Wearable Strain Sensors Based on a Porous Polydimethylsiloxane Hybrid with Carbon Nanotubes and Graphene

High-performance flexible strain sensors are urgently needed with the rapid development of wearable intelligent electronics. Here, a bifiller of carbon nanotubes (CNTs) and graphene (GR) for filling flexible porous polydimethylsiloxane (CNT-GR/PDMS) nanocomposites is designed and prepared for strain-sensing applications. The typical microporous structure was successfully constructed using the Soxhlet extraction technique, and the connected CNTs and GR constructed a perfect three-dimensional conductive network in the porous skeleton. As a result, the stretchability and sensitivity of the CNT-GR/PDMS-based strain sensors were well regulated based on the porous structure and the typical synergistic conductive network. Based on the destruction effect of the brittle synergistic conductive network located in the outer and inner layers of the cell skeleton and the contact effect between adjacent cells in different strain ranges, the prepared CNTs-GR/PDMS-based strain sensor exhibited superior gauge factors of 182.5, 45.6, 70.2, and 186.5 in the 0-3, 3-57, 57-90, and 90-120% strain regions, respectively. In addition, this material also exhibited an ultralow detection limit (0.5% strain), a fast response time (60 ms), good stability and durability (10,000 cycles), and frequency-/strain-dependent sensing performances, making it active for the detection of various external environments. Finally, the prepared porous CNTs-GR/PDMS-based strain sensor was attached to the skin to detect various human motions, such as wrist bending, finger bending, elbow bending, and knee bending, thereby demonstrating wide application prospects in smart wearable devices.

Automated summary

A high-performance flexible strain sensor based on CNT-GR/PDMS nanocomposites was designed and prepared. The sensor exhibited superior gauge factors, ultralow detection limit, fast response time, good stability and durability, and frequency-/strain-dependent sensing performances. It showed wide application prospects in smart wearable devices for detecting various human motions.