4D printing of high-performance shape memory polymer with double covalent adaptive networks

Achieving 4D printing of shape memory polymers with both high strength and high transition temperature remains challenging due to the inherent incompatibility between the rigid molecular structure required for high strength and the molecular structure that moves on demand necessary for the shape memory effect, the limitations of high-performance polymer reaction kinetics, as well as internal stress during the printing process. Here, a direct ink writing (DIW) printed high-precision cyanate ester-urethane (CU) shape memory polymer with excellent performance was accomplished by incorporating two dynamic covalent bonds (carbamate and cyanuric acid) through copolymerizing cyanate ester with polyurethane acrylates. During curing, carbamate and cyanuric acid enable stress relaxation and polymer network rearrangement, facilitating the permanent reconfiguration of CU to form a novel triazine network structure. As a result, a high mechanical properties CU with excellent strength (83 MPa) and superior Young's modulus (2.37 GPa) were obtained, besides, the transition temperature (near 250 °C) is the highest in comparison to currently reported 4D-printed shape memory polymers. Furthermore, this reconfigurability was demonstrated by imprinting various surface patterns at microscopic level. Moreover, the reconfigurability of CU provides a novel strategy for smart molds in deformation and easy demolding. Overall, this study opens up a new avenue for the development of high-performance 4D printed shape memory polymers.

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Publication Details

Journal
Advanced Industrial and Engineering Polymer Research
Published
2024-11-28
DOI
https://doi.org/10.1016/j.aiepr.2024.11.002
Citations
8
Primary Topic
Polymer composites and self-healing
Type
article
Field-Weighted Citation Impact
1.35
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article

4D printing of high-performance shape memory polymer with double covalent adaptive networks

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8 citations
Advanced Industrial and Engineering Polymer Research
Polymer composites and self-healing
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article

4D printing of high-performance shape memory polymer with double covalent adaptive networks

Zenghui Yang, Zhangzhang Tang, Yaoming Zhang, Tingmei Wang, Gao Deng, Peng Liu, Chao Wang, Qihua Wang, Liming Tao, Yiyuan Sun
article en
8 citations

Abstract

Achieving 4D printing of shape memory polymers with both high strength and high transition temperature remains challenging due to the inherent incompatibility between the rigid molecular structure required for high strength and the molecular structure that moves on demand necessary for the shape memory effect, the limitations of high-performance polymer reaction kinetics, as well as internal stress during the printing process. Here, a direct ink writing (DIW) printed high-precision cyanate ester-urethane (CU) shape memory polymer with excellent performance was accomplished by incorporating two dynamic covalent bonds (carbamate and cyanuric acid) through copolymerizing cyanate ester with polyurethane acrylates. During curing, carbamate and cyanuric acid enable stress relaxation and polymer network rearrangement, facilitating the permanent reconfiguration of CU to form a novel triazine network structure. As a result, a high mechanical properties CU with excellent strength (83 MPa) and superior Young's modulus (2.37 GPa) were obtained, besides, the transition temperature (near 250 °C) is the highest in comparison to currently reported 4D-printed shape memory polymers. Furthermore, this reconfigurability was demonstrated by imprinting various surface patterns at microscopic level. Moreover, the reconfigurability of CU provides a novel strategy for smart molds in deformation and easy demolding. Overall, this study opens up a new avenue for the development of high-performance 4D printed shape memory polymers.

Advanced Industrial and Engineering Polymer ResearchVol. 8(2)
Chinese Academy of Sciences (CN), Lanzhou Institute of Chemical Physics (CN), University of Chinese Academy of Sciences (CN), Lanzhou University (CN), Nanjing University (CN)
Affordable and clean energy
Openalex Percentile: Top 21%
Polymer composites and self-healing
1.35
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