4.4 Article

A predictive model towards understanding the effect of reinforcement agglomeration on the stiffness of nanocomposites

期刊

JOURNAL OF COMPOSITE MATERIALS
卷 56, 期 10, 页码 1591-1604

出版社

SAGE PUBLICATIONS LTD
DOI: 10.1177/00219983221076639

关键词

Polymer nanocomposites; elastic behavior; modeling; probabilistic methods; transmission electron microscopy

资金

  1. Alberta Innovates and Alberta-Ontario Innovation Program through Alberta Innovates, FPInnovations [SFR02735]
  2. Natural Science and Engineering Research Council of Canada (NSERC) Collaborative Research and Development Grants [CRDPJ 500602-16]
  3. NSERC Discovery Grants of Professors Ayranci, Kim, and McDermott

向作者/读者索取更多资源

A novel continuum-based model with a statistical approach was developed in this study to explore the effects of agglomerates on the mechanical properties of nanocomposite technologies. The model demonstrated good agreement with experimental data and can be applied to various types of polymeric nanocomposite systems.
Nanocomposite technologies can be significantly enhanced through a careful exploration of the effects of agglomerates on mechanical properties. Existing models are either overly simplified (e.g., neglect agglomeration effects) or often require a significant amount of computational resources. In this study, a novel continuum-based model with a statistical approach was developed. The model is based on a modified three-phase Mori-Tanaka model, which accounts for the filler, agglomerate, and matrix regions. Fillers are randomly dispersed in a defined space to predict agglomeration tendency. The proposed model demonstrates good agreement with the experimentally measured elastic moduli of spin-coated cellulose nanocrystal reinforced polyamide-6 films. The techniques and methodologies presented in the study are sufficiently general in that they can be extended to the analyses of various types of polymeric nanocomposite systems.

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