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Innervate Commercial Fabrics with Spirally-Layered Iontronic Fibrous Sensors Toward Dual-Functional Smart Garments.
Wu, Xiaodong; Liu, Qi; Zheng, Lifei; Lin, Sijian; Zhang, Yiqun; Song, Yangyang; Wang, Zhuqing.
Affiliation
  • Wu X; School of Mechanical Engineering, Sichuan University, Chengdu, 610065, China.
  • Liu Q; School of Mechanical Engineering, Sichuan University, Chengdu, 610065, China.
  • Zheng L; School of Mechanical Engineering, Sichuan University, Chengdu, 610065, China.
  • Lin S; School of Mechanical Engineering, Sichuan University, Chengdu, 610065, China.
  • Zhang Y; School of Mechanical Engineering, Sichuan University, Chengdu, 610065, China.
  • Song Y; School of Mechanical Engineering, Sichuan University, Chengdu, 610065, China.
  • Wang Z; School of Mechanical Engineering, Sichuan University, Chengdu, 610065, China.
Adv Sci (Weinh) ; 11(33): e2402767, 2024 Sep.
Article in En | MEDLINE | ID: mdl-38953387
ABSTRACT
Electronic fabrics exhibit desirable breathability, wearing comfort, and easy integration with garments. However, surficial deposition of electronically functional materials/compounds onto fabric substrates would consequentially alter their intrinsic properties (e.g., softness, permeability, biocompatibility, etc.). To address this issue, here, a strategy to innervate arbitrary commercial fabrics with unique spirally-layered iontronic fibrous (SLIF) sensors is presented to realize both mechanical and thermal sensing functionalities without sacrificing the intrinsic fabric properties. The mechanical sensing function is realized via mechanically regulating the interfacial ionic supercapacitance between two perpendicular SLIF sensors, while the thermal sensing function is achieved based on thermally modulating the intrinsic ionic impedance in a single SLIF sensor. The resultant SLIF sensor-innervated electronic fabrics exhibit high mechanical sensitivity of 81 N-1, superior thermal sensitivity of 34,400 Ω °C-1, and more importantly, greatly minimized mutual interference between the two sensing functions. As demonstrations, various smart garments are developed for the precise monitoring of diverse human physiological signals. Moreover, artificial intelligence-assisted object recognition with high-accuracy (97.8%) is demonstrated with a SLIF sensor-innervated smart glove. This work opens up a new path toward the facile construction of versatile smart garments for wearable healthcare, human-machine interfaces, and the Internet of Things.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Adv Sci (Weinh) Year: 2024 Document type: Article Affiliation country: China Country of publication: Alemania

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Adv Sci (Weinh) Year: 2024 Document type: Article Affiliation country: China Country of publication: Alemania