Abstract:
:Droplet microfluidics has attracted significant interests in functional microcapsule synthesis, pharmaceuticals, fine chemicals, cosmetics and biomedical research. The low variability of performing chemical reactions inside droplets could benefit from improved homogeneity and reproducibility. Therefore, accurate and convenient methods are needed to monitor dynamic droplet generation processes. Here, a novel Cosine Similarity Algorithm (CSA) method was developed to monitor the droplet generation frequency accurately and rapidly. With a microscopic droplet generation video clip captured with a high-speed camera, droplet generation frequency can be computed accurately by calculating the cosine similarities between the frames in the video clip. Four kinds of dynamic droplet generation processes were investigated including (1) a stable condition in a single microfluidic channel, (2) a stable condition in multiple microfluidic channels, (3) a single microfluidic channel with artificial disturbances, and (4) microgel fabrication with or without artificial disturbances. For a video clip with 5,000 frames and a spatial resolution of 512 × 62 pixels, droplet generation frequency up to 4,707.9 Hz can be calculated in less than 1.70 s with an absolute relative calculation error less than 0.08%. Artificial disturbances in droplet generation processes can be precisely determined using the CSA method. This highly effective CSA method could be a powerful tool for further promoting the research of droplet microfluidics.
journal_name
Sci Repjournal_title
Scientific reportsauthors
Zhu X,Su S,Fu M,Liu J,Zhu L,Yang W,Jing G,Guo Ydoi
10.1038/s41598-018-28270-8subject
Has Abstractpub_date
2018-07-02 00:00:00pages
9967issue
1issn
2045-2322pii
10.1038/s41598-018-28270-8journal_volume
8pub_type
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