Han Junlong, Hu Hong, Lei Yulin, Huang Qingyun, Fu Chen, Gai Chenhui, Ning Jia
School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen518055, China.
Shenzhen Polytechnic, Shenzhen518055, China.
ACS Omega. 2022 Dec 27;8(1):311-323. doi: 10.1021/acsomega.2c04273. eCollection 2023 Jan 10.
Microparticle separation technology is an important technology in many biomedical and chemical engineering applications from sample detection to disease diagnosis. Although a variety of microparticle separation techniques have been developed thus far, surface acoustic wave (SAW)-based microfluidic separation technology shows great potential because of its high throughput, high precision, and integration with polydimethylsiloxane (PDMS) microchannels. In this work, we demonstrate an acoustofluidic separation chip that includes a piezoelectric device that generates tilted-angle standing SAWs and a permanently bonded PDMS microchannel. We established a mathematical model of particle motion in the microchannel, simulated the particle trajectory through finite element simulation and numerical simulation, and then verified the validity of the model through acoustophoresis experiments. To improve the performance of the separation chip, the influences of particle size, flow rate, and input power on the particle deflection distance were studied. These parameters are closely related to the separation purity and separation efficiency. By optimizing the control parameters, the separation of micron and submicron particles under different throughput conditions was achieved. Moreover, the separation samples were quantitatively analyzed by digital light scattering technology and flow cytometry, and the results showed that the maximum purity of the separated particles was ∼95%, while the maximum efficiency was ∼97%.
微颗粒分离技术是从样品检测到疾病诊断等众多生物医学和化学工程应用中的一项重要技术。尽管到目前为止已经开发出了多种微颗粒分离技术,但基于表面声波(SAW)的微流控分离技术因其高通量、高精度以及与聚二甲基硅氧烷(PDMS)微通道的集成性而展现出巨大潜力。在这项工作中,我们展示了一种声流控分离芯片,它包括一个能产生倾斜角驻波表面声波的压电装置和一个永久键合的PDMS微通道。我们建立了微通道中颗粒运动的数学模型,通过有限元模拟和数值模拟对颗粒轨迹进行了模拟,然后通过声泳实验验证了该模型的有效性。为了提高分离芯片的性能,研究了颗粒尺寸、流速和输入功率对颗粒偏转距离的影响。这些参数与分离纯度和分离效率密切相关。通过优化控制参数,实现了在不同通量条件下对微米级和亚微米级颗粒的分离。此外,利用数字光散射技术和流式细胞术对分离样品进行了定量分析,结果表明,分离颗粒的最大纯度约为95%,而最大效率约为97%。