Design and Characterization of Deformable Superstructures Based on Amine-Acrylate Liquid Crystal Elastomers

Fang Zhao, Yuzhan Li*, Hong Gao*, Ran Tao*, Yiqi Mao*, Yu Chen, Sheng Zhou, Jianming Zhao, Dong Wang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Deformable superstructures are man-made materials with large deformation properties that surpass those of natural materials. However, traditional deformable superstructures generally use conventional materials as substrates, limiting their applications in multi-mode reconfigurable robots and space-expandable morphing structures. In this work, amine-acrylate-based liquid crystal elastomers (LCEs) are used as deformable superstructures substrate to provide high driving stress and strain. By changing the molar ratio of amine to acrylate, the thermal and mechanical properties of the LCEs are modified. The LCE with a ratio of 0.9 exhibited improved polymerization degree, elongation at break, and toughness. Besides an anisotropic finite deformation model based on hyperelastic theory is developed for the LCEs to capture the configuration variation under temperature activation. Built upon these findings, an LCE-based paper-cutting structure with negative Poisson's ratio and a 2D lattice superstructure model are combined, processed, and molded by laser cutting. The developed superstructure is pre-programmed to the configuration required for service conditions, and the deformation processes are analyzed using both experimental and finite element methods. This study is expected to advance the application of deformable superstructures and LCEs in the fields of defense and military, aerospace, and bionic robotics.

Original languageEnglish
Article number2303594
JournalAdvanced Science
Volume10
Issue number36
DOIs
Publication statusPublished - 27 Dec 2023

Keywords

  • amine-acrylate liquid crystal elastomers
  • deformable superstructures
  • finite element analyses
  • self-healing capabilities
  • shape memory

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