining a standing-wave optical trap with confocal Raman spectroscopy. This scheme has stronger intensity gradients and balanced scattering forces, and thus can be used to analyze many nanoparticles that cannot be measured with single-beam Raman tweezers, including individual single-walled carbon nanotubes (SWCNT), graphene flakes, biological particles, SERS-active metal nanoparticles, and high-refractive semiconductor nanoparticles. This would enable sorting and characterization of specific SWCNTs and other nanoparticles based on their increased Raman fingerprints.

摘要

光学操纵和无标记纳米结构特性分析为纳米器件和生物分子的组装和控制开辟了新的可能性。与拉曼光谱学相结合的光镊可以分析单个被捕获的粒子,但对于单个纳米粒子通常效果较差。主要的挑战是纳米粒子上的弱梯度力不足以克服散射力和布朗运动的不稳定性。在这里,我们提出了基于驻波的拉曼镊子,通过将驻波光阱与共焦拉曼光谱学相结合,以低激光功率实现对单个孤立纳米结构的稳定捕获和敏感特性分析。该方案具有更强的强度梯度和平衡的散射力,因此可用于分析许多单个光束拉曼镊子无法测量的纳米粒子,包括单个单壁碳纳米管 (SWCNT)、石墨烯薄片、生物粒子、表面增强拉曼散射 (SERS) 活性金属纳米粒子和高折射率半导体纳米粒子。这将能够根据它们增加的拉曼指纹对特定的 SWCNT 和其他纳米粒子进行分类和特性分析。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8eaa/5314326/7e888cfd6df8/srep42930-f1.jpg

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