Sodium–Alginate\nComposite Nanofiber-Based Triboelectric\nSensor for Self-Powered Wrist Posture Identification

Based on the rapid development of the Internet of Things\nand the\ndemand for self-powered sensors, triboelectric nanogenerators can\nprovide an efficient and environmentally friendly solution. Therefore,\ndeveloping high-performance and sustainable material-based TENGs is\na recent key point to achieve low-carbon society. Herein, we explore\npolyacrylonitrile (PAN)/sodium–alginate composite nanofiber\nfilms as an enhancement tribo-positive material. The PAN/sodium–alginate\ntriboelectric nanogenerator (PS–TENG) assembled from this tribo-positive\nmaterial is boosted several times to a pure PAN nanofiber film. In\naddition, the PS–TENG exhibits an excellent signal-to-noise\nratio of 66.384 dB, fast response time of 7 ms, and high sensitivity\nof 22.655 ± 0.78 V/kPa, which shows significant improvement over\nprevious studies using similar materials or configurations. Therefore,\nwe have developed an intelligent sensing system by using an array\nof four triboelectric sensors and the signal acquisition device of\nan STM32. Under the combination of K-means and SVM machine learning,\nthe average accuracy of recognizing 12 wrist postures can reach 95.18%.\nOur study not only introduces an innovative approach for creating\nhighly sensitive triboelectric sensors but also provides a significant\nway to design a self-powered sensing unit in the Internet of Things.