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Deterministic droplet coding via acoustofluidics

delete2020-01-01
delete14
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OA
AI
P
Peiran Zhang
王伟 (Wei Wang)
付海 (Hai Fu)
J
Joseph Rich
X
Xingyu Su
H
Hunter Bachman
J
Jianping Xia
J
Jinxin Zhang
S
Shuaiguo Zhao
周嘉 (Jia Zhou) *
T
Tony Jun Huang *
DOI:10.1039/d0lc00538jdelete
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Abstract

Abstract

En 中文
Droplet microfluidics has become an indispensable tool for biomedical research and lab-on-a-chip applications owing to its unprecedented throughput, precision, and cost-effectiveness. Although droplets can be generated and screened in a high-throughput manner, the inability to label the inordinate amounts of droplets hinders identifying the individual droplets after generation. Herein, we demonstrate an acoustofluidic platform that enables on-demand, real-time dispensing, and deterministic coding of droplets based on their volumes. By dynamically splitting the aqueous flow using an oil jet triggered by focused traveling surface acoustic waves, a sequence of droplets with deterministic volumes can be continuously dispensed at a throughput of 100 Hz. These sequences encode barcoding information through the combination of various droplet lengths. As a proof-of-concept, we encoded droplet sequences into end-to-end packages (e.g., a series of 50 droplets), which consisted of an address barcode with binary volumetric combinations and a sample package with consistent volumes for hosting analytes. This acoustofluidics-based, deterministic droplet coding technique enables the tagging of droplets with high capacity and high error-tolerance, and can potentially benefit various applications involving single cell phenotyping and multiplexed screening.
Keywords:
QUANTUM-DOT BARCODES
MICROFLUIDIC SYSTEM
GENERATION
ACOUSTICS
DNA
DRIVEN
CELLS
SIZE
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Journal

L
Lab on a Chip
IF:
5.4
Papers:
9.0K
Citations:
3.3W

Organization

D
Duke University
Scholars:
6.3W
Papers: 5.7W
Citations: 6.5W
F
fudan university
Scholars:
11.6W
Papers: 7.7W
Citations: 121