摘要
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 CaCl 2 /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 CaCl 2 and keratin can significantly increase the S-TENG'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 S-TENG and confirms the feasibility of the electron cloud trap model to explain biomass triboelectric materials by keratin and CaCl 2 .
危险品化学品经营许可证(带存储)