ReviewMaterials (Basel, Switzerland)2026
Multiscale Mechanisms and a Mechanism-Oriented Evaluation Framework for Warm-Mix Asphalt.
Review in Materials (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
3 authors.
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Abstract
Warm-mix asphalt (WMA) reduces mixing and compaction temperatures through wax additives, chemical additives, and foaming techniques, but their dominant mechanisms, performance trade-offs, and evaluation priorities differ. This structured narrative review synthesizes evidence for Sasobit, Evotherm, and Advera as representative technologies across mixture, binder and mastic, interfacial and microstructural, and molecular scale. Sasobit-type wax additives improve construction-stage fluidity and high-temperature stability through viscosity-temperature regulation and wax crystallization, while low-temperature and fatigue risks require attention. Evotherm-type chemical additives enhance wetting and moisture resistance through surface-active adsorption, thin-film lubrication, and improved interfacial adhesion, with high-temperature shear resistance requiring verification. Advera-type zeolite foaming extends the compaction window through water release and microbubble formation, but residual moisture and wet-condition durability remain critical concerns. On this basis, technology-specific cross-scale evidence chains are established, and a mechanism-oriented evaluation framework is proposed, linking engineering scenarios, dominant mechanisms, reduced-temperature mix design feasibility, durability constraints, and applicability assessment. Mixture performance serves as the final criterion, while binder and interfacial evidence supports risk screening and molecular evidence provides mechanistic interpretation. The framework supports targeted material selection, experimental design, risk diagnosis, and process optimization.
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