Multi-bioinspired electronic skins with on-demand adhesion and opto-electronic synergistic display capabilities
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Public summary
• The bioinspired flexible opto-electronic skin (OE-skin) mimics organism nano-micro structures.
• The OE-skin enables NIR-controlled on-demand adhesion with safe robustness at biological interfaces.
• Validated across cellular to organism levels, it ensures biocompatibility for prolonged wearable use.
• The OE-skin achieves in vivo multimodal signal acquisition, decoupling dual physiological signals.
• The OE-skin integrates microelectronics and AI for physiological monitoring and human-computer interactions.
Abstract
Flexible electronic skins hold great promise for biomedical applications, although challenges remain in achieving controllable interactions with the biological interface and accurate signal collection. Inspired by octopuses and chameleons, we propose a novel electronic skin paradigm with on-demand adhesion and opto-electronic synergistic display capabilities. Our electronic skins are composed of a stretchable polyurethane (PU) inverse opal film integrated with a carbon nanotube (CNT)-hybridized polyacrylamide (PAAm)-gelatin double-network-hydrogel conductive flexible substrate and a temperature-responsive poly(N-isopropylacrylamide) (PNIPAm) octopus-inspired hemispherical adhesive array. The device’s CNT hybrid double-network provides robust and sensitive monitoring of temperature and motion. Meanwhile, its flexible PU layer with an inverse opal structure allows for visual motion color sensing. Integrated neural network processing ensures accurate, wide-range, and independent multimodal display. Additionally, the integration of the photothermal effect of CNTs and the temperature-sensitive octopus-inspired PNIPAm adhesive array enables on-demand adhesion. The sensing and adhesion demonstrations ex vivo and in vivo showcase the proposed flexible electronic skin’s inspirational design and functional utilities. The potential applications of such a versatile device are vast, ranging from healthcare to human-machine interactions.
