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  水響應形狀記憶高分子是一類遇水能夠從臨時形狀恢復至初始形狀的智能材料。目前多數(shù)該類材料為人工合成型，摻雜天然蛋白成分的共聚物及純天然蛋白材料型（鳥類羽毛）最近被報道有明顯水響應特征。而自然界廣泛存在的型角蛋白纖維材料在水響應形狀記憶特性及機理研究方面卻未有報道，這也引起了智能材料研究者的極大興趣。
  香港理工大學胡金蓮教授課題組通過對三類典型的動物毛發(fā)（型紡織纖維材料）進行水響應形狀記憶研究，發(fā)現(xiàn)水分子可以使纖維溶脹、臨時定形和形狀回復，形狀固定率和回復率（如駝毛）分別達到95%和85%以上。

（圖a: 水能使干的毛發(fā)發(fā)生溶脹；圖b：毛發(fā)的水響應形狀記憶效果；圖c: 臨時定形的毛發(fā)在水中隨時間動態(tài)回復的瞬間照片）

  研究者解析了水對毛發(fā)纖維形變過程中的回復動力學問題發(fā)現(xiàn)：水可以使拉伸的纖維形狀回復速率加快；反過來濕的毛發(fā)纖維在逐漸變干的過程中，纖維的模量逐漸提高而損耗模量逐漸降低。毛發(fā)纖維在動態(tài)力學分析實驗中發(fā)現(xiàn)潤濕和干燥過程可是使得毛發(fā)模量呈周期性變化，體現(xiàn)了可逆性顯著的形狀記憶效果。

（圖a: 拉伸毛纖維在干燥和濕潤環(huán)境中動態(tài)回復速率的比較；圖b和c：DMA下測得毛纖維儲存模量和損耗系數(shù)在干濕狀態(tài)下的轉變）

  研究者隨后對毛發(fā)纖維在水響應形狀記憶各個環(huán)節(jié)進行了高分子模型中節(jié)點（Net-point）和開關（switch）的表征，其中XRD和拉曼波譜表征顯示毛發(fā)內部結晶和二硫鍵不隨水響應形狀記憶過程發(fā)生變化，而毛發(fā)內部氫鍵則在各個階段展示了其開關的作用，說明毛發(fā)纖維發(fā)是一類以氫鍵為開關的、結晶和二硫鍵為雙節(jié)點的水響應形狀記憶天然高分子聚合物。節(jié)點的種類和含量的多少決定了毛發(fā)纖維形狀回復能力的大小，而氫鍵的多少則決定了毛發(fā)纖維臨時形狀固定能力的強弱。

  雙節(jié)點單開關的毛發(fā)纖維記憶模型揭示了自然界蛋白纖維不同形狀記憶能力的機理，為豐富單一合成纖維不同形狀記憶能力和仿生開發(fā)更智能的合成纖維提供了借鑒和指導意義。這一研究對于開發(fā)醫(yī)用智能材料和器械指明了方向，例如，利用不同形狀記憶能力的纖維制備的矯形器械通過逐步矯形來緩解矯形過程中給患者帶來的痛苦，目前中科院和深圳善行醫(yī)療科技等單位和公司已對此項研究的應用擴展表達了濃厚的興趣。

  摘要快遞：

  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.