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Structure-Property Relationships in Graphene-Based Strain and Pressure Sensors for Potential Artificial Intelligence Applications
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 p...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6427630/ https://www.ncbi.nlm.nih.gov/pubmed/30871069 http://dx.doi.org/10.3390/s19051250 |
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author | Luo, Zewei Hu, Xiaotong Tian, Xiyue Luo, Chen Xu, Hejun Li, Quanling Li, Qianhao Zhang, Jian Qiao, Fei Wu, Xing Borisenko, V. E. Chu, Junhao |
author_facet | Luo, Zewei Hu, Xiaotong Tian, Xiyue Luo, Chen Xu, Hejun Li, Quanling Li, Qianhao Zhang, Jian Qiao, Fei Wu, Xing Borisenko, V. E. Chu, Junhao |
author_sort | Luo, Zewei |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6427630 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-64276302019-04-15 Structure-Property Relationships in Graphene-Based Strain and Pressure Sensors for Potential Artificial Intelligence Applications Luo, Zewei Hu, Xiaotong Tian, Xiyue Luo, Chen Xu, Hejun Li, Quanling Li, Qianhao Zhang, Jian Qiao, Fei Wu, Xing Borisenko, V. E. Chu, Junhao Sensors (Basel) Review 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. MDPI 2019-03-12 /pmc/articles/PMC6427630/ /pubmed/30871069 http://dx.doi.org/10.3390/s19051250 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Luo, Zewei Hu, Xiaotong Tian, Xiyue Luo, Chen Xu, Hejun Li, Quanling Li, Qianhao Zhang, Jian Qiao, Fei Wu, Xing Borisenko, V. E. Chu, Junhao Structure-Property Relationships in Graphene-Based Strain and Pressure Sensors for Potential Artificial Intelligence Applications |
title | Structure-Property Relationships in Graphene-Based Strain and Pressure Sensors for Potential Artificial Intelligence Applications |
title_full | Structure-Property Relationships in Graphene-Based Strain and Pressure Sensors for Potential Artificial Intelligence Applications |
title_fullStr | Structure-Property Relationships in Graphene-Based Strain and Pressure Sensors for Potential Artificial Intelligence Applications |
title_full_unstemmed | Structure-Property Relationships in Graphene-Based Strain and Pressure Sensors for Potential Artificial Intelligence Applications |
title_short | Structure-Property Relationships in Graphene-Based Strain and Pressure Sensors for Potential Artificial Intelligence Applications |
title_sort | structure-property relationships in graphene-based strain and pressure sensors for potential artificial intelligence applications |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6427630/ https://www.ncbi.nlm.nih.gov/pubmed/30871069 http://dx.doi.org/10.3390/s19051250 |
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