Sensitivity optimization strategies of carbon-based flexible strain sensors for low strain sensing : from 1D carbon nanotube to 2D graphene

Abstract

Flexible strain sensors have gained prominence for their ability to detect and monitor mechanical deformations in various applications. These sensors, typically made from flexible and stretchable materials, offer advantages in wearable technology, structural health monitoring, and robotics by providing real-time feedback on strain, making them crucial for dynamic and adaptable systems. Carbon-based nanomaterials like carbon nanotubes (CNTs) and graphene are valued for their strength, conductivity, and surface area, ideal for sensor technologies. Their mechanical and electrical properties enable precise strain detection. The tunnelling effect in these materials enhances sensor sensitivity, making them ideal for optimizing strain sensors in various applications. This thesis proposes strategies for optimizing the sensitivity of (CNTs or graphene)-based strain sensors to meet the increasing demand for high sensitivity in various applications. The strategies involve modifying and combining nanofillers, such as applying viscous polymer nanolayers, surface modifications, hybrid nanofiller combinations, and sandwiched-like structures. These strategies aim to enhance sensitivity and enable more accurate and precise strain detection in the sensors. For CNT-based sensors, this research focuses on optimizing thin-film strain sensors based on multi-walled carbon nanotubes (MWNTs) nanocomposites. The goal is to detect low deformations and micro-vibrations generated by ultrasonic waves, where the tunnelling effect plays a crucial role. To improve the dispersion of MWNTs, a thin viscous polydopamine (PDA) nanolayer is coated on the surface of MWNTs, resulting in a 40% increase in sensitivity compared to uncoated MWNTs. Also, nanocomposite sensors constructed from hybrid carbon nanofillers (PDA@MWNTs and graphene) exhibited significantly enhanced low deformation signal acquisition. Both types of nanofillers contribute significantly to the improved sensitivity of the proposed sensor, leading to increased geometrical contact between the nanofillers and thereby intensifying the tunneling effect. To overcome the non-conductive nature of PDA nanolayers, which limits electron tunneling, silver nanoparticles (AgNPs) are immobilized on the surfaces of MWNTs through a PDA-assisted process. Material characterizations confirm the effective incorporation of AgNPs into the PDA nanolayers on the surfaces of MWNTs, enhancing the electron transport ability of the PDA nanolayers and facilitating electron tunneling between adjacent nanofillers. Static tensile tests demonstrate that sensor specimens made from nanofillers with immobilized AgNPs exhibit a sensitivity up to 37% higher than those made with PDA nanolayers alone. Moreover, high-frequency vibration tests reveal that the AgNP content in a sensor specimen positively impacts its sensitivity across a wide frequency spectrum. For graphene-based sensors, this study is the first time to attempt the feasibility of graphene oxide (GO), equipped with great dispersion ability, in preparing Pen-on-paper (PoP) inks with high sensitivity in multitype strain sensing. First, graphene was oxidized by the Hummer’s method to different degree of oxidation and then put into the home-made print pen as the writable instruments to fabricate drawing-made sensors. The materials characterizations confirm that the GO have been separated into different degree. The GO-based paper strain sensors show the ability to capture the strain signals of tensile, compression and pressure. It is also found that the paper sensors show a similar GF value even when the sensor were placed on boards in sensing the same strains, which illustrating the reliability of the GO-based paper sensors. To further enhance sensitivity of graphene-based strain sensors, a 2-step PDA nanolayer coating method, that is to reduce DA first on graphene and then conduct the PDA coating, is proposed for controlling the tunnelling distance between graphene flakes. The surface of PDA-coated reduced graphene oxide (rGO) prepared using the 2-step method is shown to be smoother compared to direct PDA coating. Thin-film full-filler strain sensors are fabricated using the coated nanofillers, and an improvement of 21% in sensitivity is observed compared to sensors with direct PDA coating. By adjusting the number of coating cycles, different thicknesses of PDA nanolayers on graphene can be obtained, affecting the surface roughness and agglomeration of graphene nanofillers. The sensitivity of PDA-coated rGO sensors exhibits an initial increase and then a decline as the PDA content increases, indicating an optimal distance between neighbouring graphene flakes for achieving the tunnelling effect. Moreover, a hybrid approach is explored by combining PDA-coated rGO with black phosphorene (BP) nanosheets to create hybrid full-filler strain sensors due to the excellent piezoresistive effect of BP. The PDA nanolayers on rGO control the distance between graphene nanofillers, enhancing the tunnelling effect. The thickness of BP nanofillers, achieved through centrifugation, negatively impacts sensitivity, with thicker BP resulting in higher piezoresistivity. The hybrid strain sensors demonstrate varying sensitivity due to the synergy between the piezoresistivity of BP and the tunnelling effect of graphene. A hybrid BP-PDA@rGO full-filler sensor with a sensitivity of up to 1300 is achieved, highlighting the potential for obtaining strain sensors with even higher sensitivity through the use of different nanofillers and their mechanisms. In conclusion, this thesis proposes strategies to optimize the sensitivity of (CNT and graphene)-based strain sensors through nanofiller modifications and/or combinations. The research findings lead to significant improvements in sensitivity, enabling more precise strain detection in various valuable applications. Those advancements contribute to the overall progress of strain sensing research.