Efficient Particle Manipulation Using Contraction–Expansion Microchannels Embedded with Hook-Shaped Arrays
Inertial microfluidics, as an efficient method for the manipulation of micro-/nanoparticles, has garnered significant attention due to its advantages of high throughput, structural simplicity, no need for external fields, and sheathless operation. Common structures include straight channels, contrac...
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Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2025-01-01
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Series: | Micromachines |
Subjects: | |
Online Access: | https://www.mdpi.com/2072-666X/16/1/83 |
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Summary: | Inertial microfluidics, as an efficient method for the manipulation of micro-/nanoparticles, has garnered significant attention due to its advantages of high throughput, structural simplicity, no need for external fields, and sheathless operation. Common structures include straight channels, contraction–expansion array (CEA) channels, spiral channels, and serpentine channels. In this study, we developed a CEA channel embedded with hook-shaped microstructures to modify the characteristics of vortices. Through experimental studies, we investigated the particles’ migration mechanisms within the proposed structure. The findings indicated that, in comparison to conventional rectangular microstructures, the particles within the hook-shaped microstructured CEA channels experienced a more pronounced influence from inertial lift forces. Moreover, the magnitude of the second flow within the novel configuration was directly proportional to the channel width, the length of the expansion segment, and the embedding depth of the microstructure. The innovative structure was subsequently employed for particle trapping, focusing, and separation. The experimental outcomes revealed focusing efficiency of up to 99.1% and sorting efficiency of up to 97%. This research holds the potential to enhance the foundational theory of Dean flows and broaden the application spectrum of inertial contraction–expansion microfluidic chips. |
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ISSN: | 2072-666X |