South Korean researchers develop self-healing hydrogel for energy harvesting and sensing

A joint research team from Myongji University and Sungkyunkwan University has developed an innovative self-healing hydrogel-based triboelectric nanogenerator. This technology harnesses triboelectricity, a form of energy generated by friction between different materials, and integrates it with a self-healing hydrogel capable of adapting its shape. The system also functions as a tactile sensor.

The research focused on developing an organic hydrogel using polyacrylamide-polyethylenimine (PAAm-PEI) in a glycerol-water binary solvent system. The team systematically analyzed the impact of various alkali metal salts and alkaline earth metal salts on the triboelectric performance. Their findings revealed that organic hydrogels with added lithium chloride (LiCl) achieved an output voltage of approximately 400V and a high strain tolerance of up to 3000%.

Furthermore, the developed hydrogel exhibited an 87% transparency and excellent anti-freezing properties. This is attributed to lithium ions forming strong hydrogen bonds and ionic interactions with water, effectively suppressing ice crystal formation and minimizing moisture loss. The hydrogel-based triboelectric nanogenerator maintained 91.4% and 80% of its initial output after exposure to 60°C and -20°C environments, respectively.

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This study presents an effective design strategy to simultaneously achieve ionic conductivity, mechanical flexibility, and optical transparency in hydrogel-based triboelectric materials.

Notably, the material demonstrated a remarkable self-healing capability, recovering 85% of its initial voltage within 10 seconds of sustaining damage. The research team also utilized the triboelectric nanogenerator as a self-powered sensor to detect various human movements when attached to a finger. By integrating a hybrid CNN-LSTM deep learning model, they achieved a high classification accuracy of 95.64% in Morse code recognition, showcasing reliable intelligent sensing capabilities.

Professor Park Yong-tae, the lead researcher, stated, "This study presents an effective design strategy to simultaneously achieve ionic conductivity, mechanical flexibility, and optical transparency in hydrogel-based triboelectric materials." He anticipates broad applications in next-generation wearable electronics and advanced human-machine interfaces when combined with deep learning technology. The research was published in the journal Advanced Functional Materials.

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With the integration of deep learning technology, it is expected to be widely used in next-generation wearable electronics and advanced human-machine interface fields.