期刊
JOURNAL OF MATERIALS CHEMISTRY B
卷 9, 期 13, 页码 3088-3096出版社
ROYAL SOC CHEMISTRY
DOI: 10.1039/d1tb00082a
关键词
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资金
- National Natural Science Foundation of China [NSFC 21374014]
- Fundamental Research Funds for the Central Universities [DUT18RC(3)079]
- MOST innovation team in key areas [2018RA4002]
In this study, a strain sensor composed of PVA/PAA hybrid hydrogel sandwiched between two graphene layers was successfully developed, demonstrating high sensitivity and self-healing properties, with stable performance even at low temperatures. The sensor exhibited a very high GF value at 50% strain, showing potential for intelligent wearable electronic devices in real-time monitoring.
Hydrogels with specially designed structures and adjustable properties have been considered as smart materials with multi-purpose application prospects, especially in the field of flexible sensors. However, most hydrogel-based sensors have low sensitivity, which inevitably affects their promotion in the market. Herein, a strain sensor comprising a poly(vinyl alcohol)/poly(acrylic acid) (PVA/PAA) hybrid hydrogel sandwiched between two graphene layers was successfully constructed in a facile way, and it exhibited many excellent properties including extremely high sensitivity. The incorporation of glycerol ensured the good flexibility and anti-freezing performance of the hydrogel-based sensor even at -15 degrees C. The dynamic coordination bonds in the hydrogel-based sensor endowed it with excellent self-healing properties. In particular, the sandwich-structured hydrogel sensor showed a very high gauge factor (GF) value of 39 at the strain of 50%, which is much higher than those of most ordinary hydrogel-based strain sensors. A super stable signal value after 5000 strain cycles and a very short response time of 274 ms guaranteed the long-term usability and sensitivity of the hydrogel-based sandwich sensor. More importantly, the hydrogel-based sandwich sensor could detect both large and tiny human motions accurately and instantly in a series of real-time monitoring experiments, showing great potential for intelligent wearable electronic devices.
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