Machine Learning Enabled Fluorescent Anti-Freezing Core–Shell Hydrogel Realizing Deep-Sea Morse Code Communication for Human-Machine Interaction Engineering

作者：Yanqi Yin, Tianxiang Gao, Bingchen Zhou, Yan Yu, Xinrui Jia, He Ding, Shili Gai, Piaoping Yang · 发表于：Nano Letters · 年份：2025 · DOI：10.1021/acs.nanolett.5c04651 · 被引用次数：6 · 研究领域：Advanced Sensor and Energy Harvesting Materials、Hydrogels: synthesis, properties, applications、Advanced Materials and Mechanics

Underwater intelligent systems demand flexible materials with robustness, environmental tolerance, and functional integration. Hydrogels, which combine flexibility with conductivity, show promise but often fail under harsh conditions. Herein, an antifreezing, antiswelling hydrogel with core–shell architecture was fabricated by ion concentration gradient modulation. Polyacrylamide/poly(acrylic acid) pregel immersed in Al 3+ solution produced a concentration gradient. The external layer generates a dense metal oxide film, acting as a robust protective armor, while the inner polymer network preserves elasticity. A dynamic cross-linking network endowed the hydrogel with mechanical robustness (561% strain) and fracture strength (0.188 MPa stress), superior frost resistance (−48 °C), and a swift response time (198 ms). Machine learning-enabled Morse code decoding established a nonverbal underwater communication system, enabling remote human–machine interaction and efficient robotic control. The proposed hydrogel-based system achieves integrated “sensing-control-communication” in extreme environments, offering innovative strategies for continuous digital motion monitoring and human–machine interaction.