Hierarchical network relaxation of a dynamic cross-linked polyolefin elastomer for advanced reversible shape memory...

Area of Science:

• Polymer Science
• Materials Science
• Soft Robotics

Background:

• Reversible shape-memory polymers (RSMPs) are crucial for soft actuators requiring repeatable deformation.
• Existing materials often face limitations in achieving both high reconfigurability and robust shape memory effects.

Purpose of the Study:

• To develop a novel polyolefin elastomer vitrimer (POEV) with enhanced reversible shape memory effects (RSMEs).
• To investigate the relationship between hierarchical network relaxation, topological rearrangement, and material performance.
• To integrate aligned carbon nanotubes (CNTs) for improved mechanical properties and actuation strain.

Main Methods:

• Preparation of a POEV using dynamic boronic ester bonds.
• Characterization of hierarchical network relaxation across a wide temperature range.
• Implementation of a two-stage training process to incorporate aligned CNTs.
• Evaluation of shape reconfigurability and RSMEs.

Main Results:

• The POEV demonstrated tunable network relaxation and controllable chain entropy via temperature programming.
• Effective creation of actuation and skeleton domains within the POEV, enhancing RSMEs.
• Achieved complex 3D shape formation and on-demand shape-shifting.
• Successfully integrated aligned CNTs, improving elasticity and acting as a hybrid skeleton without compromising actuation strain.

Conclusions:

• The developed POEV exhibits synergistic properties including excellent shape reconfigurability and advanced RSMEs.
• Hierarchical network relaxation and topological rearrangement are key to achieving these advanced material properties.
• This work paves the way for smart materials with superior performance in soft actuation applications.