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An integrated XFEM modeling with experimental measurements for optimizing thermal conductivity in carbon nanotube reinforced polyethylene

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The present paper investigates the thermal properties of carbon nanotube reinforced polyethylene and specifically its potential as highly conductive material. To this end, an integrated approach is proposed combining both… Click to show full abstract

The present paper investigates the thermal properties of carbon nanotube reinforced polyethylene and specifically its potential as highly conductive material. To this end, an integrated approach is proposed combining both numerical and experimental procedures. First, in order to study conductive heat transfer in two-phase materials with imperfect interfaces, a detailed numerical model is developed based on the extended finite element method, where material interfaces are modeled using the level set method. The thermal conductance at the interface of the carbon nanotubes and the polymer matrix is considered to be an unknown model parameter, the value of which is obtained by utilizing a series of experimental measurements of the composite material’s effective conductivity. The interfacial thermal conductance parameter value is inferred by calibrating the numerically predicted effective conductivity to the series of the corresponding experimental measurements. Once this parameter is estimated, the data-informed model is subsequently employed to provide reliable predictions of the effective conductivity of the composite for various weight fractions and configurations of carbon nanotubes in the parent material. Furthermore, microstructural morphologies that provide upper limits on the effective conductivity of the composite are identified via sensitivity analysis, demonstrating its potential as a highly conductive material.

Keywords: reinforced polyethylene; effective conductivity; experimental measurements; carbon nanotube; nanotube reinforced; conductivity

Journal Title: Modelling and Simulation in Materials Science and Engineering
Year Published: 2022

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