摘要
Ionogels have emerged as highly promising materials for flexible electronic skin (e-skin) due to their exceptional electrical conductivity, high stability, and biocompatibility. Nevertheless, reconciling breathability with skin conformability while maintaining mechanical integrity remains a critical challenge in the development of ionogels. Herein, a hydrogen bonding and ion-dipole synergy strategy is proposed to prepare a nanonet-reinforced ultrathin ionogel film (UIF) with a thickness of only 12 µm, yet exhibiting outstanding multifunctional performance, including a remarkable sensitivity (gauge factor of 2.37), outstanding environmental resilience (−40 to 60 °C), an extensive strain response range (0–483%), and exceptional fatigue resistance. Furthermore, its superior gas permeability (2464.4 g·m −1 ·day −1 ) significantly enhances epidermal breathability, addressing a key limitation of conventional wearable materials. Moreover, when integrated into flexible wearable devices, the UIF ensures optimal skin adherence and user comfort, setting a new benchmark for wearable technology. By leveraging a supervised machine learning algorithm, such as an artificial neural network (ANN), the system achieves an impressive 96.6% accuracy in real-time analysis of human knee motion signals, enabling continuous, high-precision motion tracking. This advanced ionogel not only paves the way for next-generation flexible e-skins with high conformability but also holds great potential in smart medicine and human-machine interaction.
危险品化学品经营许可证(带存储)