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

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<sup>3+</sup> 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.

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Publication Details

Journal
Nano Letters
Published
2025-11-04
DOI
https://doi.org/10.1021/acs.nanolett.5c04651
Citations
2
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
1.35
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article

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

Piaoping Yang, Shili Gai, Tianxiang Gao, Xinrui Jia et al.
2 citations
Nano Letters
Advanced Sensor and Energy Harvesting Materials
1.35
article

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

Piaoping Yang, Shili Gai, Tianxiang Gao, Xinrui Jia, Yanqi Yin, Yan Yu, Bingchen Zhou, He Ding
article en
2 citations

Abstract

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<sup>3+</sup> 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.

Nano LettersVol. 25(46)
Harbin Engineering University (CN), Yangtze River Delta Physics Research Center (China) (CN), Material Sciences (United States) (US), Intelligent Health (United Kingdom) (GB)
Openalex Percentile: Top 17%
Advanced Sensor and Energy Harvesting Materials
1.35
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Machine Learning Enabled Fluorescent Anti-Freezing Core–Shell Hydrogel Realizing Deep-Sea Morse Code Communication for Human-Machine Interaction Engineering — Piaoping Yang, Shili Gai, et al. · Nano Letters (2025) | TGRS Research Map | TGRS