Session: 20-17-01: Rising Stars of Mechanical Engineering

Paper Number: 172649

Acoustic Vortex End-Effector Robots for Contactless Object Manipulation 

Robotic manipulation of tiny objects such as microparticles, biomaterials, and droplets holds great promise for advancing research in engineering, biology, and chemistry. However, existing robotic platforms for handling small objects face significant limitations in achieving contactless, high-resolution, four-degrees-of-freedom (4-DOF) manipulation, especially in scenarios that require noninvasive control of objects in regions shielded by barriers such as tissue and skull. To overcome these challenges, in recent years, we have developed a series of robotic platforms, which are equipped with unique contactless end-effectors based on tunable acoustic vortex beams. These systems enable contactless, multifunctional, high-resolution, 4-DOF manipulation of micro- to millimeter-sized objects in three-dimensional (3D) space. Particularly, the robotic end-effectors employ acoustic holography to generate hollow acoustic vortex beams with ring-shaped energy profiles. These beams produce radial acoustic radiation forces that can trap objects within the energy rings. They can also propagate through biological barriers such as tissue and skull, making them suited for the trapping and manipulation of objects in 3D space shielded by biological barriers. Furthermore, the acoustic vortex end-effector robots can be integrated with ultrasound phased array imaging, thereby achieving real-time ultrasound monitoring of the object position during the acoustic object manipulation process.

To demonstrate the capabilities of the acoustic vortex end-effector robots, we have performed a series of experiments, including (i) concentrating live cells in a Petri dish to construct cell spheroids, (ii) trapping flowing micro-objects to create agglomerates and removing the micro-objects for filtration, (iii) translating single particles along complex paths such as two-dimensional (2D) letter-like and 3D helical paths, (iv) trapping, rotating, and translating a zebrafish larva for observing the zebrafish from different directions, as well as (v) rotating, translating, and merging droplets for automated biochemical assays. Moreover, we demonstrated that the acoustic vortex beams of our end-effectors can transmit through a ~6 mm thick tissue with skin and a ~1.6 mm thick skull, and further trap and rotate single objects. Furthermore, we showed that our acoustic vortex end-effector robot can trap and translate an object inside a Y-shaped channel in a 36 mm thick phantom made of synthetic gelatin to mimic a tissue with a branched blood vessel. Finally, the acoustic vortex end-effector robot was combined with an ultrasound phased array imaging system to monitor the translation of an acoustically trapped object along a complex letter-like path. We believe that the successful development of the acoustic vortex end-effector robots will advance a wide range of applications, such as contactless handling of delicate biological samples (e.g., embryos, worms, zebrafish larvae, etc.) for separation and sorting, translation of objects in regions with biological barriers (e.g., tissue and skull), arranging of micro-objects for controlled self-assembly, and arranging cell distributions for biomanufacturing.

Presenting Author: Zhenhua Tian Virginia Tech

Presenting Author Biography: Dr. Zhenhua Tian received his Ph.D. in Mechanical Engineering from the University of South Carolina in December 2015 and completed postdoctoral training at Duke University in August 2019. He is currently an Assistant Professor in the Department of Mechanical Engineering at Virginia Tech. He received the College of Engineering Outstanding New Assistant Professor Award and the NSF CAREER Award. His research focuses on acoustics-based manipulation of nano- to millimeter-scale matter. More details about this research area can be found on the website of the Acoustics and Functional Materials Laboratory (https://sites.google.com/view/vt-acoustics/home).

Authors:

Zhenhua Tian Virginia Tech