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<p>This review examines hybrid and multifunctional asphalt modifiers for enhancing pavement performance and sustainability. By integrating polymers, nanomaterials, and waste-derived fillers, these systems generate multiphase networks that improve rutting resistance, fatigue tolerance, and low-temperature flexibility, while multifunctional additives enable self-healing and self-sensing capabilities. Recycled and bio-based materials can reduce environmental impacts when they substitute virgin inputs and extend service life, but laboratory gains remain constrained by interfacial compatibility, dispersion quality, aging sensitivity, and scale-up uncertainty. Advanced characterization, molecular modelling, numerical simulation, machine learning, and digital-twin concepts provide tools for formulation optimization, condition prediction, preventive maintenance, and field-performance updating. The review further introduces a methodologically conservative analytical layer, including a worked homogeneous pooled subset, a conservative Synergy Index example, decision-support equations, LCA/LCCA metrics, a Circularity-Adjusted Synergy Index, a critical digital-twin evidence synthesis, and recommendations for standards bodies. Overall, hybrid and multifunctional asphalt modifiers provide a strategic route toward durable, low-carbon pavements, provided that claims are supported by reproducible data, field validation, and transparent circularity assessment.</p>

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Hybrid and Multifunctional Asphalt Pavements: An Evidence-Based Review of Computational Intelligence, Digital Twins, and Circular Deployment

  • 期刊论文

  • 发表日期：

    2026年6月23日

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  • Adham Mohammed Alnadish,
  • Abdul Waheed

摘要

This review examines hybrid and multifunctional asphalt modifiers for enhancing pavement performance and sustainability. By integrating polymers, nanomaterials, and waste-derived fillers, these systems generate multiphase networks that improve rutting resistance, fatigue tolerance, and low-temperature flexibility, while multifunctional additives enable self-healing and self-sensing capabilities. Recycled and bio-based materials can reduce environmental impacts when they substitute virgin inputs and extend service life, but laboratory gains remain constrained by interfacial compatibility, dispersion quality, aging sensitivity, and scale-up uncertainty. Advanced characterization, molecular modelling, numerical simulation, machine learning, and digital-twin concepts provide tools for formulation optimization, condition prediction, preventive maintenance, and field-performance updating. The review further introduces a methodologically conservative analytical layer, including a worked homogeneous pooled subset, a conservative Synergy Index example, decision-support equations, LCA/LCCA metrics, a Circularity-Adjusted Synergy Index, a critical digital-twin evidence synthesis, and recommendations for standards bodies. Overall, hybrid and multifunctional asphalt modifiers provide a strategic route toward durable, low-carbon pavements, provided that claims are supported by reproducible data, field validation, and transparent circularity assessment.