Materzok, Tobias ; Eslami, Hossein ; Gorb, Stanislav N. ; Müller‐Plathe, Florian (2023)
Understanding Humidity‐Enhanced Adhesion of Geckos: Deep Neural Network‐Assisted Multi‐Scale Molecular Modeling.
In: Small : nano micro, 19 (22)
doi: 10.1002/smll.202206085
Artikel, Bibliographie
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Kurzbeschreibung (Abstract)
A higher relative humidity leads to an increased sticking power of gecko feet to surfaces. The molecular mechanism responsible for this increase, however, is not clear. Capillary forces, water mediating keratin‐surface contacts and water‐induced softening of the keratin are proposed as candidates. In previous work, strong evidence for water mediation is found but indirect effects via increased flexibility are not completely ruled out. This article studies the latter hypothesis by a bottom‐up coarse‐grained mesoscale model of an entire gecko spatula designed without explicit water particles, so that capillary action and water‐mediation are excluded. The elasticity of this model is adjusted with a deep neural network to atomistic elastic constants, including water at different concentrations. Our results show clearly that on nanoscopic flat surfaces, the softening of keratin by water uptake cannot nearly account for the experimentally observed increase in gecko sticking power. Here, the dominant mechanism is the mediation of keratin‐surface contacts by intervening water molecules. This mechanism remains important on nanostructured surfaces. Here, however, a water‐induced increase of the keratin flexibility may enable the spatula to follow surface features smaller than itself and thereby increase the number of contacts with the surface. This leads to an appreciable but not dominant contribution to the humidity‐increased adhesion. Recently, by atomistic grand‐canonical molecular dynamics simulation, the room‐temperature isotherm is obtained for the sorption of water into gecko keratin, to the authors’ knowledge, the first such relation for any beta‐keratin. In this work, it relates the equilibrium water content of the keratin to the ambient relative humidity.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2023 |
| Autor(en): | Materzok, Tobias ; Eslami, Hossein ; Gorb, Stanislav N. ; Müller‐Plathe, Florian |
| Art des Eintrags: | Bibliographie |
| Titel: | Understanding Humidity‐Enhanced Adhesion of Geckos: Deep Neural Network‐Assisted Multi‐Scale Molecular Modeling |
| Sprache: | Englisch |
| Publikationsjahr: | 2023 |
| Ort: | Darmstadt |
| Verlag: | Wiley-VCH |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | Small : nano micro |
| Jahrgang/Volume einer Zeitschrift: | 19 |
| (Heft-)Nummer: | 22 |
| Kollation: | 9 Seiten |
| DOI: | 10.1002/smll.202206085 |
| Zugehörige Links: | |
| Kurzbeschreibung (Abstract): | A higher relative humidity leads to an increased sticking power of gecko feet to surfaces. The molecular mechanism responsible for this increase, however, is not clear. Capillary forces, water mediating keratin‐surface contacts and water‐induced softening of the keratin are proposed as candidates. In previous work, strong evidence for water mediation is found but indirect effects via increased flexibility are not completely ruled out. This article studies the latter hypothesis by a bottom‐up coarse‐grained mesoscale model of an entire gecko spatula designed without explicit water particles, so that capillary action and water‐mediation are excluded. The elasticity of this model is adjusted with a deep neural network to atomistic elastic constants, including water at different concentrations. Our results show clearly that on nanoscopic flat surfaces, the softening of keratin by water uptake cannot nearly account for the experimentally observed increase in gecko sticking power. Here, the dominant mechanism is the mediation of keratin‐surface contacts by intervening water molecules. This mechanism remains important on nanostructured surfaces. Here, however, a water‐induced increase of the keratin flexibility may enable the spatula to follow surface features smaller than itself and thereby increase the number of contacts with the surface. This leads to an appreciable but not dominant contribution to the humidity‐increased adhesion. Recently, by atomistic grand‐canonical molecular dynamics simulation, the room‐temperature isotherm is obtained for the sorption of water into gecko keratin, to the authors’ knowledge, the first such relation for any beta‐keratin. In this work, it relates the equilibrium water content of the keratin to the ambient relative humidity. |
| Freie Schlagworte: | deep neural networks, gecko adhesion, humidity, molecular dynamics, multiscale molecular model, pull‐off, spatula |
| ID-Nummer: | 2206085 |
| Sachgruppe der Dewey Dezimalklassifikatin (DDC): | 500 Naturwissenschaften und Mathematik > 540 Chemie 500 Naturwissenschaften und Mathematik > 590 Tiere (Zoologie) |
| Fachbereich(e)/-gebiet(e): | 07 Fachbereich Chemie 07 Fachbereich Chemie > Theoretische Chemie (am 07.02.2024 umbenannt in Quantenchemie) |
| Hinterlegungsdatum: | 02 Aug 2024 12:54 |
| Letzte Änderung: | 02 Aug 2024 12:54 |
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Understanding Humidity‐Enhanced Adhesion of Geckos: Deep Neural Network‐Assisted Multi‐Scale Molecular Modeling. (deposited 18 Jul 2023 12:47)
- Understanding Humidity‐Enhanced Adhesion of Geckos: Deep Neural Network‐Assisted Multi‐Scale Molecular Modeling. (deposited 02 Aug 2024 12:54) [Gegenwärtig angezeigt]
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