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Digital acoustofluidics enables contactless and programmable liquid handling

Author

Listed:
  • Steven Peiran Zhang

    (Duke University)

  • James Lata

    (The Pennsylvania State University, University Park)

  • Chuyi Chen

    (Duke University)

  • John Mai

    (University of Southern California)

  • Feng Guo

    (The Pennsylvania State University, University Park)

  • Zhenhua Tian

    (Duke University)

  • Liqiang Ren

    (The Pennsylvania State University, University Park)

  • Zhangming Mao

    (The Pennsylvania State University, University Park)

  • Po-Hsun Huang

    (Duke University)

  • Peng Li

    (The Pennsylvania State University, University Park)

  • Shujie Yang

    (Duke University)

  • Tony Jun Huang

    (Duke University)

Abstract

For decades, scientists have pursued the goal of performing automated reactions in a compact fluid processor with minimal human intervention. Most advanced fluidic handling technologies (e.g., microfluidic chips and micro-well plates) lack fluid rewritability, and the associated benefits of multi-path routing and re-programmability, due to surface-adsorption-induced contamination on contacting structures. This limits their processing speed and the complexity of reaction test matrices. We present a contactless droplet transport and processing technique called digital acoustofluidics which dynamically manipulates droplets with volumes from 1 nL to 100 µL along any planar axis via acoustic-streaming-induced hydrodynamic traps, all in a contamination-free (lower than 10−10% diffusion into the fluorinated carrier oil layer) and biocompatible (99.2% cell viability) manner. Hence, digital acoustofluidics can execute reactions on overlapping, non-contaminated, fluidic paths and can scale to perform massive interaction matrices within a single device.

Suggested Citation

  • Steven Peiran Zhang & James Lata & Chuyi Chen & John Mai & Feng Guo & Zhenhua Tian & Liqiang Ren & Zhangming Mao & Po-Hsun Huang & Peng Li & Shujie Yang & Tony Jun Huang, 2018. "Digital acoustofluidics enables contactless and programmable liquid handling," Nature Communications, Nature, vol. 9(1), pages 1-11, December.
    • Handle: RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-05297-z
    DOI: 10.1038/s41467-018-05297-z
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    Cited by:

    1. Jiawei Sun & Bin Yang & Nektarios Koukourakis & Jochen Guck & Juergen W. Czarske, 2024. "AI-driven projection tomography with multicore fibre-optic cell rotation," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    2. Jan Durrer & Prajwal Agrawal & Ali Ozgul & Stephan C. F. Neuhauss & Nitesh Nama & Daniel Ahmed, 2022. "A robot-assisted acoustofluidic end effector," Nature Communications, Nature, vol. 13(1), pages 1-13, December.

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