Computational prediction of electrical and thermal properties of graphene and BaTiO3 reinforced epoxy nanocomposites

Graphene based materials e.g., graphene oxide (GO), reduced (RGO) and nano platelets (GNP) as well Barium titanate (BaTiO3) are emerging reinforcing agents which upon mixing with epoxy provides composite superior mechanical, electrical thermal properties shielding against electromagnetic (EM) radiations. Inclusion of the aforementioned has shown to improve performance, however, extent improvement remained uncertain. In this study, a computational modelling approach was adopted using COMSOL Multiphysics software in conjunction Bayesian statistical analysis investigate effects including various filler e.g. GO, RGO, GNP BaTiO3 influencing direct current (DC) conductivity (?), dielectric constant (?) on resulting polymer matrix composites. The simulation composites were performed for different volume percentage by varying geometry material. It observed that content GNPs thickness nanoplatelets can alter DC conductivity, constant, matrix. lower found offer larger value diffusivity than rest nanocomposites, while, RGO showed better neat epoxy, nanocomposites. Similarly, nanoparticles diameter modified several order magnitude epoxy. way, higher particles properties, value, diffusivity. Moreover, research guidance further examination selection enhancement