Thermal conductivity modeling beyond the dilute limit using a body-centered cubic framework for densely packed...

Area of Science:

• Materials Science
• Polymer Composites
• Thermal Transport

Background:

• Existing thermal conductivity models for polymer composites are limited to low filler concentrations (≤ 40 vol%).
• These models fail to account for strong filler interactions and reorganized heat transport in densely packed systems.
• Heat transport in dense composites is governed by thermal resistance principles and preferred pathways.

Purpose of the Study:

• To develop a mechanistic thermal conductivity model for polymer composites that accurately captures densely packed filler systems.
• To provide a more precise description of heat flow by considering reduced interparticle distances and enhanced filler interactions.
• To offer a physical interpretation of the thermal percolation transition in composites.

Main Methods:

• Introduction of a mechanistic thermal conductivity model based on a simplified body-centered cubic framework.
• The model accounts for filler interactions and heat flow along least-resistance pathways.
• Validation against diverse cross-material datasets across a wide range of filler concentrations (0-68 vol%).

Main Results:

• The model accurately predicts thermal conductivity across nearly the entire practical concentration range (0-68 vol%).
• It effectively captures the impact of reduced interparticle distances and enhanced filler interactions in dense composites.
• The model provides insights into the mechanism and onset conditions of the thermal percolation transition.

Conclusions:

• The developed model offers high-precision predictions for thermal conductivity in polymer composites, particularly in densely filled systems.
• It provides a physical interpretation of the thermal percolation transition, aiding in material design.
• The computationally efficient and modular design reduces the need for extensive experimental testing, facilitating composite optimization.