A Flexible Smart Healthcare Platform Conjugated with Artificial Epidermis Assembled by Three-Dimensionally Conductive MOF Network for Gas and Pressure Sensing - Zhou, Qingqing; Ding, Qihang; Geng, Zixun; Hu, Chencheng; Yang, Long; Kan, Zitong; Dong, Biao; Won, Miae; Song, Hongwei; Xu, Lin; Kim, Jong Seung (Nano-micro letters, 2025)
The rising flexible and intelligent electronics greatly facilitate the noninvasive and timely tracking of physiological information in telemedicine healthcare. Meticulously building bionic-sensitive moieties is vital for designing efficient electronic skin with advanced cognitive functionalities to pluralistically capture external stimuli. However, realistic mimesis, both in the skin’s three-dimensional interlocked hierarchical structures and synchronous encoding multistimuli information capacities, remains a challenging yet vital need for simplifying the design of flexible logic circuits. Herein, we construct an artificial epidermal device by in situ growing Cu 3 (HHTP) 2 particles onto the hollow spherical Ti 3 C 2 T x surface, aiming to concurrently emulate the spinous and granular layers of the skin’s epidermis. The bionic Ti 3 C 2 T x @Cu 3 (HHTP) 2 exhibits independent NO 2 and pressure response, as well as novel functionalities such as acoustic signature perception and Morse code-encrypted message communication. Ultimately, a wearable alarming system with a mobile application terminal is self-developed by integrating the bimodular senor into flexible printed circuits. This system can assess risk factors related with asthmatic, such as stimulation of external NO 2 gas, abnormal expiratory behavior and exertion degrees of fingers, achieving a recognition accuracy of 97.6% as assisted by a machine learning algorithm. Our work provides a feasible routine to develop intelligent multifunctional healthcare equipment for burgeoning transformative telemedicine diagnosis. Highlights A smart wearable alarming system integrated artificial epidermal device for pluralistically identifying asthmatic attack risk factors, achieving a 97.6% classification accuracy as assisted by machine learning algorithm. A meticulous mimicry both in the advanced structural attributes and encoding information abilities of the skin was adopted to design a novel artificial epidermal device by integrating conductive Cu 3 (HHTP) 2 coupled with spherical Ti 3 C 2 T x . The bioinspired Ti 3 C 2 T x @Cu 3 (HHTP) 2 sensors can independently perceive NO 2 gas and pressure-triggered stimuli.