Modelling the Thermal Conductivity of Nano-Porous Materials

Abstract

Nanoporous materials have fascinating properties, particularly very low thermal conductivities, owing to their nanostructured morphology [1]. Similar to many properties, the thermal conductivity of porous materials remains a function of their density. Optimizing for a desired value requires a thorough understanding of the interplay between its diverse components. While convection plays no role in nanoporous materials and radiation becomes prominent at higher temperatures, a focus has been set on solid and gaseous thermal conductivity. To this end, a mechanistic approach to model the thermal conductivity in such materials has been developed. As a first step, the porous morphology is computationally modelled [3] and considered as a resistor network [4]. The thermal conductivity is then evaluated by simulating the heat transfer across this network. In case of the solid conduction, the solid skeletal network, represented by the solid network model (SNM), forms the resistor network while in case of gaseous conduction, it is the pore connectivity represented by the pore network model (PNM). A correlation of the model parameters of the PNM with the Knudsen number has been established in order to motivate a physics-informed approach towards computationally modelling the otherwise empirically-modelled system. The results of the model approach are validated with previously developed empirical models and the thermal conductivities obtained are within the typical range for nano-porous materials. As an outlook, the model is evaluated for foam-like materials with pores in other length scales.