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Cited by 2,104

The DOI matches its Crossref record; 22 of the 22 references it cites were found in a registry or an index.

Ultrahigh-Density Nanowire Arrays Grown in Self-Assembled Diblock Copolymer Templates

Thurn-Albrecht, T., Schotter, J., Kästle, G. A., Emley, N., Shibauchi, T., Krusin-Elbaum, L., Guarini, K., Black, C. T., Tuominen, M. T., Russell, T. P.·2000·Science

Abstract

We show a simple, robust, chemical route to the fabrication of ultrahigh-density arrays of nanopores with high aspect ratios using the equilibrium self-assembled morphology of asymmetric diblock copolymers. The dimensions and lateral density of the array are determined by segmental interactions and the copolymer molecular weight. Through direct current electrodeposition, we fabricated vertical arrays of nanowires with densities in excess of 1.9 × 10 11 wires per square centimeter. We found markedly enhanced coercivities with ferromagnetic cobalt nanowires that point toward a route to ultrahigh-density storage media. The copolymer approach described is practical, parallel, compatible with current lithographic processes, and amenable to multilayered device fabrication.

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Crossref · 10.1126/science.290.5499.2126

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Metadata

Authors
Thurn-Albrecht, T., Schotter, J., Kästle, G. A., Emley, N., Shibauchi, T., Krusin-Elbaum, L., Guarini, K., Black, C. T., Tuominen, M. T., & Russell, T. P.
Venue
Science
Published
2000-12-15
Volume
290
Issue
5499
Pages
2126-2129
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
OpenAlex
W2061798607
Cited by
2,104
References
22
FWCI
56.07
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Ultrahigh-Density Nanowire Arrays Grown in Self-Assembled Diblock Copolymer Templates. https://app.cochat.ai/papers/10.1126/science.290.5499.2126
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Thurn-Albrecht, T., Schotter, J., Kästle, G. A., Emley, N., Shibauchi, T., Krusin-Elbaum, L., Guarini, K., Black, C. T., Tuominen, M. T., & Russell, T. P. (2000). Ultrahigh-Density Nanowire Arrays Grown in Self-Assembled Diblock Copolymer Templates. Science. https://doi.org/10.1126/science.290.5499.2126

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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.