Supp1-3138086.docx

Abstract

Objective: Separation and detection of micro-particles or cells from bio-samples by point-of-care (POC) systems are critical for biomedical and healthcare diagnostic applications. Among the microfluidic separation techniques, the acoustophoresis-based microfluidic separation technique has the advantages of label-free, contactless, and good biocompatibility. However, most of the separation techniques are bulky, requiring additional equipment for analysis, not suitable for POC-based in-field real-time applications. Therefore, we proposed a platform, which integrates an acoustophoresis-based separation device and a lensless imaging sensor into a compact standalone system to solve the problem. Methods: In this system, Standing Surface Acoustic Wave (SSAW) is utilized for label-free particle separation, while lensless imaging is employed for seamless particle detection and counting using self-developed dual-threshold motion detection algorithms. In particular, the microfluidic channel and interdigital transducers (IDTs) were specially optimized; a heat dissipation system was custom designed to suppress the rise of the fluid temperature; a novel frequency-temperature-curve based method was proposed to determine the appropriate signal driving frequency for the system; an effective treatment protocol that improves the bonding strength between LiNbO3 and PDMS was proposed. Results: At 2 L/min sample flow rate, the separation efficiency of 93.52% and purity of 94.29% for 15 m microbead were achieved in mixed 5m and 15m microbead solution at a 25 dBm RF driving power, the separation efficiency of 92.75% and purity of 91.43% were obtained for 15 m microbead from mixed 10 m and 15 m microbead solution at a driving power of 24 dBm. Conclusions: The results showed that the integrated platform has an excellent capability to seamlessly separate, distinguish, and count microbeads of different sizes. Significance: Such a platform and the design methodologies offer a promising POC solution for label-free cell separation and detection in biomedical diagnostics.