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Cited by 269

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

Biologically Inspired Surfaces: Broadening the Scope of Roughness**

Nosonovsky, Michael, Bhushan, Bharat·2008·Advanced Functional Materials

Abstract

Superhydrophobicity can be used for many applications that require non‐adhesive and water‐repellent surfaces. A successful design of superhydrophobic surfaces requires a correct assessment of the surface roughness effect on wetting. Roughness is an important property in surface mechanics, physics, chemistry, and biology, and it is critical for many tribological applications. Roughness can be defined in different ways, and the definition should be adequate to the problem under investigation. Our recent studies of biological and biomimetic superhydrophobic surfaces show that traditional roughness parameters, such as the root‐mean‐square, correlation length, or fractal dimension, are not always appropriate for the analysis of wetting. This is, in particular, due to the hierarchical nature of wetting mechanisms and interfaces. We discuss the effect of roughness on wetting mechanisms and relevant roughness parameters and ways to broaden the concept and scope of surface roughness.

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Crossref · 10.1002/adfm.200701195

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Metadata

Authors
Nosonovsky, M., & Bhushan, B.
Venue
Advanced Functional Materials
Publisher
Wiley
Published
2008-03-25
Volume
18
Issue
6
Pages
843-855
ISSN
  • 1616-301X (ISSN-L)
  • 1616-3028
OpenAlex
W2163400195
Cited by
269
References
2
FWCI
13.96
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Biologically Inspired Surfaces: Broadening the Scope of Roughness**. https://app.cochat.ai/papers/10.1002/adfm.200701195
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Nosonovsky, M., & Bhushan, B. (2008). Biologically Inspired Surfaces: Broadening the Scope of Roughness**. Advanced Functional Materials. https://doi.org/10.1002/adfm.200701195

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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.