Programmable magnetic-induced functional gradient hydrogel for NIR-driven underwater soft robots

Multilayered soft underwater robots achieve superior performance in deep-sea environments through enhanced environmental adaptability and structural dexterity. However, the insufficient interfacial bond strength of conventional multilayer structure designs is often compromised by interface layering and limited drive modes, leading to the interlayer peeling and poor reconfigurability. Here, a novel programmable functional gradient hydrogel is developed based on a magnetic field-guided gradient distribution, the structure-function integrated design of which is achieved by the gradient distribution of Fe₃O₄/polydopamine hybrid nanoparticles (FPHPs) with photo-thermal responsive properties into a temperature-sensitive hydrogel network. This hydrogel effectively avoids interfacial failure issues in traditional multilayer materials due to its seamless gradient structure. Upon 808 nm near-infrared (NIR) irradiation, the localized heating to 59.6 °C underwater creates a temperature gradient, which in turn induces a asymmetric swelling force for actuation. Experimental results demonstrate that the hydrogel can achieve controllable bending deformation of 180° within 5 s while maintaining initial deformation capability after more than 50 deformation cycles. We developed an underwater smart optical sensor utilizing hydrogel deformation to precisely modulate infrared tube exposure area, enabling RGB-LED multicolor tunable display for enhanced deep-sea optical communication. Furthermore, exploiting the programmable magnetization of FPHPs, we constructed various soft robots including an integrated jellyfish-inspired prototype with precisely controlled locomotion. This work advances flexible underwater robotics by solving interfacial stability problems and pioneering hydrogel-based underwater optical sensors, enabling intelligent deep-sea exploration.