Dynamic Ionic Double-Network Hydrogels of Agricultural Lignin/Zwitterionic Starch via 3D Printing for a Rapid-Rebound and Real-Time Feedback Flexible Sensor

Abstract Agricultural biomass hydrogels are environmentally friendly candidates for flexible sensors, yet their application in advanced AI devices is restricted by persistent trade-offs among mechanical strength, tensile performance, and sensitivity. Lignin can strengthen hydrogels benefiting flexible sensing, but its steric hindrance lowers photocuring cross-linking density, triggering mechanical hysteresis and slow rebound under dynamic deformation, which deteriorates sensing signal reliability. Herein, we develop a vat photopolymerization (VPP) 3D-printed double-network elastomer. Modified lignosulfonate (UALS) and cationic DMAEA-Q form a covalent primary network; electrostatic interactions between zwitterionic starch, UALS sulfonate, and DMAEA-Q ammonium groups together with intermolecular hydrogen bonds construct the secondary network. Such interpenetrating architecture elevates cross-linking density, delivering energy dissipation ≤13.3%, residual strain ≤5.8% after 10,000 compression cycles, and a rapid response ≤62.63 ms. The 3 × 3 pressure sensor matrix accurately manipulates bionic hands, demonstrating great prospects for human-machine interaction.