English

Thermal conductivity of commodity polymers under high pressures

Soft Condensed Matter 2026-01-12 v1 Materials Science

Abstract

Understanding the thermal conductivity of polymers under high-pressure conditions is essential for a range of applications, from aerospace and deep-sea engineering to common lubricants. However, the complex relationship between pressure, PP, the thermal transport coefficient, κ\kappa, and polymer architecture poses substantial challenges to both experimental and theoretical investigations. In this work, we study the pressur-dependent thermal transport properties of a widely used commodity polymer -- poly(methyl methacrylate) (PMMA) -- using a combination of all-atom molecular dynamics simulations and semi-analytical approaches. While we report both classical and quantum-corrected estimates of κ\kappa, the latter approach reveals that as the pressure increases from 1 atm to 10 GPa, κ\kappa rises by up to a factor of four -- from 0.21 W m1^{-1} K1^{-1} to 0.80 W m1^{-1} K1^{-1}. To better understand the mechanisms behind this increase, we disentangle the contributions from bonded and nonbonded monomer interactions. Our analysis shows that nonbonded energy-transfer rates increase by a factor of six over the pressure range, while bonded interactions show a more modest increase -- about a factor of three. This observation further consolidates the fact that the nonbonded interactions play the dominant role in dictating the microscopic heat flow in polymers. These individual energy-transfer rates are also incorporated into a simplified heat diffusion model to predict κ\kappa. The results obtained from different approaches show internal consistency and align well with available experimental data. Additionally, some data for polylactic acid (PLA) are presented.

Keywords

Cite

@article{arxiv.2511.06561,
  title  = {Thermal conductivity of commodity polymers under high pressures},
  author = {Otavio Higino Moura de Alencar and James Mu and Marcus Müller and Debashish Mukherji},
  journal= {arXiv preprint arXiv:2511.06561},
  year   = {2026}
}
R2 v1 2026-07-01T07:28:40.265Z