The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Anti-Icing Superhydrophobic Coatings
Abstract
We use nanoparticle-polymer composites to demonstrate the anti-icing capability of superhydrophobic surfaces and report direct experimental evidence that such surfaces are able to prevent ice formation upon impact of supercooled water both in laboratory conditions and in natural environments. We find that the anti-icing capability of these composites depends not only on their superhydrophobicity but also on the size of the particles exposed on the surface. The critical particle sizes that determine the superhydrophobicity and the anti-icing property are in two different length scales. The effect of particle size on ice formation is explained by using a classical heterogeneous nucleation theory. This result implies that the anti-icing property of a surface is not directly correlated with the superhydrophobicity, and thus, it is uncertain whether a superhydrophobic surface is anti-icing without detailed knowledge of the surface morphology. The result also opens up possibilities for rational design of anti-icing superhydrophobic surfaces by tuning surface textures in multiple length scales.
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Citations
Cites
Wettability of porous surfaces
Cassie, A. B. D., & Baxter, S. (1944) · Transactions of the Faraday Society · doi:10.1039/tf9444000546 · Cited by 13,807
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Liquid-Infused Nanostructured Surfaces with Extreme Anti-Ice and Anti-Frost Performance
Kim, P., Wong, T.-S., Alvarenga, J., Kreder, M. J., Adorno-Martinez, W. E., & Aizenberg, J. (2012) · ACS Nano · doi:10.1021/nn302310q · Cited by 1,316
Application of superhydrophobic coatings as a corrosion barrier: A review
Vazirinasab, E., Jafari, R., & Momen, G. (2018) · Surface and Coatings Technology · doi:10.1016/j.surfcoat.2017.11.053 · Cited by 659
Recent advances in the potential applications of bioinspired superhydrophobic materials
Darmanin, T., & Guittard, F. (2014) · J. Mater. Chem. A · doi:10.1039/c4ta02071e · Cited by 555
Exploiting Topographical Texture To Impart Icephobicity
Meuler, A. J., McKinley, G. H., & Cohen, R. E. (2010) · ACS Nano · doi:10.1021/nn103214q · Cited by 423
Chen, J., Dou, R., Cui, D., Zhang, Q., Zhang, Y., Xu, F., Zhou, X., Wang, J., Song, Y., & Jiang, L. (2013) · ACS Applied Materials & Interfaces · doi:10.1021/am401004t · Cited by 332
Zhang, S., Huang, J., Cheng, Y., Yang, H., Chen, Z., & Lai, Y. (2017) · Small · doi:10.1002/smll.201701867 · Cited by 328
Long-lived superhydrophobic surfaces
Xue, C.-H., & Ma, J.-Z. (2013) · Journal of Materials Chemistry A · doi:10.1039/c2ta01073a · Cited by 316
Xu, Q. F., Liu, Y., Lin, F.-J., Mondal, B., & Lyons, A. M. (2013) · ACS Applied Materials & Interfaces · doi:10.1021/am401668y · Cited by 225
Dynamic Defrosting on Superhydrophobic and Biphilic Surfaces
Gurumukhi, Y., Chavan, S., Sett, S., Boyina, K., Ramesh, S., Sokalski, P., Fortelka, K., Lira, M., Park, D., Chen, J.-Y., et al. (2020) · Matter · doi:10.1016/j.matt.2020.06.029 · Cited by 73
Suppression of Frost Nucleation Achieved Using the Nanoengineered Integral Humidity Sink Effect
Sun, X., & Rykaczewski, K. (2017) · ACS Nano · doi:10.1021/acsnano.6b07505 · Cited by 67
Ma, L., Zhang, Z., Gao, L., Liu, Y., & Hu, H. (2020) · Renewable Energy · doi:10.1016/j.renene.2020.10.013 · Cited by 62
Tian, Y., Xu, Y., Zhu, Z., Liu, Y., Xie, J., Zhang, B., Zhang, H., & Zhang, Q. (2022) · Colloids and Surfaces A: Physicochemical and Engineering Aspects · doi:10.1016/j.colsurfa.2022.129586 · Cited by 56
Park, S.-H., Lee, S., Moreira, D., Bandaru, P. R., Han, I., & Yun, D.-J. (2015) · Scientific Reports · doi:10.1038/srep15430 · Cited by 40
Metadata
- Authors
- Cao, L., Jones, A. K., Sikka, V. K., Wu, J., & Gao, D.
- Venue
- Langmuir
- Publisher
- American Chemical Society (ACS)
- Published
- 2009-10-05
- Volume
- 25
- Issue
- 21
- Pages
- 12444-12448
- ISSN
- 0743-7463 (ISSN-L)
- 1520-5827
- OpenAlex
- W4240997581
- Cited by
- 1,497
- References
- 1
- FWCI
- 18.51
- Type
- journal article
- Language
- en
- Open access
- closed
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