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A real-time cosine similarity algorithm method for continuous monitoring of dynamic droplet generation processes
- Source :
- AIP Advances, Vol 9, Iss 10, Pp 105201-105201-7 (2019)
- Publication Year :
- 2019
- Publisher :
- AIP Publishing LLC, 2019.
-
Abstract
- Droplet microfluidics is becoming an enabling technology for synthesizing microscale particles and an effective real-time method is essential to monitor the variations in a dynamic droplet generation process. Here, a novel real-time cosine similarity algorithm (RT-CSA) method was developed to investigate the droplet generation process by measuring the droplet generation frequency continuously. The RT-CSA method uses a first-in-first-out (FIFO) similarity vector buffer to store calculated cosine similarities, so that these cosine similarities are reused to update the calculation results once a new frame is captured and stored. For the first time, the RT-CSA method achieved real-time monitoring of dynamic droplet generation processes by updating calculation results over 2,000 times per second, and two pre-microgel droplet generation processes with or without artificial disturbances were monitored closely and continuously. With the RT-CSA method, the disturbances in dynamic droplet generation processes were precisely determined, and following changes were monitored and recorded in real time. This highly effective RT-CSA method could be a powerful tool for further promoting research of droplet microfluidics.
Details
- Language :
- English
- ISSN :
- 21583226
- Volume :
- 9
- Issue :
- 10
- Database :
- Directory of Open Access Journals
- Journal :
- AIP Advances
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.107faef13ede45e28ff520d525cccda0
- Document Type :
- article
- Full Text :
- https://doi.org/10.1063/1.5102131