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Cited by 533

The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.

Monodisperse 3 d Transition-Metal (Co,Ni,Fe) Nanoparticles and Their Assembly intoNanoparticle Superlattices

Murray, C.B., Sun, Shouheng, Doyle, Hugh, Betley, T.·2001·MRS Bulletin

Abstract

Magnetic colloids, or ferrofluids, have been studied to probe the fundamental size-dependent properties of magnetic particles and have been harnessed in a variety of applications. The magnetorheological properties of magnetic colloids have been exploited in high-performance bearings and seals. The deposition of magnetic dispersions on platters and tapes marked the earliest embodiments of magnet information storage. Magnetic particles enhance contrast in magnetic resonance imaging and promise future diagnostic and drug delivery applications. The need to explore the scaling limits of magnetic storage technology has motivated the preparation of size-tunable monodisperse magnetic nanoparticles with controlled internal structures. The study of these nanoparticles is critical to efforts to separate the role of defects from intrinsic, finite size effects.

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Crossref · 10.1557/mrs2001.254

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Metadata

Authors
Murray, C. B., Sun, S., Doyle, H., & Betley, T.
Venue
MRS Bulletin
Published
2001-12
Volume
26
Issue
12
Pages
985-991
ISSN
  • 0883-7694 (ISSN-L)
  • 1938-1425
OpenAlex
W2950677993
Cited by
533
References
36
FWCI
20.03
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Monodisperse 3 d Transition-Metal (Co,Ni,Fe) Nanoparticles and Their Assembly intoNanoparticle Superlattices. https://app.cochat.ai/papers/10.1557/mrs2001.254
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Murray, C. B., Sun, S., Doyle, H., & Betley, T. (2001). Monodisperse 3 d Transition-Metal (Co,Ni,Fe) Nanoparticles and Their Assembly intoNanoparticle Superlattices. MRS Bulletin. https://doi.org/10.1557/mrs2001.254

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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.