Asphalt-aggregate interface properties are considered to play a crucial role in asphalt mixture. To better understand the detailed binding mechanism, the present study analyzed the adhesion and diffusion of asphalt binder on mineral surfaces at a nanoscale based on molecular dynamics simulation. A 12-component AAA-1 asphalt model and five oxide models were generated to represent asphalt binder and mineral aggregates, respectively. The effectiveness of these models was validated by comparing the physical properties of the model with the values reported in the literature. The binding energy and diffusion coefficient obtained were examined to characterize the adhesion and diffusion of asphalt on different mineral surfaces. The results indicated that van der Waals energy played the main role in forming the strong physisorption of asphalt on the mineral surface. Among all four fractions of asphalt, asphaltene made a great contribution to the adhesion of asphalt on the mineral surface. It was also found that the work of adhesion between asphalt and five oxides ranked MgO > CaO > Al₂O₃ > Fe₂O₃ > SiO₂. The content of MgO and CaO in mineral aggregates can be further adopted as an index to evaluate and classify mineral aggregates during asphalt mixture design. Meanwhile, asphalt mobility does not entirely rely on the molecular mass but also depends strongly on the medium it adsorbed into and interaction energy. This work provides a fundamental understanding of the adhesion and diffusion of asphalt binder on the mineral aggregate surface at the atomistic scale.

With a rapid development of intelligent transportation systems (ITSs), traffic monitoring has gained increasing attention. Here, we present a new kind of waterbomb-origami-inspired triboelectric nanogenerator (WO-TENG) as a traffic monitoring system to integrate smart pavement with lightweight, cost-effective, excellent deformability, flexibility, and self-rebounding properties. The electrical performance is significantly improved by more than 67% compared with current origami-based TENG, and multi tribo-pairs have great synchronicity. The fully-packaged self-driven WO-TENG is further developed to integrate smart pavement, which can successfully decouple the influence of vehicle speed and weight on the sensing accuracy. This phenomenon demonstrates the feasibility and stability of the WO-TENG for traffic monitoring. Independently of the voltage amplitude and time interval electrical wave, vehicle speed, number of vehicles, and types of vehicles can be further evaluated accurately. This work can not only address the challenge of traditional traffic monitoring system, but also promote the development of TENG based self-powered sensors in ITSs.