Tailoring Diels–Alder Cross-Linked Liquid Crystal Elastomers for Spatially Programmable Monolithic Actuators
Yue Liu, Qing Yang, Qing Liu, Jing Zhao, Ying Zhang, Qiongyao Peng, Zhi‐Chao Jiang, Yao‐Yu Xiao, Hongbo Zeng
- 发表年份
- 2025
- 引用次数
- 10
摘要
Liquid crystal elastomers with thermo-reversible Diels-Alder cross-links (DALCEs) offer exceptional reprocessability and mild-temperature reprogrammability, enabling repeated fabrication of diverse actuators. However, optimizing their molecular design and refabrication protocols remains crucial to further unlocking their potential. This work systematically investigates DALCEs synthesized via aza-Michael addition reactions between RM82, furfurylamine, and various chain extenders (phenylethylamine, ethylamine, butylamine, hexylamine, octylamine, and 6-amino-1-hexanol). The effects of cross-linking density and chain extender selection on phase behavior, thermomechanical properties, and actuation performance have been thoroughly examined. The results show that a PEA-based formulation with moderate cross-linking density achieves the most balanced performance. Based on this optimized formulation, a novel (re)fabrication strategy is introduced by harnessing DALCEs' intrinsic reprocessability, reprogrammability, and self-healing properties. This strategy employs multilevel fiber programming before monolithic actuator formation, enabling spatially controlled liquid crystal alignment and facilitating iterative actuator refinement through reconstruction. Consequently, complex morphing behaviors in disk films and stress-modulating functions in tubular actuators were demonstrated. This work establishes a versatile, easily synthesized material platform for spatially programmable, dynamic monolithic actuators, paving the way for advanced applications in soft robotics and adaptive devices.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
Genetic Programming: On the Programming of Computers by Means of Natural Selection
John R. Koza
1992