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Fast-curing epoxy polymers with silica nanoparticles: properties and rheo-kinetic modelling
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  • 作者:A. Keller ; K. Masania ; A. C. Taylor ; C. Dransfeld
  • 刊名:Journal of Materials Science
  • 出版年:2016
  • 出版时间:January 2016
  • 年:2016
  • 卷:51
  • 期:1
  • 页码:236-251
  • 全文大小:1,454 KB
  • 刊物类别:Chemistry and Materials Science
  • 刊物主题:Chemistry
    Materials Science
    Characterization and Evaluation Materials
    Polymer Sciences
    Continuum Mechanics and Mechanics of Materials
    Crystallography
    Mechanics
  • 出版者:Springer Netherlands
  • ISSN:1573-4803
文摘
Fast-curing epoxy polymers allow thermoset parts to be manufactured in minutes, but the curing reaction is highly exothermic with heat flows up to 20 times higher than conventional epoxies. The low thermal conductivity of the polymer causes the mechanical and kinetic properties of parts to vary through their thickness. In the present work, silica nanoparticles were used to reduce the exotherm, and hence improve the consistency of the parts. The mechanical and kinetic properties were measured as a function of part thickness. The exothermic heat of reaction was significantly reduced with the addition of silica nanoparticles, which were well dispersed in the epoxy. The silica nanoparticles increased the Young’s modulus linearly from 3.6 to 4.6 GPa with 20 wt% of silica, but the fracture energy was found to increase less than for many slow-curing epoxy resins, with values of 176–211 J m−2 being measured. Although there was no additional toughening, shear band yielding was observed. Further, the addition of silica nanoparticles increased the molecular weight between crosslinks, indicating the relevance of detailed cure kinetics when studying fast-curing epoxy resins. A model was developed to describe the increase in viscosity and degree of cure of the unmodified and the silica-modified epoxies. A heat transfer equation was used to predict the temperature and resulting properties through the thickness of a plate, as well as the effect of the addition of silica nanoparticles. The predictions were compared to the experimental data, and the agreement was found to be very good.

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