4.7 Article

Keys to enhancing mechanical properties of silica nanoparticle composites hydrogels: The role of network structure and interfacial interactions

期刊

COMPOSITES SCIENCE AND TECHNOLOGY
卷 95, 期 -, 页码 1-7

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.compscitech.2014.02.003

关键词

Hybrid composites; Nano composites; Particle-reinforced composites; Fracture; Interface

资金

  1. Fundamental Research Funds for the Central Universities [TD2011-10]
  2. Research Fund for the Doctoral Program of Higher Education of China [20120014120006]

向作者/读者索取更多资源

Polymer nanocomposites have attracted an increasing interest by adding of trace amount of nano-scale fillers. The mechanical reinforcement of silica nanoparticle/poly(acrylamide) composites, which results in a homogeneous dispersion of small primary clusters in the matrix, is investigated based on a facile synthetic platform, and the structure-property relationship of the network structure is interpreted in this paper. The high grafting efficiency of polymer chains on silica nanoparticles surface pronouncedly confines the segmental motion of the chains, leading to a 6-time increase in toughness. The cluster network structure is observed by transmission electronic microscopy and mechanical response of the nanocomposites is studied by both small (oscillatory shear) and large (uniaxial tension) deformations as a function of silica particle volume fractions to demystify the effect of constrained region on the elastic properties. A constrained region model for nanocomposites is tentatively proposed and the result indicates that modulus enhancement of the nanocomposites is found to have good correlation with the volume of constrained region. This research reveals that the network structure-property relations relate to two main reinforcement effects, the filler network (filler-polymer matrix interaction) and filler mobility (energy dissipation), suggesting a need to reconsider the filler-polymer interaction and region of constraint polymer in forming a indirect bridge network among neighboring clusters. (C) 2014 Elsevier Ltd. All rights reserved.

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