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Harnessing entropy to enhance toughness in reversibly crosslinked polymer networks

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Abstract

Reversible crosslinking is a design paradigm for polymeric materials, wherein they are microscopically reinforced with chemical species that form transient crosslinks between the polymer chains. Besides the potential for self-healing, recent experimental work suggests that freely diffusing reversible crosslinks in polymer networks, such as gels, can enhance the toughness of the material without substantial change in elasticity. This presents the opportunity for making highly elastic materials that can be strained to a large extent before rupturing. Here, we employ Gaussian chain theory, molecular simulation, and polymer self-consistent field theory for networks to construct an equilibrium picture for how reversible crosslinks can toughen a polymer network without affecting its elasticity. Maximisation of polymer entropy drives the reversible crosslinks to bind preferentially near the permanent crosslinks in the network, leading to local molecular reinforcement without significant alteration of the network topology. In equilibrium conditions, permanent crosslinks share effectively the load with neighbouring reversible crosslinks, forming multi-functional crosslink points. The network is thereby globally toughened, while the linear elasticity is left largely unaltered. Practical guidelines are proposed to optimise this design in experiment, along with a discussion of key kinetic and timescale considerations.

Graphical abstract: Harnessing entropy to enhance toughness in reversibly crosslinked polymer networks

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Publication details

The article was received on 20 Dec 2018, accepted on 31 Jan 2019 and first published on 05 Feb 2019


Article type: Paper
DOI: 10.1039/C8SM02577K
Citation: Soft Matter, 2019, Advance Article

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    Harnessing entropy to enhance toughness in reversibly crosslinked polymer networks

    N. B. Tito, C. Creton, C. Storm and W. G. Ellenbroek, Soft Matter, 2019, Advance Article , DOI: 10.1039/C8SM02577K

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