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Robotic acoustofluidic single-cell picking and placement platform.

Wanqi Li1,2, Qiu Yin3,4, Jiahui Wu5

  • 1National Key Laboratory of Advanced Micro and Nano Manufacture Technology, Shanghai Jiao Tong University, Shanghai, China. xiangchen@sjtu.edu.cn.

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|April 8, 2026
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Summary
This summary is machine-generated.

This study introduces a robotic acoustofluidic platform for precise single-cell manipulation. The system uses machine vision and acoustic tweezers to automate cell picking and placement, improving stability and enabling advanced biomedical applications.

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Area of Science:

  • Biotechnology
  • Microfluidics
  • Robotics

Background:

  • Single-cell manipulation is crucial for understanding cellular heterogeneity and for applications like proteomics and drug screening.
  • Acoustofluidic techniques offer label-free, gentle cell control, but existing methods lack precision and automation.
  • Acoustic streaming causes instability, limiting the use of needle-based acoustic tweezers in biomedicine.

Purpose of the Study:

  • To develop a robotic acoustofluidic platform for automated single-cell picking and placement.
  • To enhance the precision and stability of needle-based acoustic tweezer technology.
  • To enable scalable, low-cost single-cell workflows for various biomedical applications.

Main Methods:

  • Integration of a needle-based acoustic tweezer with a YOLOv8 machine vision module for real-time control.
  • Systematic characterization of excitation voltage and frequency modulation for dynamic manipulation stability.
  • Implementation of a regulation strategy and closed-loop feedback for precise cell handling.
  • Automated positioning of diverse targets (10-100 μm) including microparticles, single cells, and spheroids.
  • Verification of dual-particle co-placement and assessment of cellular integrity post-manipulation.

Main Results:

  • Achieved stable and precise automated picking and placement of various microscale targets.
  • Demonstrated mitigation of acoustic streaming-induced disturbances through dynamic acoustic excitation adjustment.
  • Successfully performed dual-particle co-placement, maintaining cellular viability and structural integrity.
  • Validated the platform's utility for downstream single-cell proteomic analysis.

Conclusions:

  • The developed robotic acoustofluidic platform offers a low-cost, versatile solution for automated single-cell manipulation.
  • This technology enhances precision and stability, overcoming limitations of previous acoustofluidic methods.
  • The platform supports scalable single-cell workflows, paving the way for advanced applications in diagnostics, drug screening, and material synthesis.