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Cited by 269

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Nanoemulsions: the properties, methods of preparation and promising applications

Open access
Koroleva, M Yu, Yurtov, Evgenii V·2012·Russian Chemical Reviews

Abstract

The properties of nanoemulsions and various methods for their preparation including the high-energy and low-energy emulsification methods and the combined methods are reviewed. Among the high-energy methods, the emphasis is placed on high-energy stirring, ultrasonic emulsification, high-pressure homogenization including microfluidics and membrane emulsification. Among the low-energy emulsification methods, the attention is focused on the phase inversion temperature method, the emulsion inversion point method and the spontaneous emulsification. Using a combined method, which includes the high-energy and low-energy emulsification, it is possible to prepare reverse nanoemulsions in highly viscous systems. Main advantages and limitations of different methods of nanoemulsion preparation are discussed and the potential fields of nanoemulsion applications are considered. The bibliography includes 255 references.

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Crossref · 10.1070/rc2012v081n01abeh004219

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Metadata

Authors
Koroleva, M. Y., & Yurtov, E. V.
Venue
Russian Chemical Reviews
Published
2012-01-31
Volume
81
Issue
1
Pages
21-43
ISSN
  • 0036-021X (ISSN-L)
  • 1468-4837
OpenAlex
W2115147207
Cited by
269
References
3
FWCI
5.69
Type
journal article
Language
en
Open access
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CoChat. (2026). Citation check: Nanoemulsions: the properties, methods of preparation and promising applications. https://app.cochat.ai/papers/10.1070/rc2012v081n01abeh004219
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Koroleva, M. Y., & Yurtov, E. V. (2012). Nanoemulsions: the properties, methods of preparation and promising applications. Russian Chemical Reviews. https://doi.org/10.1070/rc2012v081n01abeh004219

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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.