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The Synergism of β-Cyclodextrin and Fe3+ Enabled Anti-Swelling Ion-Conductive Hydrogels for Multimodal Underwater Sensing Aided by Machine Learning Algorithms

Hao Dong, Chuanliu Liu, Yiming Luo, Dongyu Si, Menghan Zhao, Fangyu Zhao, Yixue Zhang, Wei Zeng, Eman Ramadan Elsharkawy, Terence Liu*, Zeinhom M. El-Bahy, Hua Hou, Zhanhu Guo, Huige Wei*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

As the key sensing component of flexible sensors, conductive hydrogels are prone to mechanical property degradation and signal deterioration owing to water absorption and swelling in underwater environments. Herein, an anti-swelling ion-conducting hydrogels are designed by incorporating ferric chloride (FeCl 3 ) and β-cyclodextrin (β-CD) into acrylamide-acrylic acid copolymer(MA) via a one-pot method, short for MAFx Dy . Thanks to the synergism of β-CD and Fe3+ , the swelling ratio of MAFx Dy is significantly reduced comparted to its counterparts, for example, 4% for MAF 0.2 D0.3 , compared to 760% for MAF 0.2 hydrogel withoutβ-CD and 526% for MAD0.3 without Fe3+ after soaking in deionized water for 30 days. Notably, the multimodal underwater sensor constructed based on the MAF 0.2 D0.3 hydrogel can not only monitor underwater human joint motion but also realizes the accurate transmission of underwater information with the help of Morse code. Moreover, aided by machine learning algorithms, this study proposes a novel shortcut key recognition strategy to achieve precise and rapid information transmission via letter recognition(with a recognition accuracy of 98.6%), dramatically shortening the time required for underwater communication. This study provides innovative solutions by the rational design of anti-swelling ion-conducting hydrogels for reliable and fast under water communications.
Original languageEnglish
Article numbere74916
Number of pages14
JournalAdvanced Science
Early online date28 Mar 2026
DOIs
Publication statusE-pub ahead of print - 28 Mar 2026

Keywords

  • anti-swelling
  • information transfer
  • machine learning algorithms
  • underwater sensing

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