Highly sensitive and large range strain sensor based on synergetic effects with double conductive layer structures
| Autor: | Lei Han, Xiangyu Ren, Shi Su, Jing Wang, Meng Nie, Lei Wen |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Materials science
Electronic skin Wearable computer 02 engineering and technology Carbon nanotube Elastomer 01 natural sciences law.invention law 0103 physical sciences Electronics Sensitivity (control systems) Electrical and Electronic Engineering Instrumentation Electrical conductor 010302 applied physics business.industry Metals and Alloys 021001 nanoscience & nanotechnology Condensed Matter Physics Surfaces Coatings and Films Electronic Optical and Magnetic Materials Dynamic loading Optoelectronics 0210 nano-technology business |
| Zdroj: | Sensors and Actuators A: Physical. 318:112515 |
| ISSN: | 0924-4247 |
| Popis: | The increasing demand for wearable electronic devices is promoting the development of highly elastic strain sensors, which can monitor various physical parameters and essential factors for realizing next generation electronics. However, it is still challenging to simultaneously achieve wearable strain sensors with sufficient sensitivity within wide stretching sensing ranges under mechanical stimuli in view of their widespread applications, including electronic skin, smart textiles, as well as healthcare monitoring. Herein, we propose a simple, cost-effective strain sensor based on synergetic conductive networks constituted by double-layer microstructures with multi-walled carbon nanotubes and elastomer. The micro-spinous structures of MWCNTs and the peak-valley microstructures have extended stretching sensing ranges with high sensitivities. The double-layer strain sensor exhibits high gauge factors (GF = 12.3 and 29.4) in the two linear stretching strain ranges (0–50 % and 50–200 %) with a long-term reusability, low-hysteresis, and fast response under dynamic loading. This sensor demonstrates excellent mechanical performance in real-time human motion detecting and distinguishing subtle signals, such as vocalization, muscle motions, as well as fingers or wrists. |
| Databáze: | OpenAIRE |
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