Tags

Type your tag names separated by a space and hit enter

Simultaneously Detecting Subtle and Intensive Human Motions Based on a Silver Nanoparticles Bridged Graphene Strain Sensor.
ACS Appl Mater Interfaces. 2018 Jan 31; 10(4):3948-3954.AA

Abstract

There is a growing demand for flexible electronic devices. In particular, strain sensors with high performance have attracted more and more attention, because they can be attached on clothing or human skin for applications in the real-time monitoring of human activities. However, monitoring human-body motions that include both subtle and intensive motions, and many strain sensors cannot meet the diverse demands simultaneously. In this work, a silver nanoparticles (Ag NPs) bridged graphene strain sensor is developed for simultaneously detecting subtle and intensive human motions. Ag NPs serve as many bridges to connect the self-overlapping graphene sheets, which endows the strain sensor with many excellent performances. Because of the high sensitivity, with a large gauge factor (GF) of 475 and a strain range of >14.5%, high durability of the sensor has been achieved. Besides, the excellent consistency and repeatability of the fabrication process is verified. Furthermore, the model for explaining the working mechanism of the strain sensor is proposed. Most importantly, the designed wearable strain sensor can be applied in human motion detection, including large-scale motions and small-scale motions.

Authors+Show Affiliations

Institute of Microelectronics, Tsinghua University , Beijing 100084, China. Tsinghua National Laboratory for Information Science and Technology (TNList), Tsinghua University , Beijing 100084, China.Institute of Microelectronics, Tsinghua University , Beijing 100084, China. Tsinghua National Laboratory for Information Science and Technology (TNList), Tsinghua University , Beijing 100084, China.Institute of Microelectronics, Tsinghua University , Beijing 100084, China. Tsinghua National Laboratory for Information Science and Technology (TNList), Tsinghua University , Beijing 100084, China.Institute of Microelectronics, Tsinghua University , Beijing 100084, China. Tsinghua National Laboratory for Information Science and Technology (TNList), Tsinghua University , Beijing 100084, China.Institute of Microelectronics, Tsinghua University , Beijing 100084, China. Tsinghua National Laboratory for Information Science and Technology (TNList), Tsinghua University , Beijing 100084, China.Institute of Microelectronics, Tsinghua University , Beijing 100084, China. Tsinghua National Laboratory for Information Science and Technology (TNList), Tsinghua University , Beijing 100084, China.Institute of Microelectronics, Tsinghua University , Beijing 100084, China. Tsinghua National Laboratory for Information Science and Technology (TNList), Tsinghua University , Beijing 100084, China.Institute of Microelectronics, Tsinghua University , Beijing 100084, China. Tsinghua National Laboratory for Information Science and Technology (TNList), Tsinghua University , Beijing 100084, China.Institute of Microelectronics, Tsinghua University , Beijing 100084, China. Tsinghua National Laboratory for Information Science and Technology (TNList), Tsinghua University , Beijing 100084, China.Institute of Microelectronics, Tsinghua University , Beijing 100084, China. Tsinghua National Laboratory for Information Science and Technology (TNList), Tsinghua University , Beijing 100084, China.Department of Chemistry and Center for Nano and Micro Mechanics (CNMM), Tsinghua University , Beijing 100084, China.Department of Chemistry and Center for Nano and Micro Mechanics (CNMM), Tsinghua University , Beijing 100084, China.Institute of Microelectronics, Tsinghua University , Beijing 100084, China. Tsinghua National Laboratory for Information Science and Technology (TNList), Tsinghua University , Beijing 100084, China.Institute of Microelectronics, Tsinghua University , Beijing 100084, China. Tsinghua National Laboratory for Information Science and Technology (TNList), Tsinghua University , Beijing 100084, China.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

29281246

Citation

Yang, Zhen, et al. "Simultaneously Detecting Subtle and Intensive Human Motions Based On a Silver Nanoparticles Bridged Graphene Strain Sensor." ACS Applied Materials & Interfaces, vol. 10, no. 4, 2018, pp. 3948-3954.
Yang Z, Wang DY, Pang Y, et al. Simultaneously Detecting Subtle and Intensive Human Motions Based on a Silver Nanoparticles Bridged Graphene Strain Sensor. ACS Appl Mater Interfaces. 2018;10(4):3948-3954.
Yang, Z., Wang, D. Y., Pang, Y., Li, Y. X., Wang, Q., Zhang, T. Y., Wang, J. B., Liu, X., Yang, Y. Y., Jian, J. M., Jian, M. Q., Zhang, Y. Y., Yang, Y., & Ren, T. L. (2018). Simultaneously Detecting Subtle and Intensive Human Motions Based on a Silver Nanoparticles Bridged Graphene Strain Sensor. ACS Applied Materials & Interfaces, 10(4), 3948-3954. https://doi.org/10.1021/acsami.7b16284
Yang Z, et al. Simultaneously Detecting Subtle and Intensive Human Motions Based On a Silver Nanoparticles Bridged Graphene Strain Sensor. ACS Appl Mater Interfaces. 2018 Jan 31;10(4):3948-3954. PubMed PMID: 29281246.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Simultaneously Detecting Subtle and Intensive Human Motions Based on a Silver Nanoparticles Bridged Graphene Strain Sensor. AU - Yang,Zhen, AU - Wang,Dan-Yang, AU - Pang,Yu, AU - Li,Yu-Xing, AU - Wang,Qian, AU - Zhang,Tian-Yu, AU - Wang,Jia-Bin, AU - Liu,Xiao, AU - Yang,Yi-Yan, AU - Jian,Jin-Ming, AU - Jian,Mu-Qiang, AU - Zhang,Ying-Ying, AU - Yang,Yi, AU - Ren,Tian-Ling, Y1 - 2018/01/17/ PY - 2017/12/28/pubmed PY - 2019/2/14/medline PY - 2017/12/28/entrez KW - Ag nanoparticles KW - bridge KW - graphene KW - human motions KW - strain sensor SP - 3948 EP - 3954 JF - ACS applied materials & interfaces JO - ACS Appl Mater Interfaces VL - 10 IS - 4 N2 - There is a growing demand for flexible electronic devices. In particular, strain sensors with high performance have attracted more and more attention, because they can be attached on clothing or human skin for applications in the real-time monitoring of human activities. However, monitoring human-body motions that include both subtle and intensive motions, and many strain sensors cannot meet the diverse demands simultaneously. In this work, a silver nanoparticles (Ag NPs) bridged graphene strain sensor is developed for simultaneously detecting subtle and intensive human motions. Ag NPs serve as many bridges to connect the self-overlapping graphene sheets, which endows the strain sensor with many excellent performances. Because of the high sensitivity, with a large gauge factor (GF) of 475 and a strain range of >14.5%, high durability of the sensor has been achieved. Besides, the excellent consistency and repeatability of the fabrication process is verified. Furthermore, the model for explaining the working mechanism of the strain sensor is proposed. Most importantly, the designed wearable strain sensor can be applied in human motion detection, including large-scale motions and small-scale motions. SN - 1944-8252 UR - https://www.unboundmedicine.com/medline/citation/29281246/Simultaneously_Detecting_Subtle_and_Intensive_Human_Motions_Based_on_a_Silver_Nanoparticles_Bridged_Graphene_Strain_Sensor_ L2 - https://dx.doi.org/10.1021/acsami.7b16284 DB - PRIME DP - Unbound Medicine ER -
Try the Free App:
Prime PubMed app for iOS iPhone iPad
Prime PubMed app for Android
Prime PubMed is provided
free to individuals by:
Unbound Medicine.