Alignment of Fe3O4/CNT electrodes via magnetic blade printing for wireless stress-direction-recognizing strain sensor

标度系数 材料科学 应变计 碳纳米管 磁场 电阻式触摸屏 电容感应 电极 可穿戴计算机 垂直的 拉伤 联轴节(管道) 纳米技术 制作 光电子学 声学 计算机科学 复合材料 电气工程 工程类 几何学 数学 替代医学 量子力学 化学 医学 嵌入式系统 物理化学 病理 内科学 物理
作者
Guangwei Wang,Chenhao Cong,Xianbin Zheng,Hongjiang Li,Fuhao Jiang,X.Y. Wang,Rong Li,Mingliang Jin,Pengfei Zhang,Junru Li,Chuanwei Zhang,SeHyun Kim,Shandong Li,Xinlin Li
出处
期刊:Chemical Engineering Journal [Elsevier BV]
卷期号:474: 145825-145825 被引量:7
标识
DOI:10.1016/j.cej.2023.145825
摘要

Due to the rapidly growing health field, the use of electronic skin for real-time monitoring of human metrics can provide an important basis for the monitoring of human movement patterns. Wearable flexible strain sensors combined with Internet of Things technology (IoT) are the most important units in the electronic skin. However, most current resistive strain sensors have the same response to strain from all directions, and practical applications are usually limited by a single sensing function. In the present study, a method for the synthesis of Fe3O4/ carbon nanotube (CNT) nanocomposites has been proposed using ultrasound catalysis. In addition, we present for the first time a printing method in which the coupling of an applied magnetic field and the internal friction of a high-viscosity ink acts in such a way as to promote CNT alignment consistency, which will be referred to as magnetic blade printing in this paper. The parallel alignment of CNT during the electrode preparation has then been optimized, which is here referred to as magnetic blading. The difference in sensitivity between parallel and perpendicular directions in the magnetically bladed electrodes became as large as 300%, and the resulting multifunctional sensor was able to detect both weak and large deformations. Thereby, the sensor showed the Gauge Factor of 25.9 and 0.56 in the strain range of 0–3.2 % and 5.8–17.4 %, respectively. A strain angle recognition was achieved by using the specific response of parallel arranged CNT to strain, which was based on the detection of the human joint motion and the recognition of acoustic signals. The real-time monitoring of the data was realized by a 4G transmission module, which provided a reference for the development of remote wireless tracking for human health monitoring.
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