4.7 Article

Structure-mechanical property correlations of model siloxane elastomers with controlled network topology

Journal

POLYMER
Volume 50, Issue 2, Pages 347-356

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.polymer.2008.10.027

Keywords

Elastomers; Polydimethylsiloxane; Rubber elasticity; Viscoelasticity

Funding

  1. Ministry of Education, Culture, Sports, Science and Technology (MEXT) of Japan [16750186, 19031014]
  2. Japan Society for the Promotion of Science [B-09]
  3. Grants-in-Aid for Scientific Research [16750186, 19031014] Funding Source: KAKEN

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We review our recent studies towards the molecular understanding of mechanical properties-structure relationships of elastomers using model polydimethylsiloxane (PDMS) networks with controlled topology. The model elastomers with controlled lengths of the network strands and known amounts of cross-links and dangling chains are obtained by end-linking the functionally terminated precursor PDMS with known molecular weights using multi-functional cross-linkers. Several modern entanglement theories of rubber elasticity are assessed in an unambiguous manner on the basis of the nonlinear stress-strain behavior of the model elastomers under general biaxial strains. The roles of cross-links and entanglements in the large-scale structure of the swollen state are revealed from small angle X-ray scattering spectra. A remarkably stretchable elastomer with the ultimate strain over 3000% is obtained by optimizing the network topology for high extensibility, i.e., by reducing the amounts of trapped entanglements and the end-to-end distance of the network strands. The model elastomers with unattached chains exhibit a pronounced viscoelastic relaxation originating from the relaxation by reptative motion of the guest chains. The relaxation spectra provide a definite basis to discuss the dynamics of guest linear chains trapped in fixed polymer networks. The temperature- and frequency-insensitive damping elastomers are made by introducing intentionally many dangling chains into the networks. (C) 2008 Elsevier Ltd. All rights reserved.

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