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Published October 31, 2018 | Supplemental Material + Accepted Version
Journal Article Open

Mechanisms of diffusion in associative polymer networks: evidence for chain hopping


Networks assembled by reversible association of telechelic polymers constitute a common class of soft materials. Various mechanisms of chain migration in associative networks have been proposed; yet there remains little quantitative experimental data to discriminate among them. Proposed mechanisms for chain migration include multichain aggregate diffusion as well as single-chain mechanisms such as "walking" and "hopping", wherein diffusion is achieved by either partial ("walking") or complete ("hopping") disengagement of the associated chain segments. Here, we provide evidence that hopping can dominate the effective diffusion of chains in associative networks due to a strong entropic penalty for bridge formation imposed by local network structure; chains become conformationally restricted upon association with two or more spatially separated binding sites. This restriction decreases the effective binding strength of chains with multiple associative domains, thereby increasing the probability that a chain will hop. For telechelic chains this manifests as binding asymmetry, wherein the first association is effectively stronger than the second. We derive a simple thermodynamic model that predicts the fraction of chains that are free to hop as a function of tunable molecular and network properties. A large set of self-diffusivity measurements on a series of model associative polymers finds good agreement with this model.

Additional Information

© 2018 American Chemical Society. Received: July 25, 2018; Published: October 1, 2018. We thank Andres Collazo of the Caltech Beckman Imaging Facility for expert assistance with acquisition of FRAP data. This work was supported by grant number DMR-1506483 from the Biomaterials Program of the U.S. National Science Foundation. A.K.O. acknowledges support from the National Science Foundation Graduate Research Fellowship under grant no. DGE-1144469 and an HHMI Gilliam Fellowship. B.R.S. acknowledges support from NIH predoctoral training grant 1T32GM112592 and from the Rosen Center for Bioengineering. P.B.R. and A.K.O. contributed equally to this work. The authors declare no competing financial interest.

Attached Files

Accepted Version - nihms-1792560.pdf

Supplemental Material - ja8b07908_si_001.pdf


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September 22, 2023
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