Self-healing electronic skin with high fracture strength and toughness
Abstract Human skin is essential for perception, encompassing haptic, thermal, proprioceptive, and pain-sensing functions through ion movement. Additionally, it is mechanically resilient and self-healing for protection. Inspired by these unique properties, researchers have attempted to develop stret...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2024-11-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-024-53957-0 |
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| Summary: | Abstract Human skin is essential for perception, encompassing haptic, thermal, proprioceptive, and pain-sensing functions through ion movement. Additionally, it is mechanically resilient and self-healing for protection. Inspired by these unique properties, researchers have attempted to develop stretchable, self-healing sensors based on ion dynamics. However, most self-healing sensors reported to date suffer from low fracture strength and toughness. In this work, we present an ion-based self-healing electronic skin with exceptionally high fracture strength and toughness. We enhanced self-healing polymers and ionic conductors by introducing two types of orthogonal dynamic crosslinking bonds: dynamic aromatic disulfide bonds and 2-ureido-4-pyrimidone moieties. These dynamic bonds provide autonomous self-healing and high mechanical toughness even in the presence of ionic liquids. As a result, our self-healing polymer and self-healing ionic conductor exhibit remarkable stretchability (700%, 850%), fracture strength (34 MPa, 30 MPa), and toughness (78.5 MJ/m3, 87.3 MJ/m3), the highest values reported among self-healing ionic conductors to date. Using our materials, we developed various fully self-healing sensors and a soft gripper capable of autonomously recovering from mechanical damage. By integrating these components, we created a comprehensive self-healing electronic skin suitable for soft robotics applications. |
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| ISSN: | 2041-1723 |