Carbon Black/Multi-Walled Carbon Nanotube-Based, Highly Sensitive, Flexible Pressure Sensor

Flexible piezoresistive pressure sensors have prom-ising applications in wearable devices, artificial intelligence, and other fields. However, developing low-cost and high-performance pressure sensors still poses a great challenge. Herein, we utilize low-cost carbon black (CB) and multi-walled carbon nanotubes (MWCNTs) mixed in porous polydimethylsiloxane to assemble a flexible piezoresistive pressure sensor combined with interdigitated electrodes. Simultaneously, the COMSOL Multiphysics simulation analysis was performed to predict the sensing behavior of the pressure sensor, which was verified by experiments; the preparation of the pressure sensor was guided according to the prediction. Additionally, we studied the effects of the mixed conductive filler's weight ratio, the shape of the interdigital electrode, and the line width and spacing of the interdigital electrode on the performance of the sensor. Based on the interaction of the 3D porous structure and the synergistic conductive network of CB/MWCNTs, the prepared pressure sensor exhibits a high sensitivity of 3.57 kPa-1 (similar to 21 kPa), a wide detection range of 0-275 kPa, fast response time (96 ms), fast recovery time (198 ms), good durability (about 3000 cycles), and good flexibility. Moreover, the fabricated sensor can monitor and recognize human activities (such as finger bending and mouse clicking), indicating that it has great potential in flexible wearable devices and other fields. It is worth noting that the preparation process of the entire pressure sensor was simple, low cost, and environmentally friendly, which provides a certain basis for industrial and commercial applications.

Automated summary

In this study, a flexible piezoresistive pressure sensor was developed using low-cost materials. The sensor exhibited high sensitivity, wide detection range, fast response and recovery time, good durability and flexibility. It also had the ability to monitor and recognize human activities, indicating its great potential in wearable devices and other fields. The preparation process of the sensor was simple, low-cost and environmentally friendly, providing a basis for industrial and commercial applications.