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Fe3+, NIR light and thermal responsive triple network composite hydrogel with multi-shape memory effect

  • Yan Qin Wang
  • , Yu Zhu
  • , Jing Hui Wang
  • , Xiao Na Li
  • , Xiao Gang Wu
  • , Yi Xian Qin
  • , Wei Yi Chen
  • Taiyuan University of Technology
  • South China University of Technology

Research output: Contribution to journalArticlepeer-review

52 Scopus citations

Abstract

Recently, artificial intelligence has driven the development of shape memory hydrogels (SMHs) with complicated environmental sensitive abilities. However, current SMHs possess fundamental limitations in terms of their responsive performance and mechanical properties, which severely limits their practical applications. Herein, a triple-network composite hydrogel with Fe3+, NIR light, and thermal responsive abilities is fabricated and developed as multi-SMHs, named as PDA/CMC-Fe3+/PVA hydrogel. In this hydrogel system, the interpenetrating triple network are formed by chemically-physically co-crosslinked polyvinyl alcohol (PVA) networks, and physically crosslinked carboxymethyl cellulose (CMC)-Fe3+ network. In addition, polydopamine (PDA), which is introduced into the hydrogel system by in-situ polymerization way, could not only serve as an energy converter to endow the hydrogel with NIR-based responsive ability, but also enhance its mechanical strength. Remarkably, the as-prepared PDA/CMC-Fe3+/PVA hydrogels with the optimized compositions exhibit relatively excellent mechanical properties (tensile strength = 163.48 ± 10.42 kPa, elastic modulus = 45.42 ± 3.96 kPa, toughness = 165.02 ± 7.01 kJ/m3) due to the synergistic effect of the triple-network and PDA doping. Moreover, the composition of the hydrogel is optimized to realize a stable temporary shape and rapid recovery to the permanent shape, which is controlled by Fe3+, NIR irradiation, and thermal stimulus. The resultant hydrogels exhibit not only multi-stimulus responsive abilities, but also programmable multi-shape memory properties. The versatile shape memory properties endow potential for the materials to be used in the field of artificial intelligence.

Original languageEnglish
Article number108653
JournalComposites Science and Technology
Volume206
DOIs
StatePublished - Apr 12 2021

Keywords

  • In-situ
  • Mechanical properties
  • Multi-shape memory effect
  • NIR responsive
  • Triple network

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