Highly Stretchable and Ultrasensitive Strain Sensor Based on Reduced Graphene Oxide Microtubes–Elastomer Composite

2015 ◽  
Vol 7 (49) ◽  
pp. 27432-27439 ◽  
Author(s):  
Yongchao Tang ◽  
Zongbin Zhao ◽  
Han Hu ◽  
Yang Liu ◽  
Xuzhen Wang ◽  
...  

2018 ◽  
Vol 265 ◽  
pp. 609-616 ◽  
Author(s):  
Yange Luan ◽  
Shaolin Zhang ◽  
Thuy Hang Nguyen ◽  
Woochul Yang ◽  
Jin-Seo Noh


2017 ◽  
Vol 9 (37) ◽  
pp. 32054-32064 ◽  
Author(s):  
Biao Yin ◽  
Yanwei Wen ◽  
Tao Hong ◽  
Zhongshuai Xie ◽  
Guoliang Yuan ◽  
...  


2017 ◽  
Vol 5 (31) ◽  
pp. 7746-7752 ◽  
Author(s):  
Xueliang Ye ◽  
Zhen Yuan ◽  
Huiling Tai ◽  
Weizhi Li ◽  
Xiaosong Du ◽  
...  

A novel strain sensor based on reduced graphene oxide with ultra-sensitive and ultra-durable performance was fabricated by the chemical layer-by-layer self-assembly method.





Carbon ◽  
2017 ◽  
Vol 111 ◽  
pp. 622-630 ◽  
Author(s):  
Jiesheng Ren ◽  
Chaoxia Wang ◽  
Xuan Zhang ◽  
Tian Carey ◽  
Kunlin Chen ◽  
...  


2020 ◽  
Vol 10 (18) ◽  
pp. 6230
Author(s):  
Rongqing Xu ◽  
Xin Zheng ◽  
Miao Chen ◽  
Lijun Sun ◽  
Jiangwei Chen ◽  
...  

Fabric-based strain sensors can be seamlessly integrated into wearable systems for monitoring various physiological signals. Although many different approaches have been proposed to increase the sensitivity of the fabric-based strain sensor, the linearity and stability in large strains are still challenging. In this paper, a fabric-based strain sensor with good linearity and stability was fabricated via a three-step dip-coating method. Specifically, the combination of multiwall carbon nanotubes and reduced graphene oxide was used as the conductive material to enhance the stability. Meanwhile, microfolded structures between two reduced graphene oxide layers were created via pre-stretching to achieve good linearity. Through mechanical experiments, the performance of the fabric-based strain sensor was characterized. In addition, the practical applications of the strain sensor were demonstrated by monitoring different physiological signals.





2019 ◽  
Vol 31 (3) ◽  
pp. 035501 ◽  
Author(s):  
Suresh Nuthalapati ◽  
Vijay Shirhatti ◽  
Vaishakh Kedambaimoole ◽  
Nagarjuna Neella ◽  
M M Nayak ◽  
...  


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