Literature DB >> 24347684

Self-Healing of Unentangled Polymer Networks with Reversible Bonds.

Evgeny B Stukalin1, Li-Heng Cai2, N Arun Kumar1, Ludwik Leibler3, Michael Rubinstein2.   

Abstract

Self-healing polymeric materials are systems that after damage can revert to their original state with full or partial recovery of mechanical strength. Using scaling theory we study a simple model of autonomic self-healing of unentangled polymer networks. In this model one of the two end monomers of each polymer chain is fixed in space mimicking dangling chains attachment to a polymer network, while the sticky monomer at the other end of each chain can form pairwise reversible bond with the sticky end of another chain. We study the reaction kinetics of reversible bonds in this simple model and analyze the different stages in the self-repair process. The formation of bridges and the recovery of the material strength across the fractured interface during the healing period occur appreciably faster after shorter waiting time, during which the fractured surfaces are kept apart. We observe the slowest formation of bridges for self-adhesion after bringing into contact two bare surfaces with equilibrium (very low) density of open stickers in comparison with self-healing. The primary role of anomalous diffusion in material self-repair for short waiting times is established, while at long waiting times the recovery of bonds across fractured interface is due to hopping diffusion of stickers between different bonded partners. Acceleration in bridge formation for self-healing compared to self-adhesion is due to excess non-equilibrium concentration of open stickers. Full recovery of reversible bonds across fractured interface (formation of bridges) occurs after appreciably longer time than the equilibration time of the concentration of reversible bonds in the bulk.

Entities:  

Keywords:  Self-healing; polymer networks; reversible; scaling theory

Year:  2013        PMID: 24347684      PMCID: PMC3857756          DOI: 10.1021/ma401111n

Source DB:  PubMed          Journal:  Macromolecules        ISSN: 0024-9297            Impact factor:   5.985


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