All VN-graphene architecture derived self-powered wearable sensors for ultrasensitive health monitoring

被引:0
|
作者
Lianghao Yu
Yuyang Yi
Ting Yao
Yingze Song
Yiran Chen
Qiucheng Li
Zhou Xia
Nan Wei
Zhengnan Tian
Baoqing Nie
Li Zhang
Zhongfan Liu
Jingyu Sun
机构
[1] Soochow University,College of Energy, Soochow Institute for Energy and Materials Innovations (SIEMIS), Key Laboratory of Advanced Carbon Materials and Wearable Energy Technologies of Jiangsu Province
[2] Soochow University,School of Electronic and Information Engineering
[3] Peking University,Center for Nanochemistry (CNC), Beijing Science and Engineering Center for Nanocarbons, Beijing National Laboratory for Molecular Sciences, College of Chemistry and Molecular Engineering
来源
Nano Research | 2019年 / 12卷
关键词
VN-graphene architecture; solid-state supercapacitor; pressure sensor; self-powered wearable sensor; health monitoring;
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中图分类号
学科分类号
摘要
The booming of wearable electronics has nourished the progress on developing multifunctional energy storage systems with versatile flexibility, which enable the continuous and steady power supply even under various deformed states. In this sense, the synergy of flexible energy and electronic devices to construct integrative wearable microsystems is meaningful but remains quite challenging by far. Herein, we devise an innovative supercapacitor/sensor integrative wearable device that is based upon our designed vanadium nitride-graphene (VN-G) architectures. Flexible quasi-solid-state VN-G supercapacitor with ultralight and binder-free features deliver a specific capacitance of ~ 53 F·g−1 with good cycle stability. On the other hand, VN-G derived pressure sensors fabricated throughout a spray-printing process also manifest favorably high sensitivity (40 kPa−1 at the range of 2–10 kPa), fast response time (~ 130 ms), perfect skin conformability, and outstanding stability under static and dynamic pressure conditions. In turn, their complementary unity into a self-powered wearable sensor enables the precise detection of physiological motions ranging from pulse rate to phonetic recognition, holding promise for in-practical health monitoring applications. [graphic not available: see fulltext]
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页码:331 / 338
页数:7
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