Automated monitoring and positioning of single microparticle via ultrasound-driven microbubble streaming

Abstract

We present a novel technique that uses ultrasound-driven microbubble streaming for automated positioning of single microparticles of arbitrary size and physical properties in microchannels. We have developed algorithms for automatic detection, tracking, and precise positioning of target particles with arbitrary initial positions across the entire width of microchannels in a live mode that does not require additional structures to precondition the flow for particle positioning. This approach is universally applicable in all areas of microfluidics, regardless of particle size, shape, density, and compressibility. In this study, experiments were performed to position particles of different sizes (2, 5, 10, 15 μ m) in 5 lateral regions in a 500 μ m microchannel, resulting in valid positioning accuracy for single particles (up to MADf=2.3μm in a 500 μm).