Welcome in! We are the 2024 Acousto Robotics! Below is the detalied of our project!
Final presentation
These are our team members and each person in charge of different part as show below:




Haojun Xu
Open CV
Electronic
Yujing Lu
Acoustics
Arduino
Yuqi Wu
3D printing
Website
Zhiyu Zhao
Arduino
Hardware
Abstract
Droplet manipulation in microfluidic systems plays a crucial role in advancing fields such as biomedical research, drug discovery, chemical synthesis, and lab-on-a-chip technologies. This study presents the design and operation of a transducer array device that uses acoustic waves to achieve precise, non-contact control of droplet movement. The array, composed of piezoelectric transducers, generates localized acoustic fields that can dynamically manipulate droplets by altering signal frequency, amplitude, and phase. Key applications include high-throughput screening, biological sample handling, and controlled drug delivery. However, challenges such as maintaining control precision, ensuring material compatibility, and managing large-scale throughput are critical barriers to broader implementation. To address these, we propose future enhancements, including the integration of advanced feedback systems, scalable multichannel designs, and the use of machine learning for adaptive control. This research outlines both the capabilities and limitations of transducer-based droplet manipulation, highlighting its potential to revolutionize microfluidic operations in diverse scientific and industrial settings.
Introduction

Droplet manipulation has emerged as a pivotal technique in microfluidics, enabling precise control over the assemble[1], movement and merging[1-2]. This ability is critical for a wide range of applications, including biological assays, drug screening, chemical synthesis, and lab-on-a-chip systems. Traditional methods of droplet manipulation, such as mechanical pumps or electric fields, often involve direct contact with the droplets, posing risks of contamination, limited flexibility, or reduced precision. To overcome these limitations, acoustic-based droplet manipulation using transducer arrays has gained significant attention due to its non-invasive, highly adaptable, and precise control[3-4]. Although some current methods use acoustic waves to realize particle movement, merging[5], and assembly[6], these methods require manual adjustment of the function generator, making automatic particle movement unattainable. To address this issue and achieve automatic particle movement in mid-air using low-cost acoustic technology, we developed an acousto-robotic system by combining OpenCV and an Arduino board with an ultrasonic transducer.
Project goal
Our project aims to explore and implement the manipulation of small particles/cells in mid-air using acoustic technology in low lost. By leveraging precisely controlled acoustic waves, we seek to establish a non-contact, automatic method for the movement, alignment, and aggregation of particles/cells. This project will advance the understanding of acoustic particle/cells control in open environments, with potential applications in fields such as material assembly, microfluidics, and contactless handling systems.
System decomposition



Current circuit

Project Design Process
Section 1: Working mechanism

Section 2 : Simulation
Frequency adjustment
Frequency adjustment
Section 3 : Experimental verification
Frequency adjustment
Phase adjustment
Section 4: Arduino Control




Section 5 : open CV
Open CV recognizes the position of ball
PID control
Result

Summary and future work
In our future work, we will extend the manipulation of particle from gas environments to liquid environments, enabling precise drug release through controlled droplets within liquids to realize cancer treatment. This advancement will further facilitate targeted drug delivery within tumor microenvironments, paving the way for effective cancer treatments.
Reference
[1] A. F. Demirörs, P. P. Pillai, B. Kowalczyk, B. A. Grzybowski, Nature 2013, 503, 99-103.
[2] A. Aubret, M. Youssef, S. Sacanna, J. Palacci, Nature Physics 2018, 14,1114-1118.
[3] F. Guo, P. Li, J.B. French, Z. M. Mao, H. Zhao, S. X. Li, N. Nama, J. R. Fick, S. J. Benkovic,T. J. Huang, Proc. Natl. Acad. Sci. U. S. A. 2015, 112, 43-48.
[4] D. Kamsma, P.Bochet, F. Oswald, N. Alblas, S. Goyard, G. J. L. Wuite, E. J. G. Peterman, T.Rose, Cell Rep. 2018, 24, 3008-3016.
[5] P. R. Zhang, C. Y. Chen, X. Y. Su, O. Mai, Y. Y. Gu, Z. H. Tian, H. D. Zhu, Z. W. Zhong, H. Fu, S. J. Yang, K. Chakrabarty, T. J. Huang, Science Advances 2020, 6.
[6] S. J. Yang, Z. H. Tian, Z. Y. Wang, J. Rufo, P. Li, J. Mai, J. P. Xia, H. Bachman, P. H. Huang, M. X. Wu, C. Y. Chen, L. P. Lee, T. J. Huang, Nature Materials 2022, 21, 540-+.