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Model Approach to Thermal Conductivity in Hybrid Graphene-Polymer Nanocomposites.

Andriy B NadtochiyAlla M GorbBorys M GorelovOleksiy I PolovinaOleg KorotchenkovViktor Schlosser
Published in: Molecules (Basel, Switzerland) (2023)
The thermal conductivity of epoxy nanocomposites filled with self-assembled hybrid nanoparticles composed of multilayered graphene nanoplatelets and anatase nanoparticles was described using an analytical model based on the effective medium approximation with a reasonable amount of input data. The proposed effective thickness approach allowed for the simplification of the thermal conductivity simulations in hybrid graphene@anatase TiO 2 nanosheets by including the phenomenological thermal boundary resistance. The sensitivity of the modeled thermal conductivity to the geometrical and material parameters of filling particles and the host polymer matrix, filler's mass concentration, self-assembling degree, and Kapitza thermal boundary resistances at emerging interfaces was numerically evaluated. A fair agreement of the calculated and measured room-temperature thermal conductivity was obtained.
Keyphrases
  • room temperature
  • carbon nanotubes
  • walled carbon nanotubes
  • molecular dynamics
  • artificial intelligence
  • optical coherence tomography
  • big data
  • deep learning
  • visible light