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Experimental characterisation and modelling of the strain rate dependent mechanical response of a filled thermo-reversible supramolecular polyurethane

Chen, H., Hart, L. R., Hayes, W. ORCID: https://orcid.org/0000-0003-0047-2991 and Siviour, C. R. (2022) Experimental characterisation and modelling of the strain rate dependent mechanical response of a filled thermo-reversible supramolecular polyurethane. International Journal of Impact Engineering, 166. 104239. ISSN 0734-743X

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To link to this item DOI: 10.1016/j.ijimpeng.2022.104239

Abstract/Summary

Composites consisting of a polymer binder filled with various particles are widely used in industrial applications, and key to their engineering design is the ability to produce mechanical models of these materials. One limitation of many composites is the use of cross-linked elastomers as matrix materials, which reduces re-usability and recyclability. In this research, a recently developed reusable and low temperature processable supramolecular polyurethane was mixed with sugar particles to produce a model composite material with different particle sizes or volume fractions, which were subsequently characterised and modelled. Large strain mechanical properties of the material were analysed in compression at strain rates up to approximately 1800 s-1, supported by measurements of the small strain viscoelastic response at different temperatures and frequencies. A model was developed that combined the known viscoelastic response of the supramolecular polyurethane with filler reinforcement and strain activated damage equations calibrated against quasi-static experiments. The model provided a good prediction of the high strain rate behaviour, for which the effect of adiabatic heating in the sample was also considered. The model parameters were related back to the filler particle size and volume fraction. Finally, a preliminary study of geometry and strength recovery was performed.

Item Type:Article
Refereed:Yes
Divisions:Interdisciplinary centres and themes > Chemical Analysis Facility (CAF)
Life Sciences > School of Chemistry, Food and Pharmacy > Department of Chemistry
ID Code:104608
Publisher:Elsevier

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