Dynamics in Supramolecular Polymer Networks Formed by Associating Telechelic Chains

作者：Amin Dipesh; Likhtman Alexei E; Wang Zuowei^*

来源：Macromolecules, 2016, 49(19): 7510-7524.

DOI：10.1021/acs.macromol.6b00561

We present hybrid molecular dynamics/Monte Carlo simulations of supramolecular networks formed by unentangled telechelic chains with sticky end monomers (or stickers) of finite functionality. The reversible bonding between sticky monomers leads to the formation of sticker clusters with well-defined size distribution, which in turn work as cross-links for transient polymer networks. We study the kinetics of sticky monomer association, the topological structure, and the resulting dynamic and rheological behavior of the supramolecular systems as a function of the sticker bonding energy epsilon and the parent polymer chain length. Percolated transient networks are formed above a threshold bonding energy around 4.3k(B)T. At high bonding energies epsilon >= 10k(B)T, the majority of the stickers are fully reacted and the fraction of open stickers is less than 1%. The conventional picture of a single sticker hopping from one cluster to another is energetically unfavorable. We find the dynamic and rheological behavior of such strongly associated supramolecular networks are dominated by a partner exchange mechanism in which the stickers exchange their associated partners, and so release the imposed topological constraints, through the association and disassociation of sticker clusters. The characteristic time of the partner exchange events grows exponentially with the bonding energy and is up to 2 orders of magnitude longer than the average lifetime of the reversible bonds. As a result, three relaxation regimes can be clearly identified in the stress and chain end-to-end vector relaxation functions as well as the mean-squared displacements of the stickers, which are the initial Rouse regime, the intermediate rubbery regime, and the terminal relaxation regime. A phantom chain hopping model based on the microscopic understanding is proposed to describe the chain relaxation dynamics in the supramolecular networks, which provides numerical predictions in reasonably good agreement with our simulation results.

• 出版日期2016-10-11