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Quantitative multifractal demarcation of bitumen colloidal architecture: Resolving characteristic dimensions and
Zhiyang Liu1, Shangkun Yin1, Tao Zhou2
1School of Civil Engineering and Transportation, Northeast Forestry University, Harbin 150040, People's Republic of China.
Abstract:
Colloidal architecture serves as a defining fingerprint of bitumen's chemical composition and functional performance, playing a critical role in durability enhancement and advanced material design. Current characterization approaches predominantly rely on qualitative morphological comparisons and Euclidean geometry-based statistical analyses, which inadequately capture the intricate fractal topology inherent to bitumen's irregular colloidal structures. This study addresses this gap by introducing a multifractal analysis framework for quantitative identification and hierarchical demarcation of bitumen's multiscale colloidal architecture. High-resolution morphological characterization across millimeter to nanometer scales revealed distinct colloidal features exhibiting scale-dependent susceptibility, as evidenced by systematic variations in information capacity, entropy, and correlation metrics. The generalized multifractal dimensions, analyzed as functions of moment order, revealed a bifractal structural signature. Through two-dimensional Fourier Transform decomposition, the superimposed architecture was resolved into three wavelength-specific regimes: long-wavelength surface profiles, medium-wavelength colloidal assemblies, and short-wavelength subcolloidal features. Local fractal dimension frequency distributions enabled precise identification of characteristic structures, while a critical dimensional threshold, defined as the minimum scale encapsulating ≥75 % of structural information, demonstrated a positive correlation with wavelength regimes, validating its utility for scale-dependent classification. Quantitative analysis of fractal dimensions further elucidated the enhanced heterogeneity and structural complexity induced by long-term desiccated storage and UV aging. The developed framework integrates spectral decomposition, multifractal heterogeneity analysis, colloidal feature identification, and structure-performance correlation. This methodology advances beyond conventional Euclidean descriptors by comprehensively resolving the fractal topology of bitumen's colloidal architecture, establishing a foundation for predictive modeling of bitumen performance through colloidal engineering.
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