Dual-Responsive Starch Hydrogels via Physicochemical Crosslinking for Wearable Pressure and Ultra-Sensitive Humidity Sensing
Zi Li, Jinhui Zhu, Zixuan Wang, Hao Hu, Tian Zhang
- Year
- 2025
- Citations
- 2
- Access
- Open access
Abstract
Flexible hydrogel sensors demonstrate emerging applications, such as wearable electronics, soft robots, and humidity smart devices, but their further application is limited due to their single-responsive behavior and unstable, low-sensitivity signal output. This study develops a dual-responsive starch-based conductive hydrogel via a facile “one-pot” strategy, achieving mechanically robust pressure sensing and ultra-sensitive humidity detection. The starch-Poly (2,3-dihydrothieno-1,4-dioxin)-poly (styrenesulfonate) (PEDOT:PSS)-glutaraldehyde (SPG) hydrogel integrates physical entanglement and covalent crosslinking to form a porous dual-network architecture, exhibiting high compressive fracture stress (266 kPa), and stable electromechanical sensitivity (ΔI/I0, ~2.3) with rapid response (0.1 s). In its dried state (D-SPG), the film leverages the starch’s hygroscopicity for humidity sensing, detecting minute moisture changes (ΔRH = 6.6%) within 120 ms and outputting 0.4~0.5 (ΔI/I0) signal amplitudes. The distinct state-dependent responsiveness enables tailored applications: SPG monitors physiological motions (e.g., pulse waves and joint movements) via conformal skin attachment, while D-SPG integrated into masks quantifies respiratory intensity with 3× signal enhancement during exercise. This work pioneers a sustainable candidate for biodegradable flexible electronics, overcoming trade-off limitations between mechanical integrity, signal stability, and dual responsiveness in starch hydrogels through synergistic network design.
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
Genetic Programming: On the Programming of Computers by Means of Natural Selection
John R. Koza
1992