Issue 1, 2017

Continuous micro-vortex-based nanoparticle manipulation via focused surface acoustic waves

Abstract

Despite increasing demand in the manipulation of nanoscale objects for next generation biological and industrial processes, there is a lack of methods for reliable separation, concentration and purification of nanoscale objects. Acoustic methods have proven their utility in contactless manipulation of microscale objects mainly relying on the acoustic radiation effect, though the influence of acoustic streaming has typically prevented manipulation at smaller length scales. In this work, however, we explicitly take advantage of the strong acoustic streaming in the vicinity of a highly focused, high frequency surface acoustic wave (SAW) beam emanating from a series of focused 6 μm substrate wavelength interdigital transducers patterned on a piezoelectric lithium niobate substrate and actuated with a 633 MHz sinusoidal signal. This streaming field serves to focus fluid streamlines such that incoming particles interact with the acoustic field similarly regardless of their initial starting positions, and results in particle displacements that would not be possible with a travelling acoustic wave force alone. This streaming-induced manipulation of nanoscale particles is maximized with the formation of micro-vortices that extend the width of the microfluidic channel even with the imposition of a lateral flow, occurring when the streaming-induced flow velocities are an order of magnitude larger than the lateral one. We make use of this acoustic streaming to demonstrate the continuous and differential focusing of 100 nm, 300 nm and 500 nm particles.

Graphical abstract: Continuous micro-vortex-based nanoparticle manipulation via focused surface acoustic waves

Supplementary files

Article information

Article type
Paper
Submitted
13 Sep 2016
Accepted
16 Nov 2016
First published
16 Nov 2016

Lab Chip, 2017,17, 91-103

Continuous micro-vortex-based nanoparticle manipulation via focused surface acoustic waves

D. J. Collins, Z. Ma, J. Han and Y. Ai, Lab Chip, 2017, 17, 91 DOI: 10.1039/C6LC01142J

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