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Updated: Jul 1, 2026

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Fabrication of a Bioactive, PCL-based "Self-fitting" Shape Memory Polymer Scaffold
Published on: October 23, 2015
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Dynamic Bonds Reinforced Polyamide Elastomer for Biomedical Orthosis
Zhen Li1,2, Peiyao Yan2, Hao Wang2
1School of Materials Science and Engineering, Zhengzhou University, Zhengzhou, 450001, China.
Summary
This study developed a novel 4D-printed intelligent orthosis using shape memory polyamide elastomer. The material overcomes challenges in 4D printing, enhancing shape memory performance and reducing anisotropy for advanced applications.
Area of Science:
- Materials Science
- Polymer Chemistry
- Additive Manufacturing
Background:
- 4D printing of shape memory polymers (SMPs) offers adjustable structures but faces challenges like mechanical anisotropy and poor interlayer adhesion.
- These limitations hinder the performance and application of 4D-printed SMPs in intelligent devices.
Purpose of the Study:
- To develop a multifunctional intelligent orthosis using 4D printing technology.
- To enhance the mechanical and shape memory properties of 4D-printed SMPs by addressing interlayer adhesion and anisotropy.
Main Methods:
- Developed a dynamic bonds (DBs) reinforced shape memory polyamide elastomer via reactive extrusion using a twin-screw extruder.
- Introduced dynamic covalent networks, including dynamic covalent bonds (DCBs) and hierarchical hydrogen bonds (DHBs), to improve interlayer adhesion.
- Utilized 4D printing technology to fabricate the intelligent orthosis.
Main Results:
- The developed elastomer exhibited enhanced interlayer adhesion, significantly reducing mechanical anisotropy in 4D-printed objects.
- The 4D-printed materials demonstrated improved mechanical properties and superior shape memory performance.
- The study successfully demonstrated the material's versatility and its application in a spinal orthosis.
Conclusions:
- The integration of DBs into shape memory polyamide elastomer effectively enhances interlayer adhesion and mechanical properties for 4D printing.
- This approach overcomes key limitations in 4D-printed SMPs, enabling advanced functionalities and applications like intelligent orthoses.

