Thameem Raqeeb, Rallabandi Bhargav, Hilgenfeldt Sascha
Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign , Urbana, Illinois 61801, USA.
Biomicrofluidics. 2016 Feb 26;10(1):014124. doi: 10.1063/1.4942458. eCollection 2016 Jan.
Ultrasonic driving of semicylindrical microbubbles generates strong streaming flows that are robust over a wide range of driving frequencies. We show that in microchannels, these streaming flow patterns can be combined with Poiseuille flows to achieve two distinctive, highly tunable methods for size-sensitive sorting and trapping of particles much smaller than the bubble itself. This method allows higher throughput than typical passive sorting techniques, since it does not require the inclusion of device features on the order of the particle size. We propose a simple mechanism, based on channel and flow geometry, which reliably describes and predicts the sorting behavior observed in experiment. It is also shown that an asymptotic theory that incorporates the device geometry and superimposed channel flow accurately models key flow features such as peak speeds and particle trajectories, provided it is appropriately modified to account for 3D effects caused by the axial confinement of the bubble.
半圆柱形微泡的超声驱动会产生强烈的流动,这种流动在很宽的驱动频率范围内都很稳定。我们表明,在微通道中,这些流动模式可以与泊肃叶流相结合,以实现两种独特的、高度可调的方法,用于对远小于气泡本身的颗粒进行尺寸敏感的分选和捕获。这种方法比典型的被动分选技术具有更高的通量,因为它不需要包含与颗粒尺寸相当的器件特征。我们基于通道和流动几何结构提出了一种简单的机制,该机制能够可靠地描述和预测实验中观察到的分选行为。研究还表明,一种结合了器件几何结构和叠加通道流的渐近理论能够准确地模拟关键流动特征,如峰值速度和颗粒轨迹,前提是对其进行适当修改以考虑气泡轴向限制所引起的三维效应。