石墨烯/碳纳米管嵌入式纤维传感器对树脂基复合材料原位监测的结构-性能关系对比

基于碳纳米材料的纤维传感技术已成为复合材料原位结构健康监测领域中一项十分有前景的技术。本研究采用两种不同的碳纳米传感元件—碳纳米管(carbon nanotube, CNT)涂层纤维(carbon nanotube coated fibers,CNTF)和还原氧化石墨烯(reduced graphene oxide, RGO)涂层纤维(reduced graphene oxide coated fibers, RGOF),分别制造合成具有自传感特性的复合材料,并比较研究两种嵌入式纤维传感器的传感性能和机理。从两种传感器的压阻效应可看出:RGOF的压阻灵敏度更高,并清晰地展现出从线性至非线性的两阶段压阻行为;而CNTF,则在发生断裂前始终呈现出平稳而有序的电学信号。这种强烈的结构-性能关系,可以用树脂渗透理论加以阐释。对CNTF而言,树脂分子可以渗透到其多孔的网络结构中,形成集成在纤维表面完整的CNT/树脂纳米复合结构。相比之下,具有大横向尺寸和表面一致性的RGO则可形成阻碍树脂渗透的无创网络结构。对实验结果和传感机理的进一步分析与研究表明,CNTF适用于材料的力学状态识别与长期监测,而RGOF则对结构损伤的早期预警更有实用价值。

Structure-property relationship of graphene/carbon nanotube enabled embeddable fiber sensors for in-situ monitoring of composites

Carbon nanomaterials based sensing technology has become a promising technology in the field of structural health monitoring of composites. Self-sensing composites were achieved with varied sensing elements, including carbon nanotube (CNT) coated fibers (CNTF) and reduced graphene oxide (RGO) coated fibers (RGOF), to compare their sensing performance and mechanism. Piezoresistive response of varied sensors show that RGOF has higher piezoresistive sensitivity and clearly exhibits two-stage behavior from linear to non-linear;whereas, CNTF always exhibits a smooth and orderly electrical signal before fracture occurs. This strong structure-property relationship can be explained by resin infiltration theory. For CNTF, resin molecules can penetrate its porous network structure, forming a complete CNT/resin nanocomposite structure integrated on the fiber surface. In contrast, RGOs with large lateral dimensions and surface consistency can form non-invasive network structure that impedes resin penetration. Further analysis and study show that CNTF is more suitable for long-term monitoring and mechanical state recognition, while RGOF is more practical for the early warning of structural damage.