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DOI 10.1098/rsta.2016.0184

Медицинская библиотека · Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2016

Superhydrophobicity of the gecko toe pad: biological optimization versus laboratory maximization.

Stark Alyssa Y, Subarajan Shairani, Jain Dharamdeep, Niewiarowski Peter H, Dhinojwala Ali

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Аннотация

While many gecko-inspired hierarchically structured surfaces perform as well as or better than the natural adhesive system, these designs often fail to function across a variety of contexts. For example, the gecko can adhere to rough, wet and dirty surfaces; however, most synthetic mimics cannot maintain function when faced with a similar situation. The solution to this problem lies in a more thorough investigation of the natural system. Here, we review the adhesive system of the gecko toe pad, as well as the far less-well-studied anti-adhesive system that results from the chemistry and structure of the toe pad (superhydrophobicity). This paradoxical relationship serves as motivation to study functional optimization at the system level. As an example, we experimentally investigate the role of surface lipids in adhesion and anti-adhesion, and find a clear performance trade-off related to shear adhesion in air on a hydrophilic surface. This represents the first direct investigation of the role of surface lipids in gecko adhesion and anti-adhesion, and supports the argument that a system-level approach is necessary to elucidate optimization in biological systems. Without such an approach, bioinspired designs will be limited in functionality and context, especially compared to the natural systems they mimic.This article is part of the themed issue 'Bioinspired hierarchically structured surfaces for green science'.

Для цитирования: Stark Alyssa Y, Subarajan Shairani, Jain Dharamdeep, Niewiarowski Peter H, Dhinojwala Ali. Superhydrophobicity of the gecko toe pad: biological optimization versus laboratory maximization.. Philosophical transactions. Series A, Mathematical, physical, and engineering sciences. 2016. DOI: 10.1098/rsta.2016.0184.

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