Journal
ACS APPLIED MATERIALS & INTERFACES
Volume -, Issue -, Pages -Publisher
AMER CHEMICAL SOC
DOI: 10.1021/acsami.2c17904
Keywords
MXene; hydrogel; triboelectric nanogenerator; human-computer interaction; object recognition
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In this study, an ionic hydrogel (PTSM) was developed for wearable electronic devices and virtual reality technology. The hydrogel showed excellent stretchability, adhesion, and self-healing due to the multiple weak H-bonds. The addition of MXene nanosheets resulted in a high gauge factor for the hydrogel sensor and improved energy harvesting efficiency for triboelectric nanogenerators (PTSM-TENGs). A glove-based human-computer interaction (HMI) system was created using PTSM-TENGs, enabling gesture visualization and robot hand control. The system also demonstrated potential for object recognition through triboelectric signals and machine learning techniques.
The rapid development of wearable electronic devices and virtual reality technology has revived interest in flexible sensing and control devices. Here, we report an ionic hydrogel (PTSM) prepared from polypropylene amine (PAM), tannic acid (TA), sodium alginate (SA), and MXene. Based on the multiple weak H-bonds, this hydrogel exhibits excellent stretchability (strain >4600%), adhesion, and self-healing. The introduction of MXene nanosheets endows the hydrogel sensor with a high gauge factor (GF) of 6.6. Meanwhile, it also enables triboelectric nanogenerators (PTSM-TENGs) fabricated from silicone rubber-encapsulated hydrogels to have excellent energy harvesting efficiency, with an instantaneous output power density of 54.24 mW/m2. We build a glove-based human-computer interaction (HMI) system using PTSMTENGs. The multidimensional signal features of PTSM-TENG are extracted and analyzed by the HMI system, and the functions of gesture visualization and robot hand control are realized. In addition, triboelectric signals can be used for object recognition with the help of machine learning techniques. The glove based on PTSM-TENG achieves the classification and recognition of five objects through contact, with an accuracy rate of 98.7%. Therefore, strain sensors and triboelectric nanogenerators based on hydrogels have broad application prospects in man-machine interface, intelligent recognition systems, auxiliary control systems, and other fields due to their excellent stretchable and high self-healing performance.
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