AUTHOR=Wang Xiaolin , Cao Shenyang , Wu Xu , Mu Qianqian 

TITLE=Investigating adhesion mechanisms in warm-mix recycled asphalt: a multiscale atomic force microscopy and molecular dynamics approach

JOURNAL=Frontiers in Built Environment

VOLUME=Volume 11 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/built-environment/articles/10.3389/fbuil.2025.1643779

DOI=10.3389/fbuil.2025.1643779

ISSN=2297-3362

ABSTRACT=The adhesion properties between warm-mix recycled asphalt and aggregates are a key bottleneck limiting the application of warm-mix recycled asphalt. To investigate the effects of aging, warm mix agent, and rejuvenator on the adhesion properties of SBS-modified asphalt and aggregates, this study used atomic force microscopy (AFM) to examine the surface microstructure of asphalt and aggregates. The classical Johnson-Kendall-Roberts and Derjaguin-Muller-Toporov mechanical models were chosen to characterize the micromechanics of asphalt with aggregates, and the influence of aging effects, rejuvenator, and warm mixe agents on the adhesion behavior at the asphalt-aggregate interface was explored using the Fowkes surface energy theory. Molecular dynamics (MD) methods were used to investigate the interaction energy between asphalt and aggregates, and the adhesion work between asphalt and aggregates at the molecular level was calculated. A one-dimensional linear equation between AFM and MD is proposed, and a cross-scale relationship between AFM and MD is established. The research findings indicate that the aging process increases the roughness and adhesion of the asphalt surface through the formation of polar groups, while rejuvenators and warm mix agents counteract these effects through component supplementation and crystallization. The adhesion properties of asphalt with limestone are much higher than the adhesion properties of asphalt with granite, which is the fruit of the combined effect of van der Waals and electrostatic forces. AFM and MD have a good univariate linear functional relationship, the decidability coefficient R2 > 0.9. These findings provide foundational insights for optimizing asphalt-aggregate combinations in pavement engineering.