Use of MD Simulation for Investigating Diffusion Behaviors between Virgin Asphalt and Recycled Asphalt Mastic

Abstract

The study aims at investigating diffusion behaviors between virgin asphalt and recycled asphalt mastic (RAM) at an atomistic scale. Firstly, a mutual diffusion model of virgin asphalt–RAM considering the actual mass ratio of filler to asphalt binder (F/A) condition was developed by molecular dynamic (MD)simulation. Secondly, the indexes of relative concentration (RC), radial distribution function (RDF) and mean square displacement (MSD) were used to analyze the molecular arrangement characteristics of polar components in the diffusion processes at different temperatures. Then, the blending efficiency of virgin asphalt–RAM was evaluated by Fick’s second law and the binding energy. The results indicate that the reliability of the RAM model was validated by thermodynamics properties. The results of RC and RDF show that the diffusion direction of virgin asphalt–RAM is not changed by the presence of mineral fillers. However, it will inhibit the occurrence of diffusion behaviors, and the aggregation of molecules in the blending zone increases due to the adsorption of mineral fillers, which would become a barrier to molecular diffusion. The development of MSD indicates that the diffusion coefficients of molecules in both virgin–aged asphalt and virgin asphalt–RAM are on the rise with the increase in temperature. Compared with the virgin–aged asphalt, the molecular migration speed in virgin asphalt–RAM is relatively slow. According to Fick’s second law and the binding energy, diffusion behaviors are dominated by the nonpolar components. The existence of mineral fillers has the greatest effect on the nonpolar components in diffusion. It is suggested that rejuvenator containing more aromatic components should be added or the temperature controlled within 433.15–443.15 K to promote blending efficiency. The research results contribute to a deeper understanding about diffusion behaviors of virgin asphalt–RAM, serving as a benchmark for further study of rejuvenation using computational experiments.