Self-Healing Four-Dimensional Printing with an Ultraviolet Curable Double-Network Shape Memory Polymer System.

Area of Science:

• Materials Science
• Polymer Chemistry
• Additive Manufacturing

Background:

• Four-dimensional (4D) printing allows 3D printed objects to change shape over time, with shape memory polymers (SMPs) being key materials.
• Current SMPs, often (meth)acrylate thermosets, lack self-healing capabilities, limiting their long-term application due to permanent cross-linked networks.

Purpose of the Study:

• To develop a double-network self-healing SMP (SH-SMP) system for high-resolution 4D printing.
• To address the limitations of unrepairable SMP-based 4D printing materials.
• To investigate the incorporation of polycaprolactone (PCL) for self-healing properties.

Main Methods:

• Incorporation of semicrystalline linear polycaprolactone (PCL) into a methacrylate-based SMP system.
• Fabrication of complex 4D printing structures using digital light processing (DLP) with high resolution (up to 30 μm).
• Investigation of PCL concentration effects on thermomechanical behavior, viscosity, and self-healing efficiency.
• Computational fluid dynamics (CFD) simulations to analyze the impact of viscosity on the 3D printing process.

Main Results:

• The SH-SMP system demonstrates high-resolution 4D printing capabilities.
• Mechanical properties of damaged structures recovered to over 90% with >20 wt% PCL.
• PCL concentration significantly influences thermomechanical properties, viscosity, and self-healing efficiency.
• CFD simulations confirmed the relationship between viscosity and printability.

Conclusions:

• The developed SH-SMP system offers a viable solution for creating high-resolution, self-healing 4D printed structures.
• The incorporation of PCL effectively imparts self-healing capabilities without compromising printability.
• This advancement holds significant potential for applications requiring durable and repairable 4D printed components.