The DOI matches its Crossref record; 162 of the 162 references it cites were found in a registry or an index.
Magnetic nanoparticles: recent advances in synthesis, self-assembly and applications
Abstract
Nanostructured magnetic materials have a variety of promising applications spreading from nano-scale electronic devices, sensors and high-density data storage media to controlled drug delivery and cancer diagnostics/treatment systems. Magnetic nanoparticles offer the most natural and elegant way for fabrication of such (multi-) functional materials. In this review, we briefly summarize the recent progress in the synthesis of magnetic nanoparticles (which now can be done with precise control over the size and surface chemistry), and nanoscale interactions leading to their self-assembly into 1D, 2D or 3D aggregates. Various approaches to self-organization, directed-, or template-assisted assembly of these nanostructures are discussed with the special emphasis on magnetic-field enabled interactions. We also discuss new physical phenomena associated with magnetic coupling between nanoparticles and their interaction with a substrate and the characterization of the physical properties at the nanoscale using various experimental techniques (including scanning quantum interferometry (SQUID) and magnetic force microscopy). Applications of magnetic nanoparticle assemblies in data storage, spintronics, drug delivery, cancer therapy, and prospective applications such as adaptive materials and multifunctional reconfigurable materials are also highlighted.
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Cites
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Magnetic Iron Oxide Nanoparticle (IONP) Synthesis to Applications: Present and Future
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Metadata
- Authors
- Singamaneni, S., Bliznyuk, V. N., Binek, C., & Tsymbal, E. Y.
- Venue
- Journal of Materials Chemistry
- Publisher
- Royal Society of Chemistry (RSC)
- Published
- 2011
- Volume
- 21
- Issue
- 42
- Pages
- 16819
- ISSN
- 0959-9428 (ISSN-L)
- 1364-5501
- OpenAlex
- W2041680221
- Cited by
- 537
- References
- 162
- FWCI
- 13.86
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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