Sibley School of Mechanical and Aerospace Engineering, Cornell University , Ithaca, New York 14853, United States.
Department of Medicine, Division of Hematology & Medical Oncology, Weill-Cornell Medicine , New York, New York 10021, United States.
Anal Chem. 2017 Nov 21;89(22):12192-12200. doi: 10.1021/acs.analchem.7b02858. Epub 2017 Oct 30.
Separation of particles on the order of 100 nm with acoustophoresis has been challenging to date because of the competing natures of the acoustic radiation force and acoustic streaming on the particles. In this work, we present a surface acoustic wave (SAW)-based device that integrates a Fabry-Perot type acoustic resonator into a microfluidic channel to separate submicrometer particles. This configuration enhances the overall acoustic radiation force on the particles and thereby offers controlled manipulation of particles as small as 300 nm. Additionally, SAW-based excitation generates high-frequency acoustic waves in the system relative to bulk acoustic wave (BAW)-based actuation, which suppresses Rayleigh streaming effects on the submicrometer particles. We demonstrate a continuous-flow acoustophoretic separation of 300 and 100 nm particles in our device with a separation efficiency of 86.3%. We also present an analytical stochastic method to model the transport of submicrometer particles in the device and predict the migration trajectories as a function of acoustic and velocity potential field strengths. Our model incorporates particle diffusion, which is important for small particles, and successfully predicts the size-dependent separation modality of our system. This device can be used for several applications in microfluidics that require sorting of the submicrometer particles, and the analytical method can also be extended to predict the particle transport in other systems.
迄今为止，由于粒子所受声辐射力和声波流之间的竞争特性，实现对 100nm 量级的粒子进行分离一直具有挑战性。在这项工作中，我们提出了一种基于表面声波（SAW）的器件，该器件将法布里-珀罗型声学谐振器集成到微流道中，以分离亚微米级粒子。这种结构增强了粒子的总声辐射力，从而能够对小至 300nm 的粒子进行精确控制。此外，与基于体声波（BAW）的激励相比，基于 SAW 的激励在系统中产生高频声波，从而抑制了亚微米粒子的瑞利流效应。我们在我们的设备中展示了对 300nm 和 100nm 粒子的连续流声分离，分离效率为 86.3%。我们还提出了一种分析随机方法来模拟微通道中亚微米粒子的输运，并预测迁移轨迹作为声和速度势场强度的函数。我们的模型包含了对小粒子很重要的粒子扩散，并成功地预测了系统的尺寸相关的分离模式。该设备可用于微流控中需要对亚微米粒子进行分选的多种应用，并且该分析方法还可以扩展到预测其他系统中的粒子输运。
