| Issue |
EPJ Web Conf.
Volume 372, 2026
Advanced Power Systems (APS 2026)
|
|
|---|---|---|
| Article Number | 04003 | |
| Number of page(s) | 7 | |
| Section | Power Electronics in Energy Applications | |
| DOI | https://doi.org/10.1051/epjconf/202637204003 | |
| Published online | 11 June 2026 | |
https://doi.org/10.1051/epjconf/202637204003
Predicting thermal conductivity in filled polyurethane composites
Department of Physics, Faculty of Electrical Engineering and Information Technology University of Zilina, Zilina, Slovakia
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Published online: 11 June 2026
Abstract
Predicting the effective thermal conductivity of polymer composites is crucial for optimizing materials for demanding thermal management applications. This study focuses on Polyurethane (PU) composites (specifically VUKOL Magna Blue) with Boron Nitride (BN) admixtures, testing concentrations of pure polymer, 10 wt%, and 20 wt% BN. Experimental measurements demonstrated a significant increase in effective thermal conductivity, rising from 0.2 Wm−1 K−1 for pure PU to approximately 0.68 Wm−1 K−1 at 20 wt% BN. These measured results were subsequently compared with predictions derived from established theoretical models. Particular attention was paid to the influence of Thermal Boundary Resistance (TBR), which was incorporated into a modified version of the Maxwell-Eucken model to improve the prediction accuracy at the filler-matrix interface. For validation, Finite Element Method (FEM) simulations of heat distribution and transfer within the composites were also performed. The comparison between the experimental data, theoretical calculations, and FEM simulation results revealed varying degrees of agreement and highlighted the limits and strengths of each predictive method. The findings emphasize that for accurate predictions of the thermal behavior of PU composites, it is essential not only to carefully select the appropriate theoretical model but also to responsibly consider and quantify factors such as TBR and the specific characteristics of the filler.
© The Authors, published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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