Force-sensitive Response Mechanism of Pavement Strain Self-sensing Composites Based on Molecular Dynamics Simulations
XIN Xue1,2,*, WANG Xin2, XU Sai1, CUI Jiahao1, YAO Zhanyong2
1 School of Civil Engineering and Architecture, University of Jinan, Jinan 250022, China 2 School of Qilu Transportation, Shandong University, Jinan 250002, China
Abstract: The development of polymer-based self-sensing mechanosensitive composites provides a new idea for the strain detection of asphalt pavements. Based on the self-sensing mechanosensitive composites technology, the effective monitoring of the pavement micro-strain level (10-6) can be realized by setting epoxy resin as the polymer matrix and micro-nano-structured carbon materials, such as CNTs, CB, GNP. In order to investigate the changes in the electrical conductivity of complex micro-nano-structured polymer strain self-sensing composites with multiple levels, scales and interactions, this paper constructs a kinetic model of the micro-nano conductive structure-polymer matrix and its interfacial inte-ractions by using all-atom-system molecular dynamics simulation. The conductive filler contribution and orientation change were simulated from molecular point of view to realize the systematic study of the influence of relevant parameters on the electrical conductivity and mechanical properties of the materials from the microscopic level and molecular point of view. The results show that: the compounding of CB and GNP in CNTs affects the conductivity Λ of the composite materials, but CB and GNP show a large difference in the trend of change due to their volume effect and the interaction between fillers and the splicing form. The change of the radial distribution function of the conductive fillers RDF shows that the g(r) value at the peak value is significantly lower than that of single CNTs with the same volume fraction after the incorporation of CB and GNP. The g(r) value at the peak is significantly lower than that of single CNTs with the same volume fraction, indicating that the addition of CB and GNP can effectively inhibit the aggregation of CNTs. The maximum cluster size Cn, the total number of clusters Nc, the coordination number CN, and the distribution probability PN indicate that in the case of effective dispersion, both types of complex conductive materials have a large impact on the conductive network morphology, which in turn alters the controlling body of the force-sensitive response of the strain self-sensing composites.
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2026, Vol. 40 
