Recent Advances in Shape Memory Polymers: Multifunctional Materials, Multiscale Structures, and Applications

被引:49
|
作者
Luo, Lan [1 ]
Zhang, Fenghua [1 ]
Wang, Linlin [1 ]
Liu, Yanju [2 ]
Leng, Jinsong [1 ]
机构
[1] Harbin Inst Technol HIT, Ctr Composite Mat & Struct, Harbin 150080, Peoples R China
[2] Harbin Inst Technol HIT, Dept Astronaut Sci & Mech, Harbin 150001, Peoples R China
基金
国家重点研发计划; 中国国家自然科学基金;
关键词
application; composites; multiscale structures; shape memory polymer; CARBON NANOTUBES; EPOXY COMPOSITES; NETWORKS; FIBERS; NANO; NANOCOMPOSITES; POLYURETHANE; TEMPERATURE; FABRICATION; NANOFIBERS;
D O I
10.1002/adfm.202312036
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Shape memory polymers (SMPs) are one of the primary directions in the development of modern high-tech new materials, which are integrated with sensing, actuation, information processing, and autonomous deformation. Here, multifunctional shape memory polymers are focused and a detailed introduction to the characteristics of self-deformation, self-sensing, self-healing, and self-learning is provided. Integrating with other functional materials to form shape memory polymer composites (SMPC), designing and controlling the material structure and organization at the microscale, thereby achieving more precise and controllable shape memory effects and expanding the potential of material applications. Ultimately, it is shown that SMPs and their composites have a wide range of fascinating applications in the fields of robotics, smart clothing, smart textiles, biomedical devices, and wearable technology. SMPs will thus continue to play a significant role in future deeper exploration. Shape memory polymers (SMPs) are one of the primary directions in the development of modern high-tech new materials, which are integrated with sensing, actuation, information processing, and autonomous deformation. SMPs and their composites have a wide range of fascinating applications in the fields of robotics, smart clothing, smart textiles, biomedical devices, and wearable technology.image
引用
收藏
页数:32
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