The George W. Woodruff School of Mechanical Engineering, Renewable Bioproduct Institute , Georgia Institute of Technology , Atlanta , Georgia 30332 , United States.
Department of Machine Intelligence and Systems Engineering, Faculty of Systems Science and Technology , Akita Prefectural University , Yurihonjo 015-0055 , Japan.
ACS Appl Mater Interfaces. 2019 Oct 9;11(40):37051-37059. doi: 10.1021/acsami.9b11596. Epub 2019 Sep 10.
The development of highly sensitive wearable and foldable pressure sensors is one of the central topics in artificial intelligence, human motion monitoring, and health care monitors. However, current pressure sensors with high sensitivity and good durability in low, medium, and high applied strains are rather limited. Herein, a flexible pressure sensor based on hierarchical three-dimensional and porous reduced graphene oxide (rGO) fiber fabrics as the key sensing element is presented. The internal conductive structural network is formed by the rGO fibers which are mutually contacted by interfused or noninterfused fiber-to-fiber interfaces. Thanks to the unique structures, the sensor can show an excellent sensitivity from low to high applied strains (0.24-70.0%), a high gauge factor (1668.48) at an applied compression of 66.0%, a good durability in a wide range of frequencies, a low detection limit (1.17 Pa), and anultrafast response time (30 ms). The dominated mechanism is that under compression, the slide of the graphene fibers through the polydimethylsiloxane matrix reduces the connection points between the fibers, causing a surge in electrical resistance. In addition, because graphene fibers are porous and defective, the change in geometry of the fibers also causes a change in the electrical resistance of the composite under compression. Furthermore, the interfused fiber-to-fiber interfaces can strengthen the mechanical stability under 0.01-1.0 Hz loadings and high applied strains, and the wrinkles on the surface of the rGO fibers increased the sensitivity under tiny loadings. In addition, the noninterfused fiber-to-fiber interfaces can produce a highly sensitive contact resistance, leading to a higher sensitivity at low applied strains.
高度灵敏的可穿戴和可折叠压力传感器的发展是人工智能、人体运动监测和医疗保健监测的核心课题之一。然而，目前具有在低、中和高应用应变下具有高灵敏度和良好耐用性的压力传感器相当有限。在此，提出了一种基于分层三维多孔还原氧化石墨烯（rGO）纤维织物作为关键传感元件的柔性压力传感器。rGO 纤维相互接触形成内部导电结构网络，这些纤维通过交织或非交织的纤维-纤维界面相互接触。由于独特的结构，传感器在低至高应用应变（0.24-70.0%）范围内表现出优异的灵敏度，在 66.0%的压缩下具有高应变系数（1668.48），在宽频率范围内具有良好的耐用性，低检测限（1.17 Pa）和超快响应时间（30 ms）。主要机制是在压缩下，石墨烯纤维在聚二甲基硅氧烷基质中的滑动减少了纤维之间的连接点，导致电阻急剧增加。此外，由于石墨烯纤维是多孔和有缺陷的，纤维的几何形状变化也会导致复合材料在压缩下的电阻变化。此外，交织的纤维-纤维界面可以增强 0.01-1.0 Hz 载荷和高应用应变下的机械稳定性，而 rGO 纤维表面的褶皱则增加了微小载荷下的灵敏度。此外，非交织的纤维-纤维界面可以产生高度灵敏的接触电阻，从而在低应用应变下具有更高的灵敏度。
