Fatigue-resistant, self-healing and antibacterial poly(ionic liquid) gel multichannel sensors for underwater early warning and deep learning-assisted infant monitoring

Xiaoli Liang, Longzhang Niu, Jinhan Song, Zhoujing Chen, Hongwang Qu, Didi Wen, Yuqi Li, Lina Niu, Yongkang Bai,
Fatigue-resistant, self-healing and antibacterial poly(ionic liquid) gel multichannel sensors for underwater early warning and deep learning-assisted infant monitoring,
Chemical Engineering Journal,
Volume 526,
2025,
170881,
ISSN 1385-8947,
https://doi.org/10.1016/j.cej.2025.170881.
(https://www.sciencedirect.com/science/article/pii/S1385894725117269)
Abstract: Flexible sensors are increasingly vital for next-generation wearable electronics, yet conventional materials such as hydrogels and ionogels often suffer from freezing, evaporation, and liquid leakage, limiting their reliability in complex environmental conditions. In this study, a poly(ionic liquid) (PIL) gel was successfully synthesized via the polymerization of 1-vinyl-3-butylimidazolium hexafluorophosphate (BVIM-PF₆) in 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide (EMIM-TFSI). The resulting gel synergistically combines the advantageous properties of ionic liquids with the three-dimensional porous structure of a gel matrix, exhibiting excellent ionic liquid retention capability. Benefiting from abundant intrinsic electrostatic interactions and hydrogen bonding, this PIL gel demonstrates excellent tensile strain (~270.7 %), notable fatigue resistance, and self-healing capability. Additionally, owing to the inherent antimicrobial properties of the ionic liquid, the gel also exhibits significant antibacterial efficacy. A strain sensor fabricated from this PIL gel shows real-time, rapid, and stable sensing performance, with a gauge factor (GF) of 6.20 and a response time of 318 ms. Moreover, a triboelectric nanogenerator (TENG) assembled using the PIL gel demonstrates outstanding energy-harvesting performance. Operating as a self-powered sensor integrated with deep learning algorithms, it enables smart infant monitoring and early hazard prediction. This work highlights the significant potential of PIL gels as advanced materials for next-generation flexible sensors.
Keywords: Poly(ionic liquid); Strain sensor; Triboelectric nanogenerator; Self-powered; Deep learning