材料科学
弹性体
电介质
常量(计算机编程)
体积模量
弹性模量
复合材料
模数
计算机科学
光电子学
程序设计语言
作者
Wanjiang Li,Shaoji Wu,Qiuman Zhou,Caihong Gong,Zhao Liu,Yurong Yan
标识
DOI:10.1021/acsami.4c06122
摘要
Enhancing the sensitivity of capacitive pressure sensors through microstructure design may compromise the reliability of the device and rely on intricate manufacturing processes. It is an effective way to solve this issue by balancing the intrinsic properties (elastic modulus and dielectric constant) of the dielectric layer materials. Here, we introduce a liquid metal (LM) hybrid elastomer prepared by a chain-extension-free polyurethane (PU) and LM. The synergistic strategies of extender-free and LM doping effectively reduce the elastic modulus (7.6 ± 0.2−2.1 ± 0.3 MPa) and enhance the dielectric constant (5.12−8.17 @1 kHz) of LM hybrid elastomers. Interestingly, the LM hybrid elastomer combines reprocessability, recyclability, and photothermal conversion. The obtained flexible pressure sensor can be used for detecting hand and throat muscle movements, and high-precision speech recognition of seven words has been using a convolutional neural network (CNN) in deep learning. This work provides an idea for designing and manufacturing wearable, recyclable, and intelligent control pressure sensors.
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