Automated droplet manipulation enabled by a machine-vision-assisted acoustic tweezer

Abstract

Automated droplet manipulation holds great significance for various biochemical applications, including but limited to heavy metal ions detection. Despite notable progress, contactless-acoustic-tweezer-based automated droplet manipulation on superhydrophobic surfaces is rarely reported. In this work, we introduce a machine-vision-assisted acoustic tweezer (MVAAT) for automated and contactless manipulation of droplets on a superhydrophobic surface. The MVAAT generates ultrasound standing waves between an ultrasonic transducer (UST) and a superhydrophobic surface, inducing acoustic radiation force to facilitate contactless droplet manipulation on the superhydrophobic surface. An industrial-camera-based machine vision system is employed for real-time detection and tracking of droplets, providing precise droplet positions for automated droplet transportation and merging via a UST equipped on a Cartesian robot. Experimental results demonstrate that the proposed MVAAT can transport droplets of various volumes on a superhydrophobic surface along planned paths at considerably high velocities exceeding one centimeter per second. Furthermore, with the vision feedback, the MVAAT can reliably and precisely transport a droplet to a target position, even if the droplet fails to follow the UST during its movement. Moreover, automated merging and patterning of multiple droplets are achieved, showcasing the versatility of the MVAAT. Last, the MVAAT is applied for fluorescence-based Cu2+ detection to showcase its potential for practical biochemical analyses. The proposed MVAAT significantly expands the capability of ultrasound for droplet manipulation on superhydrophobic surfaces, promising numerous practical applications in biology and chemistry.