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Highly sensitive, self-powered and wearable electronic skin based on pressure-sensitive nanofiber woven fabric sensor
The wearable electronic skin with high sensitivity and self-power has shown increasing prospects for applications such as human health monitoring, robotic skin, and intelligent electronic products. In this work, we introduced and demonstrated a design of highly sensitive, self-powered, and wearable...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5636882/ https://www.ncbi.nlm.nih.gov/pubmed/29021591 http://dx.doi.org/10.1038/s41598-017-13281-8 |
Sumario: | The wearable electronic skin with high sensitivity and self-power has shown increasing prospects for applications such as human health monitoring, robotic skin, and intelligent electronic products. In this work, we introduced and demonstrated a design of highly sensitive, self-powered, and wearable electronic skin based on a pressure-sensitive nanofiber woven fabric sensor fabricated by weaving PVDF electrospun yarns of nanofibers coated with PEDOT. Particularly, the nanofiber woven fabric sensor with multi-leveled hierarchical structure, which significantly induced the change in contact area under ultra-low load, showed combined superiority of high sensitivity (18.376 kPa(−1), at ~100 Pa), wide pressure range (0.002–10 kPa), fast response time (15 ms) and better durability (7500 cycles). More importantly, an open-circuit voltage signal of the PPNWF pressure sensor was obtained through applying periodic pressure of 10 kPa, and the output open-circuit voltage exhibited a distinct switching behavior to the applied pressure, indicating the wearable nanofiber woven fabric sensor could be self-powered under an applied pressure. Furthermore, we demonstrated the potential application of this wearable nanofiber woven fabric sensor in electronic skin for health monitoring, human motion detection, and muscle tremor detection. |
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