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A Flexible Smart Healthcare Platform Conjugated with Artificial Epidermis Assembled by Three-Dimensionally Conductive MOF Network for Gas and Pressure Sensing.

Authors :
Zhou, Qingqing
Ding, Qihang
Geng, Zixun
Hu, Chencheng
Yang, Long
Kan, Zitong
Dong, Biao
Won, Miae
Song, Hongwei
Xu, Lin
Kim, Jong Seung
Source :
Nano-Micro Letters; 10/25/2024, Vol. 17 Issue 1, p1-20, 20p
Publication Year :
2024

Abstract

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<subscript>3</subscript>(HHTP)<subscript>2</subscript> particles onto the hollow spherical Ti<subscript>3</subscript>C<subscript>2</subscript>T<subscript>x</subscript> surface, aiming to concurrently emulate the spinous and granular layers of the skin's epidermis. The bionic Ti<subscript>3</subscript>C<subscript>2</subscript>T<subscript>x</subscript>@Cu<subscript>3</subscript>(HHTP)<subscript>2</subscript> exhibits independent NO<subscript>2</subscript> 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<subscript>2</subscript> 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<subscript>3</subscript>(HHTP)<subscript>2</subscript> coupled with spherical Ti<subscript>3</subscript>C<subscript>2</subscript>T<subscript>x</subscript>. The bioinspired Ti<subscript>3</subscript>C<subscript>2</subscript>T<subscript>x</subscript>@Cu<subscript>3</subscript>(HHTP)<subscript>2</subscript> sensors can independently perceive NO<subscript>2</subscript> gas and pressure-triggered stimuli. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
23116706
Volume :
17
Issue :
1
Database :
Complementary Index
Journal :
Nano-Micro Letters
Publication Type :
Academic Journal
Accession number :
180654164
Full Text :
https://doi.org/10.1007/s40820-024-01548-5