Electric field–tunable self-sensing nanocomposites with aligned CNTs for in-situ pavement health monitoring: Electrodynamic alignment, sensor development, and performance validation

Abstract

As urban societies increasingly rely on road infrastructures, the health of pavements becomes a pressing concern. Accurate in-situ monitoring is essential for early detection and maintenance, with tensile strain and temperature being pivotal health indicators. While traditional sensors, such as resistive strain gauges and fiber Bragg gratings, offer solutions, they face challenges in durability and sensitivity. This study introduces electric field-tunable self-sensing nanocomposites with aligned carbon nanotube (CNT) networks in an epoxy matrix as a promising solution for precise pavement health assessment. Through meticulous examination of electric field, environmental, and material parameters, an optimal alignment of CNTs was achieved. Optimization led to sensors that excel in capturing minute strains, showcasing impressive attributes like a gauge factor over 8, rapid response and recovery times of 8 ms and 7 ms respectively, and exceptional durability withstanding 20,000 loading–unloading cycles. Another distinctive feature is the dual-sensing capability, enabling concurrent monitoring of strain and temperature without mutual interference. In real-world applications, the developed sensors actively monitor dynamic pavement responses under moving rollers and vehicles at varied loading models. This innovative approach promises significant advancements in the realm of pavement health monitoring, addressing existing challenges and opening avenues for next-generation pavement sensor development.