Characterizing the Self?Healing Asphalt Materials: A Neutron Imaging Study

This study breaks new ground using neutron computed tomography to investigate asphalt's self?healing properties in detail. By distinguishing bitumen from air voids, it shows that 20% sand filler optimizes crack healing, with larger cracks healing more effectively. These findings could transform sustainable road design, enhancing material durability and extending pavement life.Given the significant role of asphaltic pavement in surface transportation systems, even minor enhancements in asphalt materials hold the potential for cost savings and reduced environmental impacts. The healing properties of asphalt have drawn interest for sustainability, yet much remains unknown about the causes and influencing factors. To leverage self?healing for extending pavement life, understanding the mechanisms and conditions that stimulate microcrack healing is essential. This study aims to investigate the dynamic progress of microcrack closure in asphalt mastics. The time?series evolution of crack closure led by self?healing is tracked by neutron computed tomography, with image processing facilitating volumetric analysis over a 7?h period. The study examines the healing process in mastic samples with three different sand filler contents (10, 20, and 30%). Results show that for all the investigated samples, the healing rate declines exponentially over time, with 100% recovery not achieved after 7?h at room temperature. Filler content?influenced healing speed and 20% sand demonstrate the best performance. Meanwhile, the healing performance varies within the 10% and 30% groups, depending on initial crack size. Additionally, the study finds that initial crack size influences healing behavior in the samples.

» Author: Zhuhuan Liu, Maria C. Cavalli, Anders Kaestner, Lily Poulikakos, Nicole Kringos

» Publication Date: 24/09/2024

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This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement Nº 768737


                   




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