Evidence map›Paper›PMID 35744496›Full record

ArticleMicromachines2022

Characterization of Fluidic-Barrier-Based Particle Generation in Centrifugal Microfluidics.

Masoud Madadelahi, Javid Azimi-Boulali, Marc Madou, Sergio Omar Martinez-Chapa

Abstract read
In one paragraph

Article in Micromachines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
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  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Masoud MadadelahiSchool of Engineering and Sciences, Tecnológico de Monterrey, Ave. Eugenio Garza Sada 2501, Monterrey 64849, NL, Mexico.ORCID 0000-0002-5301-3994
Javid Azimi-BoulaliSchool of Engineering and Sciences, Tecnológico de Monterrey, Ave. Eugenio Garza Sada 2501, Monterrey 64849, NL, Mexico.ORCID 0000-0003-3322-2569
Marc MadouDepartment of Mechanical and Aerospace Engineering, University of California Irvine, Irvine, CA 92697, USA.ORCID 0000-0003-4847-3117
Sergio Omar Martinez-ChapaSchool of Engineering and Sciences, Tecnológico de Monterrey, Ave. Eugenio Garza Sada 2501, Monterrey 64849, NL, Mexico.

Funding

The authors would like to acknowledge the financial support provided by the Federico Baur Endowed Chair in Nanotechnology (0020240I03). J.A.-B. acknowledges funding from CONACYT through a doctoral scholarship. S.O.M.-C. and M.M acknowledge funding from CO 0020240I03
6 · The paper itself

Abstract

The fluidic barrier in centrifugal microfluidic platforms is a newly introduced concept for making multiple emulsions and microparticles. In this study, we focused on particle generation application to better characterize this method. Because the phenomenon is too fast to be captured experimentally, we employ theoretical models to show how liquid polymeric droplets pass a fluidic barrier before crosslinking. We explain how secondary flows evolve and mix the fluids within the droplets. From an experimental point of view, the effect of different parameters, such as the barrier length, source channel width, and rotational speed, on the particles' size and aspect ratio are investigated. It is demonstrated that the barrier length does not affect the particle's ultimate velocity. Unlike conventional air gaps, the barrier length does not significantly affect the aspect ratio of the produced microparticles. Eventually, we broaden this concept to two source fluids and study the importance of source channel geometry, barrier length, and rotational speed in generating two-fluid droplets.

Indexed as

alginate microparticlecentrifugal microfluidicsdroplet generationfluidic barrierthree-phase model

Identifiers

PMID35744496
PMCPMC9228483

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.