Laser-Induced Skin-like Flexible Pressure Sensor for Artificial Intelligence Speech Recognition

Area of Science:

• Materials Science
• Nanotechnology
• Sensor Technology

Background:

• Development of skin-like flexible pressure sensors is hindered by complex, costly, and inefficient preparation methods.
• Existing sensors often lack the required sensitivity, response time, or stability for practical applications.

Purpose of the Study:

• To propose a simple, low-cost, and efficient laser-induced forming process for preparing skin-like flexible piezoresistive sensors.
• To investigate the sensing performance and potential applications of the developed sensors.

Main Methods:

• Utilized infrared laser irradiation on a glucose/graphene/polydimethylsiloxane (PDMS) prepolymer film.
• Leveraged photothermal effect of graphene and foaming effect of glucose to create a porous, skin-like PDMS film with surface protrusions.
• Fabricated flexible piezoresistive sensors using the prepared skin-like PDMS film with an integrated graphene conductive layer.

Main Results:

• Achieved ultrahigh sensitivity (1348 kPa⁻¹) within a 0-2 kPa range, a wide operating range (200 kPa), and rapid response/recovery times (52 ms/35 ms).
• Demonstrated excellent stability over 5000 cycles.
• Successfully applied the sensor for human pulse detection and robot clamping force measurement.
• Achieved 95% accuracy in speech recognition when combined with a Convolutional Neural Network (CNN) algorithm.

Conclusions:

• The laser-induced forming process offers an efficient and scalable method for producing advanced flexible sensors.
• The developed skin-like flexible piezoresistive sensor exhibits superior performance, indicating significant potential for health monitoring, soft robotics, and intelligent wearable electronics.