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Title: Coupled bond dynamics alters relaxation in polymers with multiple intrinsic dissociation rates
Dynamic networks containing multiple bond types within a continuous network grant engineers another design parameter – relative bond fraction – by which to tune storage and dissipation of mechanical energy. However, the mechanisms governing emergent properties are difficult to deduce experimentally. Therefore, we here employ a network model with prescribed fractions of dynamic and stable bonds to predict relaxation characteristics of hybrid networks. We find that during stress relaxation, predominantly dynamic networks can exhibit long-term moduli through conformationally inhibited relaxation of stable bonds due to exclusion interactions with neighboring chains. Meanwhile, predominantly stable networks exhibit minor relaxation through non-affine reconfiguration of dynamic bonds. Given this, we introduce a single fitting parameter, ξ , to Transient Network Theory via a coupled rule of mixture, that characterizes the extent of stable bond relaxation. Treating ξ as a fitting parameter, the coupled rule of mixture's predicted stress response not only agrees with the network model's, but also unveils likely micromechanical traits of gels hosting multiple bond dissociation timescales.  more » « less
Award ID(s):
2029699
NSF-PAR ID:
10407377
Author(s) / Creator(s):
;
Date Published:
Journal Name:
Soft Matter
Volume:
19
Issue:
15
ISSN:
1744-683X
Page Range / eLocation ID:
2716 to 2725
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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