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Microsystem Technologies

, Volume 23, Issue 5, pp 1335–1342 | Cite as

Surface acoustic wave based pumping in a microchannel

  • Tao Wang
  • Qi Ni
  • Nathan Crane
  • Rasim Guldiken
Technical Paper

Abstract

Pumping and manipulation of liquids in microfluidic channels are important for many mechanical, chemical and biomedical applications. Surface acoustic wave based devices fabricated on high-efficiency piezoelectric substrates have been recently investigated for mixing and separation application within microfluidic channels. In this paper, we introduce a novel integrated surface acoustic wave based pump for liquid delivery and precise manipulation within a microchannel. The device employs a hydrophobic surface coating (Cytop) in the device design to decrease the friction force and increase the bonding. Contrary to previous surface acoustic wave based pumps which were mostly based on the filling and sucking process, we demonstrate long distance media delivery (up to 8 mm) and high pumping velocity increasing the device’s application space and mass production potential. Additionally, the device design does not need precise layers of water and glass between substrate and channel, simplifying the design significantly. In this study, we conducted extensive parametric studies to quantify the effects of the liquid volume pumped, microchannel size, input applied power as well as the existence of hydrophobic surface coating on the pumping velocity and pump performance. Our results indicate that the pumping velocity for a constant liquid volume with the same applied input power can be increased by over 130 % (2.31 vs 0.99 mm/min) by employing a hydrophobic surface coating (Cytop) in a thinner microchannel (250 vs 500 µm) design. This device can be used in circulation, dosing, metering and drug delivery applications which necessitates small-scale precise liquid control and delivery.

Keywords

PDMS Surface Acoustic Wave Lithium Niobate Liquid Volume Microfluidic Channel 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Department of Mechanical EngineeringUniversity of South FloridaTampaUSA

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