Structure-Property Relationships in Graphene-Based Strain and Pressure Sensors for Potential Artificial Intelligence Applications

Abstract

Wearable electronic sensing devices are deemed to be a crucial technology of smart personal electronics. Strain and pressure sensors, one of the most popular research directions in recent years, are the key components of smart and flexible electronics. Graphene, as an advanced nanomaterial, exerts pre-eminent characteristics including high electrical conductivity, excellent mechanical properties, and flexibility. The above advantages of graphene provide great potential for applications in mechatronics, robotics, automation, human-machine interaction, etc.: graphene with diverse structures and leverages, strain and pressure sensors with new functionalities. Herein, the recent progress in graphene-based strain and pressure sensors is presented. The sensing materials are classified into four structures including 0D fullerene, 1D fiber, 2D film, and 3D porous structures. Different structures of graphene-based strain and pressure sensors provide various properties and multifunctions in crucial parameters such as sensitivity, linearity, and hysteresis. The recent and potential applications for graphene-based sensors are also discussed, especially in the field of human motion detection. Finally, the perspectives of graphene-based strain and pressure sensors used in human motion detection combined with artificial intelligence are surveyed. Challenges such as the biocompatibility, integration, and additivity of the sensors are discussed as well.

Highly Uniform and Low Hysteresis Piezoresistive Pressure Sensors Based on Chemical Grafting of Polypyrrole on Elastomer Template with Uniform Pore Size

“…This would be a major issue for practical applications as it would significantly degrade the reliability of the sensors. Hysteresis is also a major issue with piezoresistive materials, which renders the measured signal inaccurate . Many reported piezoresistive sensors show large difference in the output signal under loading and unloading of pressure .…”

“…Hysteresis is also a major issue with piezoresistive materials, which renders the measured signal inaccurate . Many reported piezoresistive sensors show large difference in the output signal under loading and unloading of pressure . Also, their initial resistance changes after repeated loading of pressure .…”

Directional Response of Randomly Dispersed Carbon Nanotube Strain Sensors

“…This behavior means a severe limitation for the possibilities of CNT-doped films as strain sensors when compared to alternatives, such as strain gauges or fiber optic sensors, which are able to distinguish the strain components, but this is similar to the behavior of piezoelectric films, whose response is also insensitive to the direction of in-plane strains. In an excellent review on graphene-based strain sensors [30], the similarities among resistive, capacitive, and piezoelectric sensors were also highlighted.…”

Artificial intelligence-enabled smart mechanical metamaterials: advent and future trends

“…Unlike the AI methods, almost all of the traditional statistical methods rely on the prior knowledge of the nature of the relationship between dependent and independent variables [240][241][242][243]. Given their capability in capturing subtle knowledge without a need to assume prior form of the relationship, AI has become a powerful component in integrated systems or an alternative approach to conventional techniques, which is typically applied to resolve complicated practical problems in various fields such as materials science [244][245][246][247][248][249][250] and engineering [251][252][253][254][255][256][257][258][259][260][261][262][263][264][265]. Due to the inadequacy of physics-based models developed using the first principles, AI has recently attracted significant attention in architected materials and structures [266][267][268][269][270][271][272].…”