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Cited by 174

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Molding of Deep Polydimethylsiloxane Microstructures for Microfluidics and Biological Applications

Folch, A., Ayon, A., Hurtado, O., Schmidt, M. A., Toner, M.·1999·Journal of Biomechanical Engineering

Abstract

Here we demonstrate the microfabrication of deep (>25 μm) polymeric microstructures created by replica-molding polydimethylsiloxane (PDMS) from microfabricated Si substrates. The use of PDMS structures in microfluidics and biological applications is discussed. We investigated the feasibility of two methods for the microfabrication of the Si molds: deep plasma etch of silicon-on-insulator (SOI) wafers and photolithographic patterning of a spin-coated photoplastic layer. Although the SOI wafers can be patterned at higher resolution, we found that the inexpensive photoplastic yields similar replication fidelity. The latter is mostly limited by the mechanical stability of the replicated PDMS structures. As an example, we demonstrate the selective delivery of different cell suspensions to specific locations of a tissue culture substrate resulting in micropatterns of attached cells.

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Crossref · 10.1115/1.2798038

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Metadata

Authors
Folch, A., Ayon, A., Hurtado, O., Schmidt, M. A., & Toner, M.
Venue
Journal of Biomechanical Engineering
Published
1999-02-01
Volume
121
Issue
1
Pages
28-34
ISSN
  • 0148-0731 (ISSN-L)
  • 1528-8951
OpenAlex
W2058238342
Cited by
174
References
1
FWCI
10.51
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Molding of Deep Polydimethylsiloxane Microstructures for Microfluidics and Biological Applications. https://app.cochat.ai/papers/10.1115/1.2798038
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Folch, A., Ayon, A., Hurtado, O., Schmidt, M. A., & Toner, M. (1999). Molding of Deep Polydimethylsiloxane Microstructures for Microfluidics and Biological Applications. Journal of Biomechanical Engineering. https://doi.org/10.1115/1.2798038

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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.