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Cited by 1,866

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Block Copolymer Lithography: Periodic Arrays of ~10 11 Holes in 1 Square Centimeter

Park, Miri, Harrison, Christopher, Chaikin, Paul M., Register, Richard A., Adamson, Douglas H.·1997·Science

Abstract

Dense periodic arrays of holes and dots have been fabricated in a silicon nitride–coated silicon wafer. The holes are 20 nanometers across, 40 nanometers apart, and hexagonally ordered with a polygrain structure that has an average grain size of 10 by 10. Spin-coated diblock copolymer thin films with well-ordered spherical or cylindrical microdomains were used as the templates. The microdomain patterns were transferred directly to the underlying silicon nitride layer by two complementary techniques that resulted in opposite tones of the patterns. This process opens a route for nanometer-scale surface patterning by means of spontaneous self-assembly in synthetic materials on length scales that are difficult to obtain by standard semiconductor lithography techniques.

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Crossref · 10.1126/science.276.5317.1401

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Metadata

Authors
Park, M., Harrison, C., Chaikin, P. M., Register, R. A., & Adamson, D. H.
Venue
Science
Published
1997-05-30
Volume
276
Issue
5317
Pages
1401-1404
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
OpenAlex
W2003398981
Cited by
1,866
References
2
FWCI
22.88
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Block Copolymer Lithography: Periodic Arrays of ~10 11 Holes in 1 Square Centimeter. https://app.cochat.ai/papers/10.1126/science.276.5317.1401
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Park, M., Harrison, C., Chaikin, P. M., Register, R. A., & Adamson, D. H. (1997). Block Copolymer Lithography: Periodic Arrays of ~10 11 Holes in 1 Square Centimeter. Science. https://doi.org/10.1126/science.276.5317.1401

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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.