Lopes Cláudia, Araújo Andreia, Silva Fernando, Pappas Panagiotis-Nektarios, Termine Stefania, Trompeta Aikaterini-Flora A, Charitidis Costas A, Martins Carla, Mould Sacha T, Santos Raquel M
Physics Centre of Minho and Porto Universities (CF-UM-UP), University of Minho, 4710-057 Braga, Portugal.
LaPMET-Laboratory of Physics for Materials and Emergent Technologies, University of Minho, 4710-057 Braga, Portugal.
Polymers (Basel). 2024 Sep 24;16(19):2698. doi: 10.3390/polym16192698.
High electrical conductivity, along with high piezoresistive sensitivity and stretchability, are crucial for designing and developing nanocomposite strain sensors for damage sensing and on-line structural health monitoring of smart carbon fiber-reinforced polymer (CFRP) composites. In this study, the influence of the geometric features and loadings of carbon-based nanomaterials, including reduced graphene oxide (rGO) or carbon nanofibers (CNFs), on the tunable strain-sensing capabilities of epoxy-based nanocomposites was investigated. This work revealed distinct strain-sensing behavior and sensitivities (gauge factor, GF) depending on both factors. The highest GF values were attained with 0.13 wt.% of rGO at various strains. The stability and reproducibility of the most promising self-sensing nanocomposites were also evaluated through ten stretching/relaxing cycles, and a distinct behavior was observed. While the deformation of the conductive network formed by rGO proved to be predominantly elastic and reversible, nanocomposite sensors containing 0.714 wt.% of CNFs showed that new conductive pathways were established between neighboring CNFs. Based on the best results, formulations were selected for the manufacturing of pre-impregnated materials and related smart CFRP composites. Digital image correlation was synchronized with electrical resistance variation to study the strain-sensing capabilities of modified CFRP composites (at 90° orientation). Promising results were achieved through the incorporation of CNFs since they are able to form new conductive pathways and penetrate between micrometer-sized fibers.
高电导率以及高压阻灵敏度和拉伸性,对于设计和开发用于智能碳纤维增强聚合物(CFRP)复合材料损伤传感和在线结构健康监测的纳米复合应变传感器至关重要。在本研究中,研究了包括还原氧化石墨烯(rGO)或碳纳米纤维(CNF)在内的碳基纳米材料的几何特征和负载量对环氧基纳米复合材料可调应变传感能力的影响。这项工作揭示了取决于这两个因素的不同应变传感行为和灵敏度(应变片系数,GF)。在不同应变下,添加0.13 wt.%的rGO可获得最高的GF值。还通过十个拉伸/松弛循环评估了最有前景的自传感纳米复合材料的稳定性和可重复性,并观察到了明显的行为。虽然由rGO形成的导电网络的变形被证明主要是弹性的和可逆的,但含有0.714 wt.% CNF的纳米复合传感器表明,相邻CNF之间建立了新的导电通路。基于最佳结果,选择配方用于制造预浸材料和相关的智能CFRP复合材料。将数字图像相关技术与电阻变化同步,以研究改性CFRP复合材料(90°取向)的应变传感能力。由于CNF能够形成新的导电通路并渗透到微米级纤维之间,因此通过加入CNF取得了有希望的结果。