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Cited by 265

The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.

Microfluidic stickers

Bartolo, Denis, Degré, Guillaume, Nghe, Philippe, Studer, Vincent·2008·Lab Chip

Abstract

We present how to make and assemble micro-patterned stickers (microPS) to construct high performance plastic microfluidic devices in a few minutes. We take advantage of soft UV imprint techniques to tailor the geometry, the mechanical properties, and the surface chemistry of 2D and 3D microfluidic circuits. The resulting microfluidic stickers substantially overcome the actual performance of the very popular PDMS devices for a wide range of applications, while sharing their celebrated fast and easy processing. To highlight the intrinsic advantages of this method, three important applications are detailed: (i) we show that both aqueous and organic droplets can be produced and stored in stickers without any specific surface coating. (ii) We report on the outstanding pressure resistance of the microPS, which open the way to the transport of viscous complex fluids. (iii) Finally, a simple design strategy is proposed to generate complex flow patterns in interconnected stacks of microPS.

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Crossref · 10.1039/b712368j

Cites

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Citations

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Metadata

Authors
Bartolo, D., Degré, G., Nghe, P., & Studer, V.
Venue
Lab Chip
Published
2008
Volume
8
Issue
2
Pages
274-279
ISSN
  • 1473-0189 (ISSN-L)
  • 1473-0197
OpenAlex
W4232172826
Cited by
265
References
21
FWCI
9.17
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Microfluidic stickers. https://app.cochat.ai/papers/10.1039/b712368j
The paper
Bartolo, D., Degré, G., Nghe, P., & Studer, V. (2008). Microfluidic stickers. Lab Chip. https://doi.org/10.1039/b712368j

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.