4.7 Article

Real time size-dependent particle segregation and quantitative detection in a surface acoustic wave-photoacoustic integrated microfluidic system

Journal

SENSORS AND ACTUATORS B-CHEMICAL
Volume 252, Issue -, Pages 568-576

Publisher

ELSEVIER SCIENCE SA
DOI: 10.1016/j.snb.2017.06.006

Keywords

Surface acoustic wave; Photoacoustics; Microfluidics; Lab-on-a-chip

Funding

  1. A*STAR SIMTech [CRP-U12-V-027SU/SIMT/12-410012]
  2. iFood Research Grant, NTU [M4061455]

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We present an integrated microfluidic system capable of size-dependent separation, concentration, and quantitative detection of microparticles on a single piezoelectric (128 degrees YX LiNbO3) substrate using surface acoustic wave (SAW) and photoacoustic (PA) technique. First, using a tilted-angle standing SAW highly efficient segregation of polystyrene beads of two different sizes was achieved in a continuous particle flow inside the channel. Flow-assisted migration of separated particles would then undergo particle aggregation using a SAW device, to preconcentrate the sample before detection The optical absorption of the pulsed laser by the polystyrene microparticles generates the PA wave. The detection scheme involves sensing the SAW generated by the optically induced mechanical resonance of the PA wave inside the microfluidic channel. The SAW-PA signal was further correlated to the particle count. The developed integrated microfluidic system performs effectively, with separation efficiency above 95% for the 3- and 10-mu m diameter polystyrene beads. The separated 10-mu m particles were directed into the sensing chamber, where a SAW device concentrate the particles before real-time quantitative detection. The configuration and theoretical aspects of each integrated segments were studied and explained. The sensor presented a reliable (R-2 = 0.98) detection of the 10-mu m particles down to 7 particles in 10 mu L of the sample volume in 15 min. This technique paves the way to the design and development of future lab-on-a-chip (LOC) devices for clinical analyte detection and quantification. (C) 2017 Elsevier B.V. All rights reserved.

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