Optimization Analysis of Particle Separation Parameters for a Standing Surface Acoustic Wave Acoustofluidic Chip.

Abstract

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%.