Viscoelastic properties of composite materials with random structure.

Area of Science:

• Materials Science
• Polymer Science
• Computational Modeling

Background:

• Filled polymeric composites require accurate structural models to predict properties.
• Understanding filler-filler and filler-matrix interactions is crucial for material design.

Purpose of the Study:

• Develop a mesoscale structural model for filled polymeric composites.
• Calculate and analyze the viscoelastic properties of these materials.

Main Methods:

• Utilized Voronoi polyhedra to represent filler particles and fractal concepts for coarse-grained structures.
• Employed an iterative method based on renormalization group transformations to compute viscoelastic properties.
• Investigated the effects of frequency, filler, and matrix properties across a wide concentration range.

Main Results:

• The developed model accurately predicts storage and loss moduli.
• Model calculations show good agreement with experimental results for polystyrene melt filled with glass spheres.
• Findings align with established percolation theory predictions.

Conclusions:

• The Voronoi-fractal model provides a robust framework for simulating filled polymeric composites.
• The method effectively captures the influence of constituent properties and structure on viscoelastic behavior.
• This approach offers a valuable tool for designing and optimizing composite materials.