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实时表征光阱微粒子网络中的流体动力学。

Real time characterization of hydrodynamics in optically trapped networks of micro-particles.

机构信息

Department of Physics and Astronomy, University of Glasgow, Glasgow, UK.

出版信息

J Biophotonics. 2010 Apr;3(4):244-51. doi: 10.1002/jbio.201000003.

Abstract

The hydrodynamic interactions of micro-silica spheres trapped in a variety of networks using holographic optical tweezers are measured and characterized in terms of their predicted eigenmodes. The characteristic eigenmodes of the networks are distinguishable within 20-40 seconds of acquisition time. Three different multi-particle networks are considered; an eight-particle linear chain, a nine-particle square grid and, finally, an eight-particle ring. The eigenmodes and their decay rates are shown to behave as predicted by the Oseen tensor and the Langevin equation, respectively. Finally, we demonstrate the potential of using our micro-ring as a non-invasive sensor to the local environmental viscosity, by showing the distortion of the eigenmode spectrum due to the proximity of a planar boundary.

摘要

使用全息光镊测量并描述了被困在各种网络中的微硅球的流体动力相互作用,根据其预测的本征模式进行了测量和描述。在 20-40 秒的采集时间内,可以区分网络的特征本征模式。考虑了三种不同的多粒子网络:八粒子线性链、九粒子正方形网格,最后是八粒子环。本征模式及其衰减率分别表现为 Oseen 张量和 Langevin 方程的预测。最后,我们通过展示由于平面边界的接近而导致本征模式谱的变形,证明了我们的微环作为局部环境粘度的非侵入式传感器的潜力。

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