Abstract

• Innovative application of Fenton reaction in the modification of polyacrylonitrile fibers. • Biomimetic multi-layered structure modified polyacrylonitrile fibers. • KF-PAN/SBS/RP modified asphalt had better viscoelastic performance. • KF-PAN/SBS/RP modified asphalt had better low temperature anti-cracking performance, high temperature stability and fatigue damage resistance. • KF-PAN/SBS/RP modified asphalt had better rutting resistance and high temperature adhesion performance. In this study, a surface modified polyacrylonitrile fiber (KF-PAN) with a fish-scale whisker-like biomimetic hierarchical structure was successfully prepared via in situ competition effect of Fenton reaction. The modified fibers were used as secondary modifiers to prepare fiber-reinforced styrene–butadienestyrene (SBS) block copolymers and rubber powder (RP) modified asphalt binders (KF-PAN/SBS/RP). Energy dispersive spectroscopy, scanning electron microscopy, and atomic force microscopy analyses revealed the successful construction of bionic hierarchy on the fiber surface, and confirmed rough surface of the KF-PAN fibers. The hierarchical structure of the fiber surface acted as a buffer in the asphalt and strengthened the mutual interaction of the fiber and asphalt. Dynamic rheometer shear and strip-tensile tests showed that the KF-PAN/SBS/RP modified asphalt exhibited better viscoelasticity, rutting resistance, and tensile properties than the PAN/SBS/RP modified asphalt. The linear amplitude sweep test showed that KF-PAN/SBS/RP modified asphalt had better fatigue resistance. Thermogravimetric analysis tests indicated that the surface bionic structure of KF-PAN fibers boosted thermal stability of the fibers, which in turn enhanced the thermal stability of KF-PAN/SBS/RP modified asphalt. Fluorescence microscopy analysis showed that incorporating KF-PAN fibers improved the SBS and RP microstructure inside the asphalt, forming a good mesh structure, and alleviating the stress concentration phenomenon in SBS/RP asphalt under external traffic load.

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