To investigate the evolution of the mechanical properties and the underlying degradation mechanisms of asphalt mortars and mixtures, this study combines macroscopic indirect tensile (IDT) tests, nanoscale molecular dynamics (MD) simulations, and a supplementary back-propagation (BP) neural network model. Results reveal a distinct scale effect where mastic hardening is more influential in mortars while interfacial weakening governs mixture performance, a process effectively mitigated by the inclusion of a modifier. In the context of this complex damage, the comprehensive secant modulus (Sbp) is established as a more robust evaluation index than other traditional single-stage indexes. The BP neural network model details that the complex performance degradation is obscured by a competing aging effect from its virgin asphalt mastic. MD simulations reveal the nanoscopic origin of this behavior, identifying that the presence of water and ions strengthens the asphalt mastic’s interaction energies, a phenomenon driven by the formation of potent hydrogen-bond and ion-dipole networks that fundamentally restructure the mastic system. Further, the long-term immersion degradation of asphalt mastic is a synergistic process governed by a thickening water film, which disrupts adhesion and creates a corrosive environment. This environment drives a dual degradation mechanism during long-term immersion: it physically disrupts interfacial adhesion while promoting the electrostatic-driven dismantling of the asphaltenic network and resin phase. This process ultimately transforms the material’s colloidal structure into a destabilized, multi-phase entity responsible for macroscopic deterioration. The study mechanistically links the mechanical degradation of asphalt mortar and mixture under solution erosion to the nanoscopic, electrostatic-driven restructuring of their mastic’s colloidal structure.
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Li et al. (2025) studied this question.
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