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

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Abstract

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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Demir, E. C., Benkaddour, A., Aldrich, D. R., McDermott, M. T., Kim, C. I., & Ayranci, C. (2022). A predictive model towards understanding the effect of reinforcement agglomeration on the stiffness of nanocomposites. Journal of Composite Materials, 56(10), 1591–1604. https://doi.org/10.1177/00219983221076639

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