Sustainable and high performance MXene hydrogel with interlocked structure for machine learning-facilitated human-interactive sensing

Abstract

Wearable epidermal electronics fabricated from MXene-based conductive hydrogels have attracted considerable interest because of their promising prospects in real-time health monitoring and human–computer interaction sensing. However, the development of a sustainable hydrogel with exceptional mechanical toughness, high conductivity, and self-adhesion is crucial to reliably capture signals through polymer network designs that establish robust interactions between MXene nanosheets and network substrates while minimizing electronic waste generated by discarded sensors. This study presents the fabrication of a sustainable conductive MXene-based dual-network hydrogel through skillful assembly of MXene nanosheets, β-cyclodextrin with azobenzene-modified polyacrylic acid chains, and poly (vinyl alcohol) polymer networks. The hydrogel demonstrates exceptional mechanical properties (strength at breaking ∼ 625 kPa, elongation at break ∼ 630 %) attributed to the presence of numerous hydrogen bonds and host–guest interactions, along with superior electrical conductivity (23.65 S/cm) and self-adhesion. The hydrogel demonstrates exceptional sensitivity across a wide range of strains, enabling the detection of various human movements and achieving successful applications in handwriting recognition and sign language translation. Under acidic condition and UV irradiation, the disassembly of AZO and β-CD as well as the untangling of PVA chains entanglement facilitate the release and recycling of MXene. This study presents a technological platform that holds promise for developing conductive hydrogels with enhanced sensing capabilities, catering to the requirements of stretchable electronic skin and intelligent robotic systems.