A flexible triboelectric nanogenerator with MXene paste as conductive layer for smart sensing

MXene-fabric TENG shows linear response to twist, fold, stretch for sensing. • TENG detect pressure down to 0.27 Pa for blinking, facial, swallowing monitoring. • TENG is integrated for real-time wrist monitoring and joint injury prevention. Herein, a Triboelectric Nanogenerator (TENG) was constructed as flexible self-powered sensors with excellent performance for smart sensing. Ti 3 C 2 MXene paste is directly coated on the surface of cotton fabric as conductive layers of the TENG. The conductive layer is encapsulated by silicone rubber films, which also work as triboelectric layers of the TENG. The sensor shows an excellent linear response to stretching, twisting and folding deformation, demonstrating its capability for quantitative deformation measurement without external power supply. More importantly, the sensor possesses ultra-low-pressure detection capability (as low as 0.27 Pa), and thus can accurately recognize physiological activities such as blinking, facial micro-expressions, and swallowing with high sensitivity. Furthermore, it was integrated into a human–computer interaction system as a complete measurement and instrumentation platform, to monitor wrist movement during dumbbell training in real-time and provide feedback on the correctness of the movement to reduce the risk of joint injury. This study provides a low-cost, simple, and highly sensitive solution for smart wearable devices with well-defined input–output relationship and stable dynamic response, offering important applications in sports health monitoring, joint protection, and flexible self-powered measurement systems. In this paper, a flexible self-powered sensor based on a Triboelectric Nanogenerator (TENG) was designed by spin-coating MXene paste as conductive layers. The sensor exhibits excellent linear responses to twisting, folding, stretching, as well as an ultra-low pressure detection limit of 0.27 Pa. It accurately detects physiological activities such as blinking and swallowing and is integrated into a human–computer interaction system to monitor wrist movements during dumbbell training for joint protection. This work presents a low-cost, sensitive wearable sensor with well-defined input–output relationship for self-powered measurement systems. Download: Download high-res image (114KB) Download: Download full-size image