Ultrasensitive Airflow Sensors Based on Suspended Carbon Nanotube Networks

© 2022 Wiley-VCH GmbH.

Bibliographische Detailangaben
Veröffentlicht in:Advanced materials (Deerfield Beach, Fla.). - 1998. - 34(2022), 18 vom: 13. Mai, Seite e2107062
1. Verfasser: Jiang, Qinyuan (VerfasserIn)
Weitere Verfasser: Li, Run, Wang, Fei, Shi, Xiaofei, Chen, Fengxiang, Huang, Ya, Wang, Baoshun, Zhang, Wenshuo, Wu, Xueke, Wei, Fei, Zhang, Rufan
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2022
Zugriff auf das übergeordnete Werk:Advanced materials (Deerfield Beach, Fla.)
Schlagworte:Journal Article airflow carbon nanotubes networks sensors suspended carbon nanotube networks
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520 |a High-performance airflow sensors are in great demand in numerous fields but still face many challenges, such as slow response speed, low sensitivity, large detection threshold, and narrow sensing range. Carbon nanotubes (CNTs) exhibit many advantages in fabricating airflow sensors due to their nanoscale diameters, excellent mechanical and electrical properties, and so on. However, the intrinsic extraordinary properties of CNTs are not fully exhibited in previously reported CNT-based airflow sensors due to the mixed structures of macroscale CNT assemblies. Herein, this article presents suspended CNT networks (SCNTNs) as high-performance airflow sensors, which are self-assembled by ultralong CNTs and short CNTs in a one-step floating catalyst chemical vapor deposition process. The SCNTN-based airflow sensors achieved a record-breaking short response time of 0.021 s, a high sensitivity of 0.0124 s m-1 , a small detection threshold of 0.11 m s-1 , and a wide detection range of ≈0.11-5.51 m s-1 , superior to most of the state-of-the-art airflow sensors. To reveal the sensing mechanism, an acoustic response testing system and a mathematical model are developed. It is found that the airflow-caused intertube stress change resulted in the resistance variation of SCNTNs 
650 4 |a Journal Article 
650 4 |a airflow 
650 4 |a carbon nanotubes 
650 4 |a networks 
650 4 |a sensors 
650 4 |a suspended carbon nanotube networks 
700 1 |a Li, Run  |e verfasserin  |4 aut 
700 1 |a Wang, Fei  |e verfasserin  |4 aut 
700 1 |a Shi, Xiaofei  |e verfasserin  |4 aut 
700 1 |a Chen, Fengxiang  |e verfasserin  |4 aut 
700 1 |a Huang, Ya  |e verfasserin  |4 aut 
700 1 |a Wang, Baoshun  |e verfasserin  |4 aut 
700 1 |a Zhang, Wenshuo  |e verfasserin  |4 aut 
700 1 |a Wu, Xueke  |e verfasserin  |4 aut 
700 1 |a Wei, Fei  |e verfasserin  |4 aut 
700 1 |a Zhang, Rufan  |e verfasserin  |4 aut 
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773 1 8 |g volume:34  |g year:2022  |g number:18  |g day:13  |g month:05  |g pages:e2107062 
856 4 0 |u http://dx.doi.org/10.1002/adma.202107062  |3 Volltext 
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