In the past decades, considerable efforts have been made for the development of energy-efficient and eco-friendly convective heat transfer and lubricating agents because of growing energy demands, precision manufacturing, miniaturization and sustainability issues. In this study, different concentrations of graphene–sunflower oil nanofluid were prepared and their thermal conductivity was experimentally investigated and compared with the correlations of similar researches found in the literature. The morphology of graphene nanoplatelets was appraised by X-ray diffractometer (XRD) and scanning electron microscope (SEM). The results show that the thermal conductivity of nanofluid was enhanced with temperature and nanoparticles weight fraction. The nanoconvection at high temperatures, less meandering mobility of graphene nanoplatelets and high kinematic viscosity of graphene nanofluids at low temperatures were identified as the key factors for the thermal conductivity enhancement. Further, the concentration and temperature-dependent theoretical correlation were proposed for estimating the thermal conductivity of graphene nanofluids using backpropagation algorithm of artificial neural network (ANN) with the minimum margin of deviation.
Fused deposition modelling (FDM) of composites of graphene nanoplatelets and polymers for high thermal conductivity: a mini-review
