Recently, research on shape memory-based materials has increased because of their shape programming and shape recovery attributes. Compared with shape memory alloy, shape memory polymer polyurethane (SMPU) fiber and its fabric find applications in biomaterials and wearable devices because of its easy manufacturing and flexibility. However, generating high stress to support shape recovery in the SMPU fiber is difficult, and reports about SMPU electrospun nanofiber-based yarn are rare. This study presents a novel method for preparing SMPU electrospun nanofiber-based yarn and coil using a twisting process. Our results demonstrated that, compared with the traditional melting SMPU fiber, the nanofiber interlayer friction increases the shape recovery properties of the SMPU electrospun nanofiber-based yarns and coils. Moreover, the recovery stress of aligned nanofiber-based yarn (with nanofibers’ direction parallel to the tensile direction) is increased by 403%. However, aligned nanofiber-based yarns and coils can resist static and repeated tensile stress above the glass transition temperature. Based on the excellent shape recovery properties, excellent shape memory, and mechanical properties, as well as a combination of nanofibrous network structure, yarn shapes can be realized, which would be a new choice for smart fiber and textile in various applications.

最近，由于形状编程和形状恢复属性，对基于形状记忆的材料的研究有所增加。与形状记忆合金相比，形状记忆聚合物聚氨酯 (SMPU) 纤维及其织物因其易于制造和柔韧性而在生物材料和可穿戴设备中得到应用。然而，产生高应力以支持 SMPU 纤维的形状恢复很困难，关于 SMPU 电纺纳米纤维纱线的报道很少。本研究提出了一种使用加捻工艺制备 SMPU 电纺纳米纤维基纱线和线圈的新方法。我们的结果表明，与传统的熔融 SMPU 纤维相比，纳米纤维层间摩擦增加了 SMPU 电纺纳米纤维基纱线和线圈的形状恢复性能。而且，对齐的纳米纤维基纱线（纳米纤维的方向平行于拉伸方向）的恢复应力增加了 403%。然而，排列的基于纳米纤维的纱线和线圈可以抵抗高于玻璃化转变温度的静态和重复拉伸应力。基于优异的形状恢复性能、优异的形状记忆和机械性能，以及纳米纤维网络结构的结合，可以实现纱线形状，这将是智能纤维和纺织品在各种应用中的新选择。