Negatively thermodynamic toughening in double network hydrogel towards cooling-triggered multi-shape memory effect

Lu, Haibao, Li, Zhenghong, Wang, Xiaodong, Xing, Ziyu and Fu, Richard (2021) Negatively thermodynamic toughening in double network hydrogel towards cooling-triggered multi-shape memory effect. Smart Materials and Structures, 30 (10). p. 105011. ISSN 0964-1726

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Official URL: https://doi.org/10.1088/1361-665x/ac1dbc

Abstract

This paper explores fundamental mechanisms of negatively thermodynamic toughening during microphase separations of double network (DN) hydrogels, which have dynamically coordinating components with adjustable swelling behavior and designable multi-shape memory effect (multi-SME). Based on the Flory-Huggins theory and Fick’s second law, a thermodynamic model is formulated to study the diffusive dynamics, cooling-triggered multi-SME and mechanical toughness of the DN hydrogels. The negatively thermodynamic toughening effect of the DN hydrogels is strongly dependent on their water concentration, hydrophobic transition, and microphase separation. Finally, effectiveness of this new model is demonstrated by applying it to predict dual-SME, quadruple-SME and thermodynamic shape memory behaviors of DN hydrogels. This study provides a methodology for the design of shape memory DN hydrogels with tunable, giant and programmable cooling-triggered SME.

Item Type: Article
Additional Information: Funding information: This work was financially supported by the National Natural Science Foundation of China (NSFC) under Grant No. 11725208 and International Exchange Grant (IEC/NSFC/201078) through Royal Society UK and NFSC.
Uncontrolled Keywords: shape memory effect, hydrogel, double network, thermodynamics
Subjects: F200 Materials Science
F300 Physics
Department: Faculties > Engineering and Environment > Mathematics, Physics and Electrical Engineering
Depositing User: Rachel Branson
Date Deposited: 12 Jul 2021 14:59
Last Modified: 30 Sep 2021 16:30
URI: http://nrl.northumbria.ac.uk/id/eprint/46656

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