| Literature DB >> 33103674 |
Peiran Zhang1, Wei Wang, Hai Fu, Joseph Rich, Xingyu Su, Hunter Bachman, Jianping Xia, Jinxin Zhang, Shuaiguo Zhao, Jia Zhou, Tony Jun Huang.
Abstract
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.Entities:
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Year: 2020 PMID: 33103674 PMCID: PMC7688411 DOI: 10.1039/d0lc00538j
Source DB: PubMed Journal: Lab Chip ISSN: 1473-0189 Impact factor: 6.799