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Cited by 342

The DOI matches its Crossref record; 126 of the 126 references it cites were found in a registry or an index.

Preparation and properties of magnetic nano‐ and microsized particles for biological and environmental separations

Horák, Daniel, Babič, Michal, Macková, Hana, Beneš, Milan J.·2007·Journal of Separation Science

Abstract

The paper presents a critical overview on magnetic nanoparticles and microspheres used as separation media in different fields of chemistry, biochemistry, biology, and environment protection. The preparation of most widely used magnetic iron oxides in appropriate form, their coating or encapsulation in polymer microspheres, and functionalization is discussed in the first part. In the second part, new developments in the main application areas of magnetic composite particles for separation and catalytical purposes are briefly described. They cover separations and isolations of toxic inorganic and organic ions, proteins, and other biopolymers, cells, and microorganisms. Only selected number of relevant papers could be included due to the restricted extent of the review.

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Registry

Crossref · 10.1002/jssc.200700088

Cites

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Metadata

Authors
Horák, D., Babič, M., Macková, H., & Beneš, M. J.
Venue
Journal of Separation Science
Publisher
Wiley
Published
2007-07
Volume
30
Issue
11
Pages
1751-1772
ISSN
  • 1615-9306 (ISSN-L)
  • 1615-9314
OpenAlex
W2106489547
Cited by
342
References
126
FWCI
11.34
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Preparation and properties of magnetic nano‐ and microsized particles for biological and environmental separations. https://app.cochat.ai/papers/10.1002/jssc.200700088
The paper
Horák, D., Babič, M., Macková, H., & Beneš, M. J. (2007). Preparation and properties of magnetic nano‐ and microsized particles for biological and environmental separations. Journal of Separation Science. https://doi.org/10.1002/jssc.200700088

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.