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Cited by 284

The DOI matches its Crossref record; 29 of the 29 references it cites were found in a registry or an index.

Magnetic slippery extreme icephobic surfaces

Open access
Irajizad, Peyman, Hasnain, Munib, Farokhnia, Nazanin, Sajadi, Seyed Mohammad, Ghasemi, Hadi·2016·Nature Communications

Abstract

Anti-icing surfaces have a critical footprint on daily lives of humans ranging from transportation systems and infrastructure to energy systems, but creation of these surfaces for low temperatures remains elusive. Non-wetting surfaces and liquid-infused surfaces have inspired routes for the development of icephobic surfaces. However, high freezing temperature, high ice adhesion strength, and high cost have restricted their practical applications. Here we report new magnetic slippery surfaces outperforming state-of-the-art icephobic surfaces with a ice formation temperature of −34 °C, 2–3 orders of magnitude higher delay time in ice formation, extremely low ice adhesion strength (≈2 Pa) and stability in shear flows up to Reynolds number of 10 5. In these surfaces, we exploit the magnetic volumetric force to exclude the role of solid–liquid interface in ice formation. We show that these inexpensive surfaces are universal and can be applied to all types of solids (no required micro/nano structuring) with no compromise to their unprecedented properties.

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Metadata

Authors
Irajizad, P., Hasnain, M., Farokhnia, N., Sajadi, S. M., & Ghasemi, H.
Venue
Nature Communications
Published
2016-11-08
Volume
7
Issue
1
Pages
13395-13395
ISSN
2041-1723 (ISSN-L)
OpenAlex
W2555976726
Cited by
284
References
29
FWCI
27.14
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Magnetic slippery extreme icephobic surfaces. https://app.cochat.ai/papers/10.1038/ncomms13395
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Irajizad, P., Hasnain, M., Farokhnia, N., Sajadi, S. M., & Ghasemi, H. (2016). Magnetic slippery extreme icephobic surfaces. Nature Communications. https://doi.org/10.1038/ncomms13395

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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