Super-tough, self-sensing and shape-programmable polymers via topological structure crosslinking networks

韧性 智能材料 形状记忆聚合物 聚合物 热固性聚合物 环氧树脂 材料科学 拓扑(电路) 智能聚合物 形状记忆合金 纳米技术 工程类 复合材料 电气工程
作者
Lan Luo,Fenghua Zhang,Yanju Liu,Jinsong Leng
出处
期刊:Chemical Engineering Journal [Elsevier BV]
卷期号:457: 141282-141282 被引量:24
标识
DOI:10.1016/j.cej.2023.141282
摘要

Shape-memory polymers (SMPs) are smart materials capable of deforming actively under external excitation. Owing to their characteristics, including variable stiffness, programmable deformation, composability, and self-sensing, and its behavior is similar to the intelligent reflection of life, these materials are highly valuable for applications in many fields. We have developed a molecular engineering strategy based on topological cross-linking networks, which form hydrogen bonds, hyperbranching, ring network structure, etc. to obtain shape memory epoxy resin (SMEP) with super toughness, high-temperature resistance and triple shape memory effect (TSME). Additionally, the internal relationship between the molecular network structure and material performance is simulated by molecular dynamics. It has super toughness (1288 %) and high impact energy (216 MJ/m3) above its transition temperature, breaking through the previously reported thermosetting resin. Importantly, the developed SMPs system exhibited outstanding fatigue resistance and was successfully loaded repeatedly for more than 100 cycles. Finally, the intramolecular cyclization effect led to the generation of different linked structures in situ, which endowed SMEP with TSME, thereby rendering such materials potentially applicable in engineering fields, such as aerospace, smart furniture, and soft robotics.
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