Excessive usage of non-renewable natural resources and massive construction wastes put pressure on the environment. Steel slags, the main waste material from the metal industry, are normally added in asphalt concrete to replace traditional aggregate. In addition, as a typical microwave absorber, steel slag has the potential to transfer microwave energy into heat, thus increasing the limited self-healing ability of asphalt mixture. This paper aims to investigate the microwave absorption potentials of steel slag and the effect of its addition on road performance. The magnetic parameters obtained from a microwave vector network analyzer were used to estimate the potential use of steel slag as microwave absorber to heal cracks. Meanwhile, the initial self-healing temperature was further discussed according to the frequency sweeping results. The obvious porous structure of steel slag observed using scanning electron microscopy (SEM) had important impacts on the road performance of asphalt mixtures. Steel slag presented a worse effect on low-temperature crack resistance and water stability, while high-temperature stability can be remarkably enhanced when the substitution of steel slag was 60% by volume with the particle size of 4.75–9.5 mm. Overall, the sustainability of asphalt mixtures incorporating steel slag can be promoted due to its excellent mechanical and microwave absorption properties.

To investigate the effect of styrene-butadiene-styrene (SBS) modifier content on the viscoelastic behavior of SBS-modified asphalt (SBSMA) at different temperatures and phase structures, the star SBS modifier was chosen to fabricate seven types of SBSMA with different contents. Multiple stress creep recovery (MSCR), linear amplitude sweep (LAS), and low-temperature frequency sweep tests were adopted to study the influence of SBS modifier content on the viscoelastic performance of SBSMA at high to low temperatures. The SBSMA’s microstructure with different contents was investigated using a fluorescence microscope. The results indicated that the change in non-recoverable creep compliance and creep recovery rate was bounded by 4.5% content at high temperatures, with an apparent turning point. The changing slope of content at less than 4.5% was much higher than that of the content greater than 4.5%. At medium temperatures, the fatigue life of SBSMA increased exponentially with the rising modifier content. The rate of increase in fatigue life was the largest as the content increased from 4.5% to 6.0%. At low temperatures, the low-temperature viscoelastic property index G (60 s) of SBSMA decreased logarithmically as the modifier content increased. In terms of the microscopic phase structure, the SBS modifier gradually changed from the dispersed to the continuous phase state with the increasing SBS modifier content.

In recent years, smart aggregates have emerged as a promising tool for monitoring the movement of and changes in particles inside asphalt mixtures. However, there remain significant differences between smart aggregates and real rock aggregates, particularly the lack of an asphalt coating on the surface of smart aggregates. Currently, the research on the impact of smart aggregates themselves on the structure and properties of asphalt mixtures is lacking. Therefore, this study focuses on the influence of smart aggregate size on the mesostructure and mechanical properties of asphalt mixtures. Firstly, based on laboratory tests and the discrete element method (DEM), discrete element models of asphalt mixture specimens containing smart aggregates of various sizes were constructed, followed by simulated compaction tests. The effects of smart aggregate size on the mesostructure of asphalt mixture voids were then analyzed. Lastly, in this study, the changes in the dynamic modulus of asphalt mixtures were explored with increasing smart aggregate size and the underlying mechanisms. The results indicate that as the size of smart aggregates increases, the average void ratio of the asphalt mixture specimens decreases, but the heterogeneity of the void distribution increases. Additionally, with the increase in smart aggregate size, the dynamic modulus of the mixture specimens decreases. Further strain analysis of the specimens suggests that the increase in cross-sectional deformation is the primary cause of the reduction in modulus.