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Please use this identifier to cite or link to this item: https://libeldoc.bsuir.by/handle/123456789/35249
Title: Structure-property relationships in graphene-based strain and pressure sensors for potential artificial intelligence applications
Authors: Luo, Z.
Hu, X.
Tian, X.
Luo, C.
Xu, H.
Zhang, J.
Qiao, F.
Wu, X.
Borisenko, V. E.
Chu, J.
Keywords: публикации ученых;Graphene;strain sensor;pressure sensor;structure-property;artificial intelligence
Issue Date: 2019
Publisher: Multidisciplinary Digital Publishing Institute
Citation: Structure-property relationships in graphene-based strain and pressure sensors for potential artificial intelligence applications / Z. Luo [et al.] // Sensors. - 2019. - № 19(5). – Р. 1250. DOI: https://doi.org/10.3390/s19051250
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.
URI: https://libeldoc.bsuir.by/handle/123456789/35249
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