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Conductive hydrogels hold great promise for next-generation wearable electronics and intelligent systems due to their ability to combine tissue-like compliance with electronic functionality. While liquid metal particles (LMPs) offer substantial potential for improving hydrogel performance, their tendency to coalesce, stemming from high surface energy and low viscosity, poses a significant challenge to dispersion stability. To overcome this limitation, this work presents a biopolymer-mediated stabilization strategy employing gelatin, whose abundant amino and carboxyl groups form coordination bonds with LMPs, effectively inhibiting their aggregation. The resulting uniformly dispersed LMPs enable rapid, initiator-free polymerization of acrylic acid, yielding hydrogels with outstanding mechanical properties, including high stretchability (> 700%), robust elasticity (46.5 kPa), and excellent fatigue resistance. Furthermore, these gelatin-metal hydrogels (GMHs) exhibit high electrical conductivity (0.15 S·m−1) and pronounced strain sensitivity, with gauge factors of 1.85 and 3.66 for strains below 260% and between 260% and 500%, respectively. This combination of electrical characteristics allows GMHs to function as high-performance biomimetic electronic skins capable of precise and stable human motion monitoring. When integrated with convolutional neural networks (CNNs), the system further enables real-time handwriting recognition. Beyond sensing applications, the GMHs also demonstrate photo-thermal conversion capability, which can be leveraged for electricity generation. Overall, this study establishes a versatile interface-engineering strategy for the design of multifunctional hydrogels, contributing to the development of sustainable and scalable functional hydrogel systems.

This is an open access article under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0, https://creativecommons.org/licenses/by/4.0/).
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