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Cited by 285

The DOI matches its Crossref record; 140 of the 140 references it cites were found in a registry or an index.

Nanoparticles: Synthesis, characteristics, and applications in analytical and other sciences

Sajid, Muhammad, Płotka-Wasylka, Justyna·2020·Microchemical Journal

Abstract

Abstract Nanoparticles (NPs) are widely employed in different research areas, ranging from analytical chemistry and environmental science to medicine, the agriculture and pharmaceutical industry. This is mainly due to the unique characteristics of NPs and the novelty they introduce in such applications. In analytical chemistry, the role of NPs can differ depending on the nature of the steps involved in analytical process. NPs are probably most useful for detection, but sample preparation has also profited from them. For instance, NPs can advantageously replace conventional sorbents for solid-phase extraction. Moreover, NPs are being increasingly used as stationary phases in gas and liquid chromatography or electrochromatography. In this review, a brief summary on the classification, synthesis methods, and properties of NPs is given. Moreover, the examples of applications in different research area are shortly presented. However, the merits of this work are to present the use of NPs in analytical chemistry field.

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Metadata

Authors
Sajid, M., & Płotka-Wasylka, J.
Venue
Microchemical Journal
Publisher
Elsevier BV
Published
2020-05
Volume
154
Pages
104623
ISSN
0026-265X (ISSN-L)
OpenAlex
W2999333082
Cited by
285
References
140
FWCI
14.84
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Nanoparticles: Synthesis, characteristics, and applications in analytical and other sciences. https://app.cochat.ai/papers/10.1016/j.microc.2020.104623
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Sajid, M., & Płotka-Wasylka, J. (2020). Nanoparticles: Synthesis, characteristics, and applications in analytical and other sciences. Microchemical Journal. https://doi.org/10.1016/j.microc.2020.104623

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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.