静电纺丝
可穿戴计算机
对偶(语法数字)
材料科学
双模
干扰(通信)
功能(生物学)
双重功能
光电子学
压力传感器
纳米技术
复合材料
嵌入式系统
计算机科学
机械工程
聚合物
电子工程
电信
工程类
艺术
频道(广播)
文学类
计算机图形学(图像)
轮廓
生物
进化生物学
作者
He Gong,Lingyun Ni,Hang Zhu,Hongli Chao,Lan Luo,Mengchao Chen,Wei Ji,Tianli Hu,Ying Guo,Zhiqiang Cheng,Ye Mu,Xiuling Yu
出处
期刊:Materials horizons
[Royal Society of Chemistry]
日期:2025-01-01
卷期号:12 (17): 6793-6803
被引量:1
摘要
Human skin has the complex function of sensing pressure, strain, friction, temperature, and humidity. Flexible electronic skin (e-skin) plays a key role in advancing intelligent human-computer interaction and wearable health monitoring devices. However, achieving effective integration of multifunctional sensors while minimizing potential interference between them is a significant challenge. In this paper, we use an improved electrostatic spinning layered integration process to fabricate a sandwich-structured CNFs/Al2O3-SiC SBD pressure-temperature dual-mode e-skin, in which the top and bottom layers are composed of the temperature-sensitive material SiC SBD, which also functions as capacitive electrodes, forming a capacitive pressure sensor together with the pressure-sensitive material CNFs/Al2O3 in the middle layer. The experimental results show that the e-skin exhibits good performance in pressure and temperature tests: the response/recovery time of the pressure sensor is 0.52 s/0.53 s in the pressure range of 0-5 kPa, and the sensitivity reaches 0.366 kPa-1 in the range of 0-10 kPa. In the range of 25-50 °C, the response/recovery time of the top layer temperature sensor is 5.12 s/8.97 s, and the sensitivity can reach -1.291 °C-1. In the range of 25-50 °C, the response/recovery time of the bottom layer temperature sensor is 4.96 s/8.92 s, and the sensitivity can reach -1.614 °C-1. In this study, the preparation of CNFs/Al2O3-SiC SBD pressure-temperature dual-mode e-skin is described, which has good repeatability and independent sensing characteristics, unaffected by interference from other conditions. In addition, its excellent flexibility allows it to accurately perceive human movements and physiological signals such as gesture recognition and breath monitoring, while also detecting the spatial distribution of external stimuli, showing widespread application potential in intelligent human-computer interaction and wearable health monitoring devices.
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