Rapidly and Repeatedly Reprogrammable Liquid Crystalline Elastomer via a Shape Memory Mechanism

Area of Science:

• Materials Science
• Polymer Chemistry
• Soft Robotics

Background:

• Achieving muscle-like actuation in liquid crystal elastomers (LCEs) necessitates precise mesogen alignment.
• Current methods typically fix alignment chemically during synthesis, limiting post-synthesis control.
• Developing convenient and repeatable methods for post-synthesis alignment regulation remains a significant challenge.

Purpose of the Study:

• To design and synthesize a novel dual-phase LCE network for controllable mesogen alignment.
• To enable post-synthesis reprogramming of LCE actuation through a physical mechanism.
• To explore the potential for versatile 3D printed LCEs with programmable actuation modes.

Main Methods:

• Synthesized a dual-phase LCE network with distinct crystalline and liquid crystalline transition temperatures.
• Utilized the crystalline phase as a physical
• alignment frame
• leveraging a shape memory mechanism.
• Investigated erasure of alignment via melting, facilitating reprogramming.

Main Results:

• Demonstrated that the crystalline phase effectively fixes mechanical deformation and induces mesogen alignment in the liquid crystalline phase.
• Showcased repeatable reprogramming of alignment within seconds by exploiting the melting transition.
• Achieved unprecedented versatility in programming actuation modes for 3D printed LCEs.

Conclusions:

• The developed strategy offers a physical, shape-memory-based approach for mesogen alignment in LCEs.
• This method allows for rapid, repeatable, and post-synthesis reprogramming of LCE actuation.
• The findings open new avenues for designing advanced 3D printed soft actuators with tailored functionalities.