
Nanohydrogel Brushes for Switchable Underwater Adhesion
Author(s) -
Shuanhong Ma,
Michele Scaraggi,
Lin Peng,
Bo Yu,
Daoai Wang,
Daniele Dini,
Feng Zhou
Publication year - 2017
Publication title -
journal of physical chemistry. c./journal of physical chemistry. c
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.401
H-Index - 289
eISSN - 1932-7455
pISSN - 1932-7447
DOI - 10.1021/acs.jpcc.7b01305
Subject(s) - adhesion , dissipation , materials science , nanotechnology , membrane , mechanism (biology) , underwater , substrate (aquarium) , work (physics) , computer science , composite material , mechanical engineering , engineering , chemistry , geology , biochemistry , physics , philosophy , oceanography , epistemology , thermodynamics
of the related article: In nature, living systems commonly adopt the switchable friction/adhesion mechanism during locomotion. For example, geckos can move on ceilings, relying on the reversible attachment and detachment of their feet on substrate surfaces. Inspired by this scientists have used different materials to mimic natural dynamic friction/adhesion systems. However, synthetic systems usually cannot work in water environments and are also limited to single-contact interfaces, while nature has provided living systems with complex features to perform energy dissipation and adhere on multiple contact interfaces. Here, for the first time, we report the design, synthesis, and testing of a novel double-sided synthetic construct that relies on nanohydrogel brushes to provide simultaneous friction switching on each side of the membrane that separates the nanohydrogel fibers. This highly tunable response is linked to the swelling and shrinkage of the brushes in basic/acid media. Such a system shows three different friction states, which depend on the combination of pH control of the two membrane sides. Importantly, each side of the membrane can independently provide continuous but stable friction switching from high to ultralow friction coefficients in a wet environment under high load conditions. An in-depth theoretical study is performed to explore the mechanisms governing the hydration state responsible for the observed switching. This novel design opens a promising route for the development of new solutions for intelligent devices, which can adapt to multistimulus-responsive complex environments.The dataset file names are given by the related figure names. Furthermore, the data file are in Origin format (.opj), ASCII data (.dat) and Mathematica (.nb).Abstract of the related article: In nature, living systems commonly adopt the switchable friction/adhesion mechanism during locomotion. For example, geckos can move on ceilings, relying on the reversible attachment and detachment of their feet on substrate surfaces. Inspired by this scientists have used different materials to mimic natural dynamic friction/adhesion systems. However, synthetic systems usually cannot work in water environments and are also limited to single-contact interfaces, while nature has provided living systems with complex features to perform energy dissipation and adhere on multiple contact interfaces. Here, for the first time, we report the design, synthesis, and testing of a novel double-sided synthetic construct that relies on nanohydrogel brushes to provide simultaneous friction switching on each side of the membrane that separates the nanohydrogel fibers. This highly tunable response is linked to the swelling and shrinkage of the brushes in basic/acid media. Such a system shows three different friction states, which depend on the combination of pH control of the two membrane sides. Importantly, each side of the membrane can independently provide continuous but stable friction switching from high to ultralow friction coefficients in a wet environment under high load conditions. An in-depth theoretical study is performed to explore the mechanisms governing the hydration state responsible for the observed switching. This novel design opens a promising route for the development of new solutions for intelligent devices, which can adapt to multistimulus-responsive complex environments. The dataset file names are given by the related figure names. Furthermore, the data file are in Origin format (.opj), ASCII data (.dat) and Mathematica (.nb)