PSI - Issue 83

Shayiq Rashid et al. / Procedia Structural Integrity 83 (2026) 79–84

83

Pavement composite

Year

Functional phases

Mechanism

Scale

Results

Ref. #

ACEP with 5% EPM (PVDF-HFP + carbon black) delivers stable piezoelectric output (~260 mV at 5 mm) and acceptable binder properties (penetration 55.2 dmm, ductility 285 mm, softening point 62.3 °C). Excess EPM causes agglomeration/pores and weaker polarization, identifying 5% as the optimal content for smart, energy harvesting asphalt that also supports battery-waste recycling. Carbon-fiber ASS reached percolation at 0.5–1.0 wt% and exhibited strong piezoresistivity under cyclic loading, as asphalt matrix deformation improved conductive paths; four electrode/DIC tests confirmed robust electromechanical coupling.

P. Li et al.,

Asphalt #70 +PVDF-HFP

2024

CB

Piezoelectric

Lab

Class C450 Bitumen + Aggregates

CF: 0.5-4.0% (avg dia 7 micrometer and L=1 mm)

Deng et al.,

2025

Piezoresistive

Lab

CF: Carbon Fiber, SF: Steel Fiber, PMB: Polymer Modified Bitumen, SSWs: Stainless Steel Wires, SSFs: Stainless Steel Fibers, CNF: Carbon Nano Fibers, PC: Portland Cement, PZT: Lead Zirconate Titanate, PVDF: Polyvinylidene Fluoride, CB: Carbon Black, ε r: Relative Dielectric Constant, σ c: Compressive strength, σ f: Flexural strength, PVDF-HFP: Polyvinylidene Fluoride Hexafluoropropylene, ASS: Asphalt-Based Self-Sensing Sensors, DIC: Digital Image Correlation, EPM: Electroactive Polymer Modifier, ACEP: Asphalt-Based Composites Containing Electroactive Polymer 3. Challenges and Future Directions The most significant technical challenge facing self-sensing pavements lies in ensuring signal fidelity and reliability. Current piezoresistive composites suffer from high sensitivity to pervasive environmental noise, specifically temperature and moisture variations, which frequently mask the desired electrical changes induced by structural strain or micro-damage (Birgin et al., 2020; Gulisano et al., 2024b). This lack of signal decoupling is the critical research gap that must be bridged for practical application. Furthermore, integrating conductive nano-additives requires solving complex engineering problems related to uniform dispersion at industrial scales, directly impacting sensing consistency and repeatability (Ding et al., 2021). Beyond material science, a lack of standardized testing protocols and proven long-term durability under full-scale traffic loads prevents the technology from achieving widespread adoption and clear life-cycle cost (LCC) justification in infrastructure management. The transition from pilot studies to large-scale implementation introduces substantial integration challenges, primarily concerning cost, data infrastructure, and system validation. The current expense of high-performance conductive fillers and the necessary robust data acquisition hardware impedes cost-effectiveness compared to conventional methods. However, the future is highly dependent on leveraging this technology as a foundational