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Scientists Design Microfluidic Flexible Strain Sensor Based on Wave-patterned Liquid Metal

Jun 04, 2020

Flexible strain sensors have been widely used in wearable electronic devices to capture body physical parameters. However, regardless of the stretchability of sensing material, the resolution of small strain changes, or the hysteresis between loading/unloading states, has always limited the various applications of these sensors. 

A research team led by Prof. LI Hui and Prof. WANG Lei from the Shenzhen Institutes of Advanced Technology (SIAT) of the Chinese Academy of Sciences has developed a microfluidic flexible strain sensor by introducing liquid metal eutectic gallium indium (EGaIn) embedded into wave-shaped microchannel elastomeric matrix.

The novel wave-shaped design of the microchannels reduced the viscoelasticity, increased deformation recovery capability, and improved the hysteresis either. 

This flexible strain sensor could withstand a strain up to 320%. The hysteresis performance was also improved from 6.79% to 1.02% by the wave-patterned structure, which could restrain the viscoelasticity of elastomer effectively.  

Moreover, an enhanced wave-shaped strain sensor was fabricated by increasing the length of microfluidic channel. It showed highly sensitivity and resolution, and a strain change even as low as 0.09% could be detected, which was capable of resolving microdeformation. Besides, the enhanced wave-shaped strain sensor exhibited quick response time of 116ms. 

A series of key indicators demonstrated that the enhanced wave-shaped strain sensor had excellent mechanical compliance, making it promising for wearable electronic, motion recognition, healthcare and soft robotics.

The study was published in ACS Applied Materials & Interfaces.  

 

The images of enhanced wave-shaped strain sensor (Image by SIAT)

Contact

ZHANG Xiaomin

Shenzhen Institutes of Advanced Technology

E-mail:

Superelastic, Sensitive, and Low Hysteresis Flexible Strain Sensor Based on Wave-Patterned Liquid Metal for Human Activity Monitoring

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