Quantitative Evaluation of the Dispersion of Graphene Sheets With and Without Functional Groups Using Molecular Dynamics Simulations

Abstract

Nanofluids with enhanced thermal properties are candidates for thermal management in automotive systems, with scope for improving energy efficiency. In particular, many studies have reported on dispersions of nanoparticles with long-term stability in the base fluid, with qualitative evaluations of the dispersion stability via either the naked eye or optical instruments. Additives such as surfactants can be used to enhance the dispersion of nanoparticles

however, this may diminish their intrinsic thermal properties. Here, we describe molecular dynamics simulations of nanofluids containing graphene sheets dispersed in ethylene glycol and water. We go on to suggest a quantitative evaluation method for the degree of dispersion, based on the ratio of the total number of nanoparticles to the number of clustered nanoparticles. Moreover, we investigate the effects of functional groups on the surface of graphene, which are expected to improve the dispersion without requiring additives such as surfactants due to steric hindrance and chemical affinity for the surrounding fluid. We find that, for pure graphene, the degree of dispersion decreased as the quantity of graphene sheets increased, which is attributed to an increased probability of aggregation at higher loadings

however, the presence of functional groups inhibited the graphene sheets from forming aggregates.