A highly linear stretchable MXene-based biocompatible hydrogel–elastomer hybrid with tissue-level softness

Maintaining low modulus while endowing the wide-range linear stretchability to wearable or implantable devices is crucial for these devices to reduce the mechanical mismatch between the devices and human skin/tissue interfaces. However, improving linear stretchability often results in an increased m...

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Veröffentlicht in:Science China materials 2024-10, Vol.67 (10), p.3368-3378
Hauptverfasser: Wan, Shu, Huang, Haizhou, He, Zisheng, Ye, Yizhou, Li, Shen, Su, Shi, Shen, Jiaxin, Han, Longxiang, Wan, Peng, Ran, Xu, Chen, Li, He, Xuefeng, Sun, Litao, Bi, Hengchang
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Sprache:eng
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Zusammenfassung:Maintaining low modulus while endowing the wide-range linear stretchability to wearable or implantable devices is crucial for these devices to reduce the mechanical mismatch between the devices and human skin/tissue interfaces. However, improving linear stretchability often results in an increased modulus of stretchable electronic materials, which hinders their conformability in long-term quantifiable monitoring of organs. Herein, we develop a hybrid structure involving interlocking low-modulus porous elastomers (Ecoflex-0030) and MXene-based hydrogels with crosslinking networks of polyvinyl alcohol, sodium alginate, and MXene. This hydrogel–elastomer structure exhibits superior performance compared with previous reports, with a wide linear stretchability strain range from 0 to 1000% and maintaining a low modulus of 6.4 kPa. Moreover, the hydrogel–elastomer hybrids can be utilized as highly sensitive strain sensors with remarkable characteristics, including high sensitivity (gauge factor ∼3.52), a linear correlation between the resistance and strain (0–200%), rapid response (0.18 s) and recovery times (0.21 s), and excellent electrical reproducibility (1000 loading–unloading cycles). Those electrical and mechanical properties allow the sensor to act as a suitable quantifiable equipment in organ monitoring, human activities detecting, and human–machine interactions.
ISSN:2095-8226
2199-4501
DOI:10.1007/s40843-024-2985-8