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Cited by 265

The DOI matches its Crossref record; 37 of the 37 references it cites were found in a registry or an index.

Purification of Nanoparticles by Size and Shape

Open access
Robertson, James D., Rizzello, Loris, Avila-Olias, Milagros, Gaitzsch, Jens, Contini, Claudia, Magoń, Monika S., Renshaw, Stephen A., Battaglia, Giuseppe·2016·Scientific Reports

Abstract

Producing monodisperse nanoparticles is essential to ensure consistency in biological experiments and to enable a smooth translation into the clinic. Purification of samples into discrete sizes and shapes may not only improve sample quality, but also provide us with the tools to understand which physical properties of nanoparticles are beneficial for a drug delivery vector. In this study, using polymersomes as a model system, we explore four techniques for purifying pre-formed nanoparticles into discrete fractions based on their size, shape or density. We show that these techniques can successfully separate polymersomes into monodisperse fractions.

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Crossref · 10.1038/srep27494

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Metadata

Authors
Robertson, J. D., Rizzello, L., Avila-Olias, M., Gaitzsch, J., Contini, C., Magoń, M. S., Renshaw, S. A., & Battaglia, G.
Venue
Scientific Reports
Published
2016-06-08
Volume
6
Issue
1
Pages
27494-27494
ISSN
2045-2322 (ISSN-L)
OpenAlex
W2410936082
Cited by
265
References
37
FWCI
8.14
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Purification of Nanoparticles by Size and Shape. https://app.cochat.ai/papers/10.1038/srep27494
The paper
Robertson, J. D., Rizzello, L., Avila-Olias, M., Gaitzsch, J., Contini, C., Magoń, M. S., Renshaw, S. A., & Battaglia, G. (2016). Purification of Nanoparticles by Size and Shape. Scientific Reports. https://doi.org/10.1038/srep27494

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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.