水响应形状记忆高分子是一类遇水能够从临时形状恢复至初始形状的智能材料。目前多数该类材料为人工合成型，掺杂天然蛋白成分的共聚物及纯天然蛋白材料型（鸟类羽毛）最近被报道有明显水响应特征。而自然界广泛存在的型角蛋白纤维材料在水响应形状记忆特性及机理研究方面却未有报道，这也引起了智能材料研究者的极大兴趣。
  香港理工大学胡金莲教授课题组通过对三类典型的动物毛发（型纺织纤维材料）进行水响应形状记忆研究，发现水分子可以使纤维溶胀、临时定形和形状回复，形状固定率和回复率（如驼毛）分别达到95%和85%以上。

（图a: 水能使干的毛发发生溶胀；图b：毛发的水响应形状记忆效果；图c: 临时定形的毛发在水中随时间动态回复的瞬间照片）

  研究者解析了水对毛发纤维形变过程中的回复动力学问题发现：水可以使拉伸的纤维形状回复速率加快；反过来湿的毛发纤维在逐渐变干的过程中，纤维的模量逐渐提高而损耗模量逐渐降低。毛发纤维在动态力学分析实验中发现润湿和干燥过程可是使得毛发模量呈周期性变化，体现了可逆性显著的形状记忆效果。

（图a: 拉伸毛纤维在干燥和湿润环境中动态回复速率的比较；图b和c：DMA下测得毛纤维储存模量和损耗系数在干湿状态下的转变）

  研究者随后对毛发纤维在水响应形状记忆各个环节进行了高分子模型中节点（Net-point）和开关（switch）的表征，其中XRD和拉曼波谱表征显示毛发内部结晶和二硫键不随水响应形状记忆过程发生变化，而毛发内部氢键则在各个阶段展示了其开关的作用，说明毛发纤维发是一类以氢键为开关的、结晶和二硫键为双节点的水响应形状记忆天然高分子聚合物。节点的种类和含量的多少决定了毛发纤维形状回复能力的大小，而氢键的多少则决定了毛发纤维临时形状固定能力的强弱。

  双节点单开关的毛发纤维记忆模型揭示了自然界蛋白纤维不同形状记忆能力的机理，为丰富单一合成纤维不同形状记忆能力和仿生开发更智能的合成纤维提供了借鉴和指导意义。这一研究对于开发医用智能材料和器械指明了方向，例如，利用不同形状记忆能力的纤维制备的矫形器械通过逐步矫形来缓解矫形过程中给患者带来的痛苦，目前中科院和深圳善行医疗科技等单位和公司已对此项研究的应用扩展表达了浓厚的兴趣。

  摘要快递：

  Animal Hairs as Water-stimulated Shape Memory Materials: Mechanism and Structural Networks in Molecular Assemblies

  Scientific Reports

  DOI: 10.1038/srep26393

  Published: 27 May 2016

  Animal hairs consisting of α-keratin biopolymers existing broadly in nature may be responsive to water for recovery to the innate shape from their fixed deformation, thus possess smart behavior, namely shape memory effect (SME). In this article, three typical animal hair fibers were first time investigated for their water-stimulated SME, and therefrom to identify the corresponding net-points and switches in their molecular and morphological structures. Experimentally, the SME manifested a good stability of high shape fixation ratio and reasonable recovery rate after many cycles of deformation programming under water stimulation. The effects of hydration on hair lateral size, recovery kinetics, dynamic mechanical behaviors and structural components (crystal, disulfide and hydrogen bonds) were then systematically studied. SME mechanisms were explored based on the variations of structural components in molecular assemblies of such smart fibers. A hybrid structural network model with single-switch and twin-net-points was thereafter proposed to interpret the water-stimulated shape memory mechanism of animal hairs. This original work is expected to provide inspiration for exploring other natural materials to reveal their smart functions and natural laws in animals including human as well as making more remarkable synthetic smart materials.