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Article . 2016
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Advanced Functional Materials
Article . 2016 . Peer-reviewed
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Mechanical Properties of Highly Porous Super Liquid‐Repellent Surfaces

Authors: Maxime Paven; Regina Fuchs; Taro Yakabe; Doris Vollmer; Michael Kappl; Akiko N. Itakura; Hans-Jürgen Butt;

Mechanical Properties of Highly Porous Super Liquid‐Repellent Surfaces

Abstract

Surfaces with self‐cleaning properties are desirable for many applications. Conceptually, super liquid‐repellent surfaces are required to be highly porous on the nano‐ or micrometer scale, which inherently makes them mechanically weak. Optimizing the balance of mechanical strength and liquid repellency is a core aspect toward applications. However, quantitative mechanical testing of porous, super liquid‐repellent surfaces is challenging due to their high surface roughness at different length scales and low stress tolerance. For this reason, mechanical testing is often performed qualitatively. Here, the mechanical responses of soot‐templated super liquid‐repellent surfaces are studied qualitatively by pencil and finger scratching and quantitatively by atomic force microscopy, colloidal probe force measurements, and nanoindentation. In particular, colloidal probe force measurements cover the relevant force and length scales. The effective elastic modulus, the plastic work Wplastic and the effective adhesive work Wadhesive are quantified. By combining quantitative information from force measurements with measurements of surface wetting properties, it is shown that mechanical strength can be balanced against low wettability by tuning the reaction parameters.

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    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    40
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
40
Top 10%
Top 10%
Top 10%
Green
bronze