A High-Sensitivity, Fast-Response Sawtooth-Structured Flexible Pressure Sensor Based on MWCNTs/Rubber Composites for Machine Learning-Assisted Recognition

Flexible piezoresistive pressure sensors demonstrate extensive application prospects in fields such as human-computer interaction, wearable electronics, and intelligent detection. Although pressure sensors have made significant advancements in sensitivity and detection range, the contradiction between high sensitivity and a wide detection range remains prevalent. The challenge of achieving a wide detection range while maintaining high sensitivity in sensors remains a significant hurdle at the current stage of this field. Inspired by the design of the sawtooth structure (enhancing impact resistance), we proposed a multiwalled carbon nanotubes (MWCNTs)/silicone rubber (SR) composites-based sawtooth structure as a pressure-sensitive layer for flexible sensors. Experimental results show that this sensor achieves an improved sensitivity of 10.612 kPa-1 alongside a detection range of up to 100 kPa, achieving a good balance between high sensitivity and a broad detection range. Furthermore, the sensor exhibits good performance characteristics, including rapid response/recovery times of 25/25 ms and robust durability (1,000 cycles). The functionality of this sensor has been successfully extended to applications such as object weighting, information transmission, and spatial distribution detection. The combination of sensor arrays and machine learning can accurately identify different objects with 100% accuracy. The proposed sensor design not only presents strategies for addressing the conflict between high sensitivity and a wide detection range but also provides support for promising advancements in the fields of pressure distribution monitoring and intelligent identification.