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Cited by 2,607

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Soft Lithography in Biology and Biochemistry

Whitesides, George M., Ostuni, Emanuele, Takayama, Shuichi, Jiang, Xingyu, Ingber, Donald E.·2001·Annual Review of Biomedical Engineering

Abstract

▪ Abstract Soft lithography, a set of techniques for microfabrication, is based on printing and molding using elastomeric stamps with the patterns of interest in bas-relief. As a technique for fabricating microstructures for biological applications, soft lithography overcomes many of the shortcomings of photolithography. In particular, soft lithography offers the ability to control the molecular structure of surfaces and to pattern the complex molecules relevant to biology, to fabricate channel structures appropriate for microfluidics, and to pattern and manipulate cells. For the relatively large feature sizes used in biology (≥50 μm), production of prototype patterns and structures is convenient, inexpensive, and rapid. Self-assembled monolayers of alkanethiolates on gold are particularly easy to pattern by soft lithography, and they provide exquisite control over surface biochemistry.

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Crossref · 10.1146/annurev.bioeng.3.1.335

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Metadata

Authors
Whitesides, G. M., Ostuni, E., Takayama, S., Jiang, X., & Ingber, D. E.
Venue
Annual Review of Biomedical Engineering
Published
2001-08
Volume
3
Issue
1
Pages
335-373
ISSN
  • 1523-9829 (ISSN-L)
  • 1545-4274
OpenAlex
W2137034111
Cited by
2,607
References
3
FWCI
8.73
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Soft Lithography in Biology and Biochemistry. https://app.cochat.ai/papers/10.1146/annurev.bioeng.3.1.335
The paper
Whitesides, G. M., Ostuni, E., Takayama, S., Jiang, X., & Ingber, D. E. (2001). Soft Lithography in Biology and Biochemistry. Annual Review of Biomedical Engineering. https://doi.org/10.1146/annurev.bioeng.3.1.335

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.