Gecko Adhesion on Flat and Rough Surfaces: Simulations with a Multi-Scale Molecular Model.

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Eduard-Zintl-Institut für Anorganische und Physikalische Chemie and Profile Area Thermofluids and Interfaces, Technische Universität Darmstadt, Alarich-Weiss-Str. 8, D-64287, Darmstadt, Germany.

Published: September 2022

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A multiscale modeling approach is used to develop a particle-based mesoscale gecko spatula model that is able to link atomistic simulations and mesoscale (0.44 µm) simulations. It is used to study the detachment of spatulae from flat as well as nanostructured surfaces. The spatula model is based on microscopical information about spatulae structure and on atomistic molecular simulation results. Target properties for the coarse-graining result from a united-atom model of gecko keratin in periodic boundary conditions (PBC), previously developed by the authors. Pull-off forces necessary to detach gecko keratin under 2D PBC parallel to the surface are previously overestimated when only a small region of a spatula is examined. It is shown here that this is due to the restricted geometry (i.e., missing peel-off mode) and not model parameters. The spatula model peels off when pulled away from a surface, both in the molecular picture of the pull-off process and in the force-extension curve of non-equilibrium simulations mimicking single-spatula detachment studied with atomic force microscopy equipment. The force field and spatula model can reproduce experimental pull-off forces. Inspired by experimental results, the underlying mechanism that causes pull-off forces to be at a minimum on surfaces of varying roughnesses is also investigated. A clear sigmoidal increase in the pull-off force of spatulae with surface roughness shows that adhesion is determined by the ratio between spatula pad area and the area between surface peaks. Experiments showed a correlation with root-mean-square roughness of the surface, but the results of this work indicate that this is not a causality but depends on the area accessible.

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http://dx.doi.org/10.1002/smll.202201674DOI Listing

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