Modeling the Thermal Conductivity Inhomogeneities of Injection-Molded Particle-Filled Composites, Caused by...

Area of Science:

• Materials Science
• Polymer Engineering
• Manufacturing Processes

Background:

• Developing materials with high thermal conductivity, electrical insulation, and easy processability is crucial for many applications.
• Thermally conductive composites offer a viable alternative to metals, but their performance is affected by particle segregation.
• Existing models often overlook the impact of segregation on the local thermal conductivity of composites.

Purpose of the Study:

• To investigate and model the phenomenon of segregation during injection molding of polymer composites.
• To understand how segregation influences the distribution of thermally conductive fillers and local thermal conductivity.
• To develop an accurate, segregation-dependent model for predicting the thermal conductivity of polymer composites.

Main Methods:

• Injection molding of polypropylene samples filled with glass beads of varying sizes.
• Analysis of filler content distribution along the flow path within the molded samples.
• Development of a mathematical model to describe filler distribution and a subsequent segregation-dependent thermal conductivity model.

Main Results:

• Segregation significantly impacts filler distribution and local thermal conductivity in injection-molded polymer composites.
• The developed mathematical model accurately describes filler distribution as a function of the flow path.
• The new segregation-dependent model predicts local thermal conductivity with high accuracy based on filler content.

Conclusions:

• Segregation is a critical factor in determining the thermal conductivity of polymer composites processed via injection molding.
• Accurate modeling of segregation enables precise prediction of local thermal conductivity.
• The developed model provides a valuable tool for designing high-performance thermally conductive polymer composites.