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Cited by 787

The DOI matches its Crossref record; 134 of the 134 references it cites were found in a registry or an index.

Superhydrophobic Surfaces: Insights from Theory and Experiment

Open access
Parvate, Sumit, Dixit, Prakhar, Chattopadhyay, Sujay·2020·The Journal of Physical Chemistry B

Abstract

Biomimetic nanosurfaces with distinct wettability and versatility have found special enthusiasm in both fundamental research and industrial applications. With the advent of nanotechnology, it is doable to acclimate surface architecture and surface chemistry to attain superhydrophobicity. The uniqueness of superhydrophobic surfaces arises from various phenomenal advances, and its progress is expected to continue for decades in the future. In this Review Article, we discuss recent progress made in defining physical aspects of numerical modeling, experimental practices adopted, and applications of superhydrophobic surfaces. First, we revisit various classical models of superhydrophobicity and recent theoretical advances achieved related to the wetting phenomena. Subsequently, we emphasize various precursors and advance fabrication strategies adopted to fabricate superhydrophobic surfaces. In the following section, we take up various potential applications and appropriate working principles to explain wettability phenomena. Finally, some general conclusions are drawn along with proposed guidelines for designing robust superhydrophobic coatings.

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Crossref · 10.1021/acs.jpcb.9b08567

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Metadata

Authors
Parvate, S., Dixit, P., & Chattopadhyay, S.
Venue
The Journal of Physical Chemistry B
Published
2020-01-13
Volume
124
Issue
8
Pages
1323-1360
ISSN
  • 1520-5207 (ISSN-L)
  • 1520-6106
OpenAlex
W3000318384
Cited by
787
References
134
FWCI
23.97
Type
journal article
Language
en
Open access
hybrid

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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.