ArticleMicrosystems & nanoengineering2024
Twisted fiber microfluidics: a cutting-edge approach to 3D spiral devices.
Article in Microsystems & nanoengineering, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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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.
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Who cites it
2 citing papers in PubMed.
- Design and Performance Analysis of Spiral Microchannels for Efficient Particle Separation Using Inertial Microfluidics.Micromachines · 2025Article
- Synergistic potential of stem cells and microfluidics in regenerative medicine.Molecular and cellular biochemistry · 2025Review
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The development of 3D spiral microfluidics has opened new avenues for leveraging inertial focusing to analyze small fluid volumes, thereby advancing research across chemical, physical, and biological disciplines. While traditional straight microchannels rely solely on inertial lift forces, the novel spiral geometry generates Dean drag forces, eliminating the necessity for external fields in fluid manipulation. Nevertheless, fabricating 3D spiral microfluidics remains a labor-intensive and costly endeavor, hindering its widespread adoption. Moreover, conventional lithographic methods primarily yield 2D planar devices, thereby limiting the selection of materials and geometrical configurations. To address these challenges, this work introduces a streamlined fabrication method for 3D spiral microfluidic devices, employing rotational force within a miniaturized thermal drawing process, termed as mini-rTDP. This innovation allows for rapid prototyping of twisted fiber-based microfluidics featuring versatility in material selection and heightened geometric intricacy. To validate the performance of these devices, we combined computational modeling with microtomographic particle image velocimetry (
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