Acoustic-Based Microbubble Grippers for Automatic On-Chip Selection of Spherical Microrobot Models
Spherical micro/nanorobots are reported as attractive candidates in nano-surgery, contamination degradation, analytical chemistry, medical engineering, etc. Unlike macroscopic robots, the standard fabrication and inspection strategy to control the high quality of microrobots are rarely explored before. Overcoming the geometrical discrepancy is now essential to keep an identical locomotion behavior for spherical microrobot individuals for complex usages. Herein, acoustic-based microbubble grippers are proposed controlled by a machine vision system to realize agile recognition and sorting of unqualified spherical microrobot models. Theoretical analysis and numerical simulation reveal the basic grabbing mechanisms via acoustic stimuli. The acoustic resonation of microbubbles can generate a locally enhanced acoustic field, attracting microrobots toward the bubble surface by the acoustic forces. The viscosity of microfluid makes it possible to instantaneously grab or release just by controlling the microbubble activation. Further, a machine vision-based monitor and control system is proposed to enable automatic control for the entire process. Based on extracted characteristic parameters, target microrobot models are quickly selected and grabbed out. It is expected that such a combination of microgrippers with an advanced control system will pave the way for high-qualified inspection for microrobots and improve their unique versatility in myriad micromanipulation scenarios.
危险品化学品经营许可证（带存储）