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Cited by 464

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Stimuli-responsive polymer vesicles

Li, Min-Hui, Keller, Patrick·2009·Soft Matter

Abstract

Polymer vesicles, commonly called polymersomes, are spherical shell structures in which an aqueous compartment is enclosed by a bilayer membrane made from amphiphilic block copolymers. Compared to liposomes, their low molecular weight analogues, polymersomes have many superior properties (higher toughness, better stability, tailorable membrane properties), which make them attractive candidates for applications including encapsulation, drug delivery, nanoreactors and templates for micro- or nano-structured materials. Many potential applications require the ability to control the release of substances encapsulated in the interior compartment and/or in the hydrophobic core of membrane. To address this goal, polymersomes have to be developed in which a specific stimulus destabilises the vesicle structure. In this article we review the most promising approaches to make stimuli-responsive polymer vesicles that permit the controlled release of encapsulated contents. Stimuli including hydrolysis, oxidation, reduction, pH, temperature and light are discussed and their effect on the chemical and physical structure of the amphiphilic copolymers is also described.

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Metadata

Authors
Li, M.-H., & Keller, P.
Venue
Soft Matter
Published
2009
Volume
5
Issue
5
Pages
927
ISSN
  • 1744-683X (ISSN-L)
  • 1744-6848
OpenAlex
W2002730188
Cited by
464
References
3
FWCI
22.19
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Stimuli-responsive polymer vesicles. https://app.cochat.ai/papers/10.1039/b815725a
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Li, M.-H., & Keller, P. (2009). Stimuli-responsive polymer vesicles. Soft Matter. https://doi.org/10.1039/b815725a

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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.