A high-performance S-TENG based on the synergistic effect of keratin and calcium chloride for finger activity tracking

作者：Zhang, Shuai; Meng, Shuo; Zhang, Ke; Wang, Zhuang; Xu, Xiaoyun; Zhi, Chuanwei; Shi, Shuo; Hu, Jinlian^*

来源：Nano Energy, 2023, 112: 108443.

DOI：10.1016/j.nanoen.2023.108443

• S-TENG
• DFT
• Keratin
• Calcium chloride
• Shape recognition
• Machine learning

Triboelectric nanogenerator (TENG) is one of the key research directions for future human-computer interaction (HCI), biomedicine, and environmental protection. Bio-based materials are an essential branch of many degradable materials. Keratin has attracted much attention due to its advantages of easy access, biodegradability, and good biocompatibility. A highly sensitive single-electrode TENG (S-TENG) based on CaCl2/PVA/keratin and Ecoflex with micro-domes is designed. The excellent stability (18,000 cycles) and stretchability (200%) of the sensor are confirmed by research. Moreover, the presence of CaCl2 and keratin can significantly increase the STENG's output voltage, and the reason is also explored by the density functional theory (DFT) method. Through simulation, it is found that the decrease of the HOMO (highest occupied molecular orbital)-LUMO (lowest unoccupied molecular orbital) gap and the increase of the electrostatic potential are the root causes of the voltage increase. Relying on the excellent characteristics of the S-TENG, finger curvatures, gestures, and object shapes are recognized. Among them, the accuracy of object shape recognition by machine learning algorithm reached 98.1%. This study provides a new method for improving the output efficiency and prolonging the service life of STENG and confirms the feasibility of the electron cloud trap model to explain biomass triboelectric materials by keratin and CaCl2.