Shimpi Prasad, Omastova Maria, Aniskevich Andrey, Zeleniakiene Daiva
Department of Mechanical Engineering, Kaunas University of Technology, 51424 Kaunas, Lithuania.
Polymer Institute, Slovak Academy of Sciences, 84541 Bratislava, Slovakia.
Materials (Basel). 2022 Apr 7;15(8):2730. doi: 10.3390/ma15082730.
The aim of this study was to develop a process-efficient smart three-dimensional (3D) woven composite T-profile by depositing MXene nanoparticles at the junction for sensing damage and deformation at the junction. Such smart composites could find application in the online health monitoring of complex-shaped parts. The composites were manufactured by infusing epoxy resin in a single-layer fabric T-profile preform, woven in folded form on a dobby shuttle loom using 300 tex glass roving. The chemically etched TiCT MXene nanoparticles were dispersed in deionised water and 10 layers were sprayed at the junction of the composite to form a conductive coating. The MXene-coated composite T-profile specimens were subjected to tensile and fatigue loading to study the electromechanical response of the MXene coating to applied displacement. The results showed that the MXene coating was able to sense the sample deformation till ultimate failure of the composite. The MXene coating was also able to effectively sense the tensile-tensile fatigue loading, carried out at 2000 cycles and 4000 cycles for a 50 N-0.5 Hz and a 100 N-1 Hz load-frequency combination, respectively, while being sensitive to the overall deformation of the composite. The smart complex-shaped composites developed in this work were capable of monitoring their health under tensile and fatigue loading in real time.
本研究的目的是通过在连接点处沉积MXene纳米颗粒来开发一种工艺高效的智能三维(3D)编织复合材料T型材,以检测连接点处的损伤和变形。这种智能复合材料可应用于复杂形状部件的在线健康监测。复合材料是通过将环氧树脂注入单层织物T型材预制件中制成的,该预制件在多臂梭织机上以折叠形式编织,使用300 tex玻璃粗纱。将化学蚀刻的TiCT MXene纳米颗粒分散在去离子水中,并在复合材料的连接点处喷涂10层以形成导电涂层。对涂有MXene的复合材料T型材试样进行拉伸和疲劳加载,以研究MXene涂层对施加位移的机电响应。结果表明,MXene涂层能够感知样品变形,直至复合材料最终失效。MXene涂层还能够有效感知拉伸-拉伸疲劳加载,分别在50 N-0.5 Hz和100 N-1 Hz的载荷-频率组合下进行2000次循环和4000次循环,同时对复合材料的整体变形敏感。本研究中开发的智能复杂形状复合材料能够在拉伸和疲劳加载下实时监测其健康状况。