Effect of graphene and carbon-nitride nanofillers on the thermal transport properties of polymer nanocomposites: A combined molecular dynamics and finite element study

Abstract

Low thermal conductivity of polymers, which is one of the considerable drawbacks of commonly used composite structures, has been the focus of many researchers aiming to achieve high-performance polymer-based nanocomposites through the inclusion of highly thermally conductive fillers inside the polymer matrices. Thus, in the present study, a multiscale scheme using non-equilibrium molecular dynamics (NEMD) and finite element (FE) method is developed to explore the impact of different nano-sized fillers (carbon-nitride and graphene) on the effective thermal conductivity of polyethylene-based nanocomposites. We show that the thermal conductivity of amorphous polyethylene at room temperature using the reactive bond order (REBO) interatomic potential is nearly 0.36 0.05W/mK. Also, the atomistic results predict that, compared to the C3N and graphene nanosheets, the C2N nanofilm presents a much stronger interfacial thermal conductance (ITC) with polyethylene. Furthermore, the results indicate that the effective thermal conductivity values of C2N-polyethylene, C3N-polyethylene, and graphene-polyethylene nanocomposite, at constant volume fractions of 1%, are about 0.47, 0.56, and 0.74 W/mK, respectively. In other words, the results of our models reveal that the thermal conductivity of fillers is the dominant factor that defines the effective thermal conductivity of nanocomposites.

24 pages, 10 figures

References in corpus (5)

• Graphene or h-BN paraffin composite structures for the thermal management of Li-ion batteries: A multiscale investigation
• Nanoporous graphene: a 2D semiconductor with anisotropic mechanical, optical and thermal conduction properties
• Correlations between mechanical, structural, and dynamical properties of polymer nanocomposites
• Thermal transport in silicene nanotubes: Effects of length, grain boundary and strain
• Thermal transport across grain boundaries in polycrystalline silicene: a multiscale modeling

Cited by in corpus (4)

• Machine learning assisted multiscale modeling of composite phase change materials for Li-ion batteries thermal management
• Ultrahigh thermal conductivity and strength in direct-gap semiconducting graphene-like BC6N: A first-principles and classical investigation
• Thermal transport in two-dimensional C3N/C2N superlattices: A molecular dynamics approach
• Enhanced interfacial thermal conductance in functionalized Boron Nitride/Polylactic acid nanocomposite: A molecular dynamics study