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<p>Polycaprolactone (PCL)-shape memory polyurethane (SMPU) is widely used in various fields due to its excellent performance. However, PCL-SMPU often struggles to obtain high fracture elongation and shape memory recovery ability because of its large crystal size and relatively low hydrogen bonding energy. To overcome the difficulties and achieve better properties, our research proposed an optimization strategy that combines hydrogen bonding and crystallization control, which involves introducing a small amount of polyethylene adipate 1, 4-butanediol ester (PBA) and adjusting the ratio of soft-to-hard segments. The addition of PBA can form strong hydrogen bonding with isocyanate and form secondary hydrogen bonding with PCL, which can significantly improve the tensile strength and fracture elongation through multiple-level hydrogen bonding. Moreover, regular PBA chains can form microcrystals, thereby not only ensuring the crystallinity but also refining the large crystal size of PCL segments and optimizing the stress distribution. Apart from compounding PBA, the adjustment of the ratio of soft-to-hard segments plays a significant role in resulting in a better overall performance. This modification endows the material with excellent mechanical properties (tensile strength of 20.29&#xa0;MPa, elongation at break of 1462.09%) and shape memory properties. (Both shape recovery rate and shape fixation rate are above 99%, and the shape recovery driving force is 4.11&#xa0;MPa.) Besides, the synthesized SMPU can achieve reversible deformation of 16.85% under 0.2&#xa0;MPa external force. Based on the excellent performance mentioned above, this material has great potential for application in the field of intelligent actuators.</p> Graphical Abstract <p></p> <p>The synthesized PBA/PCL-based shape memory polyurethane acquires great overall performance, making it potential in the field of intelligent actuator fields and so on.</p>

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Hydrogen bonding and crystallization optimization in shape memory polymers for intelligent actuator applications

  • 期刊论文

  • 发表日期：

    2026年1月28日

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  • Junyi Yao,
  • Zhongzheng Zhu,
  • Qitan Zheng,
  • Yi Xin,
  • Hezhou Liu,
  • Hua Li

摘要

Polycaprolactone (PCL)-shape memory polyurethane (SMPU) is widely used in various fields due to its excellent performance. However, PCL-SMPU often struggles to obtain high fracture elongation and shape memory recovery ability because of its large crystal size and relatively low hydrogen bonding energy. To overcome the difficulties and achieve better properties, our research proposed an optimization strategy that combines hydrogen bonding and crystallization control, which involves introducing a small amount of polyethylene adipate 1, 4-butanediol ester (PBA) and adjusting the ratio of soft-to-hard segments. The addition of PBA can form strong hydrogen bonding with isocyanate and form secondary hydrogen bonding with PCL, which can significantly improve the tensile strength and fracture elongation through multiple-level hydrogen bonding. Moreover, regular PBA chains can form microcrystals, thereby not only ensuring the crystallinity but also refining the large crystal size of PCL segments and optimizing the stress distribution. Apart from compounding PBA, the adjustment of the ratio of soft-to-hard segments plays a significant role in resulting in a better overall performance. This modification endows the material with excellent mechanical properties (tensile strength of 20.29 MPa, elongation at break of 1462.09%) and shape memory properties. (Both shape recovery rate and shape fixation rate are above 99%, and the shape recovery driving force is 4.11 MPa.) Besides, the synthesized SMPU can achieve reversible deformation of 16.85% under 0.2 MPa external force. Based on the excellent performance mentioned above, this material has great potential for application in the field of intelligent actuators.

Graphical Abstract

The synthesized PBA/PCL-based shape memory polyurethane acquires great overall performance, making it potential in the field of intelligent actuator fields and so on.