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On-line Access: 2024-08-27

Received: 2023-10-17

Revision Accepted: 2024-05-08

Crosschecked: 2023-11-25

Cited: 0

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Citations:  Bibtex RefMan EndNote GB/T7714

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Bio-Design and Manufacturing  2024 Vol.7 No.1 P.31-42

http://doi.org/10.1007/s42242-023-00257-z


A novel integrated microfluidic chip for on-demand electrostatic droplet charging and sorting


Author(s):  Jinhui Yao, Chunhua He, Jianxin Wang, Canfeng Yang, Ye Jiang, Zhiyong Liu, Guanglan Liao & Tielin Shi

Affiliation(s): 

Corresponding email(s):   zhiyong_liu@hust.edu.cn, guanglan.liao@hust.edu.cn

Key Words:  Copper wire, Droplet generation, Droplet sorting, Microfluidic chips, On-demand charging


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Abstract: 
On-demand droplet sorting is extensively applied for the efficient manipulation and genome-wide analysis of individual cells. However, state-of-the-art microfluidic chips for droplet sorting still suffer from low sorting speeds, sample loss, and labor-intensive preparation procedures. Here, we demonstrate the development of a novel microfluidic chip that integrates droplet generation, on-demand electrostatic droplet charging, and high-throughput sorting. The charging electrode is a copper wire buried above the nozzle of the microchannel, and the deflecting electrode is the phosphate buffered saline in the microchannel, which greatly simplifies the structure and fabrication process of the chip. Moreover, this chip is capable of high-frequency droplet generation and sorting, with a frequency of 11.757 kHz in the drop state. The chip completes the selective charging process via electrostatic induction during droplet generation. On-demand charged microdroplets can arbitrarily move to specific exit channels in a three-dimensional (3D)-deflected electric field, which can be controlled according to user requirements, and the flux of droplet deflection is thereby significantly enhanced. Furthermore, a lossless modification strategy is presented to improve the accuracy of droplet deflection or harvest rate from 97.49% to 99.38% by monitoring the frequency of droplet generation in real time and feeding it back to the charging signal. This chip has great potential for quantitative processing and analysis of single cells for elucidating cell-to-cell variations.

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