Biological adhesion, in particular the mechanisms by which animals and plants ‘stick’ to surfaces, has been widely studied in recent years, and some of the structural principles have been successfully applied to bioinspired adhesives. However, modelling of adhesion, such as in single or multiple peeling theories, has in most cases been limited to ideal cases, and due consideration of the role of substrate geometry and mechanical properties has been limited. In this paper, we propose a numerical model to evaluate these effects, including substrate roughness, patterning, curvature, and deformability. The approach is validated by comparing its predictions with classical thin film peeling theoretical results, and is then used to predict the effects of substrate properties. These results can provide deeper insight into experiments, and the developed model can be a useful tool to design and optimize artificial adhesives with tailor-made characteristics.
In-Situ Hybridization of an Epoxy Resin using Polyurethane and MXene Nanoplatelets for Thermally Stable Nanocomposites with Improved Strength and Toughness / Hu, Yi; Chen, Junzhen; Yang, Guoyu; Li, Yujun; Dong, Ming; Li, Qi; Yuan, Hongna; Zhang, Han; Pugno, Nicola M.; Jiang, Jianjun; Papageorgiou, Dimitrios G.. - In: POLYMER. - ISSN 0032-3861. - 2024, 302:026004(2024), pp. 1-11. [10.1016/j.polymer.2024.127065]
In-Situ Hybridization of an Epoxy Resin using Polyurethane and MXene Nanoplatelets for Thermally Stable Nanocomposites with Improved Strength and Toughness
Pugno, Nicola M.;
2024-01-01
Abstract
Biological adhesion, in particular the mechanisms by which animals and plants ‘stick’ to surfaces, has been widely studied in recent years, and some of the structural principles have been successfully applied to bioinspired adhesives. However, modelling of adhesion, such as in single or multiple peeling theories, has in most cases been limited to ideal cases, and due consideration of the role of substrate geometry and mechanical properties has been limited. In this paper, we propose a numerical model to evaluate these effects, including substrate roughness, patterning, curvature, and deformability. The approach is validated by comparing its predictions with classical thin film peeling theoretical results, and is then used to predict the effects of substrate properties. These results can provide deeper insight into experiments, and the developed model can be a useful tool to design and optimize artificial adhesives with tailor-made characteristics.File | Dimensione | Formato | |
---|---|---|---|
361-BB18-peeling.pdf
accesso aperto
Tipologia:
Versione editoriale (Publisher’s layout)
Licenza:
Creative commons
Dimensione
800.57 kB
Formato
Adobe PDF
|
800.57 kB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione