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Cited by 325

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Superhydrophobic polymer-coated copper-mesh; membranes for highly efficient oil–water separation

Crick, Colin R., Gibbins, James A., Parkin, Ivan P.·2013·Journal of Materials Chemistry A

Abstract

A novel filtration system has been developed for the separation of water and hydrophobic solvents. Copper meshes of various pore diameter (297, 251, 178 and 152 μm) were coated with extremely rough silicone elastomer films. Depositions of this polymer were carried out by aerosol assisted chemical vapour deposition. The polymer coating rendered all meshes superhydrophobic, with static water contact angles of 152–167° depending on mesh diameter. The meshes were found to be exceptionally efficient in separating organic solvents (hexane, petroleum ether and toluene) from water. The dual-layered filtration system developed focuses on directing the transport of oil away from water with the highest efficiency. The device provides a scalable solution to many challenges, including microanalysis, filtration and chemical processing.

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Crossref · 10.1039/c3ta10636e

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Metadata

Authors
Crick, C. R., Gibbins, J. A., & Parkin, I. P.
Venue
Journal of Materials Chemistry A
Published
2013
Volume
1
Issue
19
Pages
5943
ISSN
  • 2050-7488 (ISSN-L)
  • 2050-7496
OpenAlex
W2020121493
Cited by
325
References
2
FWCI
11.83
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Superhydrophobic polymer-coated copper-mesh; membranes for highly efficient oil–water separation. https://app.cochat.ai/papers/10.1039/c3ta10636e
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Crick, C. R., Gibbins, J. A., & Parkin, I. P. (2013). Superhydrophobic polymer-coated copper-mesh; membranes for highly efficient oil–water separation. Journal of Materials Chemistry A. https://doi.org/10.1039/c3ta10636e

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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.