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Shenzhen Advanced Institute developed high-performance microfluidic flexible strain sensor
[ Instrument network instrument research and development ] Recently, the team of Wang Lei, a researcher at the Minimally Invasive Center of the Institute of Medical Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, and Li Hui, an associate researcher, are using wave-shaped micro-channel design to improve the hysteresis and response time of liquid metal-based flexible strain sensors. And the research on sensitivity has made new progress. The related research results are titled Superelastic, Sensitive, and Low Hysteresis Flexible Strain Sensor Based on Wave-Patterned Liquid Metal for Human Activity Monitoring, published on ACS Applied Materials & Interfaces.
Flexible strain sensors have become an important research direction in the development of smart devices in the future, and have broad application prospects in the fields of human-computer interaction, electronic skin, and motion monitoring. At present, flexible strain sensors have been widely used in wearable electronic devices to obtain physical parameters of the human body, but regardless of the stretchability of the sensing material, the resolution of small strain changes is insufficient or the hysteresis between the loading/unloading states, The various applications of these sensors are limited. Based on this, the medical microsystem team of the Minimally Invasive Center of Shenzhen Advanced Institute has developed a microfluidic flexible strain sensor by embedding liquid metal eutectic gallium indium (EGaIn) into a wave-shaped micro-channel flexible substrate. Its new wave-shaped design suppresses The viscoelasticity of the microchannel is improved, the deformation recovery ability is improved, and the hysteresis and response speed are improved.
The flexible strain sensor can withstand up to 320% strain and can work normally. The wave-shaped structure can effectively inhibit the viscoelasticity of the microchannel, and the hysteresis is increased from 6.79% to 1.02%. In addition, by extending the length of the wave-shaped microchannel, while the sensitivity (GF=4.91) and resolution of the sensor are improved, it can detect very small strain changes as low as 0.09%, and the response time is as low as 116ms. Experiments verify that the flexible strain sensor can be used for human and robot motion monitoring, such as the different motion states of fingers, neck, breathing chest cavity and robot joints, etc. It has applications in the fields of wearable electronics, motion recognition, medical health and software robots prospect.
Li Hui is the corresponding author of the paper, and research assistant Chen Jing is the first author of the paper. The research work is supported by the key research and development plan of the Ministry of Science and Technology, the National Natural Science Foundation of China, the Guangdong Provincial Natural Science Fund and the Shenzhen Basic Research.
Figure 1. Comparison of response curves of linear microchannel sensor and wave-shaped microchannel sensor. (a, c) The relative resistance of linear strain sensor and (b, d) wave-shaped strain sensor under longitudinal and lateral load respectively; (e) linear strain sensor and wave-shaped strain sensor structure; (f) straight line The response curve changes of type strain sensor and wave-shaped strain sensor in continuous distributed loading experiment.
Figure 2. (a) Enhanced wave-shaped microfluidic strain sensor structure. (b) The enhanced wave-shaped microfluidic strain sensor shows good conformability, flexibility and bendability.
Figure 3. The enhanced wave-shaped strain sensor is used as a wearable device to monitor the motion status of the human body and robot in real time. (a) The signal response when the human finger is bent/stretched; (b) The relative change of the signal when grasping objects of different sizes with the sensor attached to the finger (1) Beaker (2) Plastic cup (3) Ballpoint pen; (c) The output signal changes of the enhanced wave-shaped sensor under the dynamic cyclic loading of human neck bending and (d) chest breathing. (e) The response curve of the flexible sensor integrated on the robot's motion joints with different motion states of the robot.