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Cited by 522

The DOI matches its Crossref record; 25 of the 25 references it cites were found in a registry or an index.

Magnetism of Fe, Co and Ni nanowires in self-assembled arrays

Open access
Sellmyer, D J, Zheng, M, Skomski, R·2001·Journal of Physics: Condensed Matter

Abstract

Recent work on magnetic properties of transition-metal nanowire arrays produced by electro-deposition is reviewed. The wires, which are electro-deposited into self-assembled porous anodic alumina, form nearly hexagonal arrays characterized by wire diameters down to less than 10 nm, wire lengths up to about 1 µm, and variable centre-to-centre spacings of the order of 50 nm. The fabrication and structural characterization of the arrays is summarized, magnetic data are presented and theoretical explanations of the behaviour of the wires are given. Emphasis is on extrinsic phenomena such as coercivity, magnetization reversal and interactions of the magnetic nanowires. In particular, we analyse how wire imperfections give rise to magnetic localization and dominate the hysteresis behaviour of the wires. Potential applications are outlined in the last section.

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Crossref · 10.1088/0953-8984/13/25/201

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Metadata

Authors
Sellmyer, D. J., Zheng, M., & Skomski, R.
Venue
Journal of Physics: Condensed Matter
Published
2001-06-07
Volume
13
Issue
25
Pages
R433-R460
ISSN
  • 0953-8984 (ISSN-L)
  • 1361-648X
OpenAlex
W2009432134
Cited by
522
References
25
FWCI
16.98
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Magnetism of Fe, Co and Ni nanowires in self-assembled arrays. https://app.cochat.ai/papers/10.1088/0953-8984/13/25/201
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Sellmyer, D. J., Zheng, M., & Skomski, R. (2001). Magnetism of Fe, Co and Ni nanowires in self-assembled arrays. Journal of Physics: Condensed Matter. https://doi.org/10.1088/0953-8984/13/25/201

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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.