Abstract

Surface acoustic wave (SAW) micromanipulation offers modularity, easy integration into microfluidic devices and a high degree of flexibility. A major challenge for acoustic manipulation, however, is the existence of a lower limit on the minimum particle size that can be manipulated. As particle size reduces, the drag force resulting from acoustic streaming dominates over acoustic radiation forces; reducing this threshold is key to manipulating smaller specimens. To address this, we investigate a novel excitation configuration based on diffractive-acoustic SAW (DASAW) actuation and demonstrate a reduction in the critical minimum particle size which can be manipulated. DASAW exploits the inherent diffractive effects arising from a limited transducer area in a microchannel, requiring only a travelling SAW (TSAW) to generate time-averaged pressure gradients. We show that these acoustic fields focus particles at the channel walls, and further compare this excitation mode with more typical standing SAW (SSAW) actuation. Compared to SSAW, DASAW reduces acoustic streaming effects whilst generating a comparable pressure field. The result of these factors is a critical particle size with DASAW (1 upmum) that is significantly smaller than that for SSAW actuation (1.85 upmum), for polystyrene particles and a given lambda _{text {SAW}} = 200 upmum. We further find that streaming magnitude can be tuned in a DASAW system by changing the channel height, noting optimum channel heights for particle collection as a function of the fluid wavelength at which streaming velocities are minimised in both DASAW and SSAW devices.

Highlights

  • The small dimensions characteristic of microfluidic devices has enabled selective manipulation of small objects such as cells and microparticles (Lee et al 2017; Di Carlo 2009; Tayebi et al 2020), including for tissue engineering (Choi et al 2007; Andersson and van den Berg 2004; Khademhosseini et al 2006; Novak et al 2020; Bhatia and Ingber 2014), cell–cell interaction and signalling studies (Regehr et al 2009; Faley et al 2008; Zervantonakis et al 2011), sample concentration and sorting (Ding et al 2012; Gascoyne and Vykoukal 2002; Ahmed et al 2018)

  • The Surface acoustic wave (SAW)-based acoustofluidic device consists of a 128◦ Y-cut X-propagating lithium niobate (LiNbO3 ; LN) piezoelectric crystal patterned with interdigital transducers (IDTs) bonded to the microchannel embedded within polydimethylsiloxane (PDMS)

  • Further testing the hypothesis that reducing the relative streaming strength would result in a reduction of acrit, we analyse the particle trajectory subjected to their corresponding acoustic radiation forces and the streaming induced drag forces

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Summary

Introduction

The small dimensions characteristic of microfluidic devices has enabled selective manipulation of small objects such as cells and microparticles (Lee et al 2017; Di Carlo 2009; Tayebi et al 2020), including for tissue engineering (Choi et al 2007; Andersson and van den Berg 2004; Khademhosseini et al 2006; Novak et al 2020; Bhatia and Ingber 2014), cell–cell interaction and signalling studies (Regehr et al 2009; Faley et al 2008; Zervantonakis et al 2011), sample concentration and sorting Gascoyne and Vykoukal 2002; Ahmed et al 2018) This accurate and versatile manipulation of biological matter is essential for many lab-on-a-chip platforms, especially those designed for diagnostic purposes. A multitude of particle manipulation methods have been explored for manipulating specimens in microfluidic systems, covering both passive (Di Carlo 2009; Inglis et al 2006; Davis et al 2006) and active techniques (Baret et al 2009; Inglis et al 2004). The former relies on the configuration and design geometry of the microfluidic channels and sample inertia.

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Operating principle
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Time‐averaged acoustic forces
Numerical model
Pressure and streaming fields
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Height dependence: comparison between the SSAW and DASAW
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Height dependence: effect of SAW wavelength
Optimum channel height
Feature 1: the relationship between height and streaming field
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Feature 2: spatial force dominance variance
Conclusion
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