Mitigating the Degradation of Microwave Self-Healing Efficiency in Asphalt Mixtures under Water Damage and Freeze–Thaw Cycles via Silicon Carbide Aggregates

To assess the potential of silicon carbide (SiC) as microwave-enhanced aggregates for improving the self-healing performance of asphalt mixtures, this study examined the influence of SiC particle size and substitution rate under water damage and freeze–thaw conditions. Microwave heating tests compared the thermal responses of SiC, steel slag, natural aggregates, and SiC-enhanced asphalt mixtures. Mixtures without SiC and those containing 25% by weight fine SiC were further evaluated for self-healing after water damage and freeze–thaw cycles. COMSOL simulations were used to analyze temperature distribution and energy utilization. Results show that SiC reached much higher temperatures than natural aggregates under microwave heating, and the optimal substitution rate was 25% by weight for fine SiC (0.075–2.36 mm), which increased the healing index by 17% and reduced water and freeze–thaw damage effects by 5.2 and 16.3%, respectively. Simulations indicated minimal temperature differences between SiC and surrounding aggregates, while energy utilization efficiency improved by 43% at higher SiC contents. These findings demonstrate that incorporating SiC can enhance microwave heating efficiency and mitigate performance loss caused by moisture and freeze–thaw in asphalt mixtures, highlighting its promise as a functional aggregate for durable, self-healing asphalt pavements.

Authors

Publication Details

Journal
Journal of Materials in Civil Engineering
Published
2026-04-24
DOI
https://doi.org/10.1061/jmcee7.mteng-22810
Primary Topic
Asphalt Pavement Performance Evaluation
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Mitigating the Degradation of Microwave Self-Healing Efficiency in Asphalt Mixtures under Water Damage and Freeze–Thaw Cycles via Silicon Carbide Aggregates

Guojia Fan, Xiaoming Liu, Sheng Li
Journal of Materials in Civil Engineering
Asphalt Pavement Performance Evaluation
article

Mitigating the Degradation of Microwave Self-Healing Efficiency in Asphalt Mixtures under Water Damage and Freeze–Thaw Cycles via Silicon Carbide Aggregates

Guojia Fan, Xiaoming Liu, Sheng Li
article en

Abstract

To assess the potential of silicon carbide (SiC) as microwave-enhanced aggregates for improving the self-healing performance of asphalt mixtures, this study examined the influence of SiC particle size and substitution rate under water damage and freeze–thaw conditions. Microwave heating tests compared the thermal responses of SiC, steel slag, natural aggregates, and SiC-enhanced asphalt mixtures. Mixtures without SiC and those containing 25% by weight fine SiC were further evaluated for self-healing after water damage and freeze–thaw cycles. COMSOL simulations were used to analyze temperature distribution and energy utilization. Results show that SiC reached much higher temperatures than natural aggregates under microwave heating, and the optimal substitution rate was 25% by weight for fine SiC (0.075–2.36 mm), which increased the healing index by 17% and reduced water and freeze–thaw damage effects by 5.2 and 16.3%, respectively. Simulations indicated minimal temperature differences between SiC and surrounding aggregates, while energy utilization efficiency improved by 43% at higher SiC contents. These findings demonstrate that incorporating SiC can enhance microwave heating efficiency and mitigate performance loss caused by moisture and freeze–thaw in asphalt mixtures, highlighting its promise as a functional aggregate for durable, self-healing asphalt pavements.

Journal of Materials in Civil EngineeringVol. 38(7)
Affordable and clean energy
Openalex Percentile: Top 7%
Asphalt Pavement Performance Evaluation
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.