期刊论文详细信息
POLYMER 卷:186
Quantitative predictions of maximum strain storage in shape memory polymers (SMP)
Article
Hornat, Chris C.1  Nijemeisland, Marlies2  Senardi, Michele2  Yang, Ying1  Pattyn, Christian1  van der Zwaag, Sybrand2  Urban, Marek W.1 
[1] Clemson Univ, COMSET, Dept Mat Sci & Engn, Clemson, SC 29634 USA
[2] Delft Univ Technol, Fac Aerosp Engn, Novel Aerosp Mat Grp, Kluyverweg 1, NL-2629 HS Delft, Netherlands
关键词: Shape memory;    Polymers;    Quantitative determination;   
DOI  :  10.1016/j.polymer.2019.122006
来源: Elsevier
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【 摘 要 】

Shape memory polymers (SMPs) are dynamic materials able to recover previously defined shapes when activated by external stimuli. The most common stimulus is thermal energy applied near thermal transitions in polymers, such as glass transition (T-g) and melting (T-m) temperatures. The magnitude of the geometrical changes as well as the amount of force and energy that a SMP can output are critical properties for many applications. While typically deformation steps in the shape memory cycles (SMC) are performed at temperatures well above thermal transitions used to activate shape changes, significantly greater amounts of strain, stress, and mechanical energy can be stored in T-g-based SMPs when deformed near their T-g. Since maximum shape memory storage capacity can be appraised by evaluating the viscoelastic length transitions (VLTs) in a single dynamic mechanical analysis (DMA) experiment, this study correlates VLTs with the measured storage capacities obtained from stress-strain experiments for a broad range of well-defined crosslinked acrylates, epoxies, and polyurethanes. This systematic approach allows for assessment of crosslink/junction density (nu(j)), viscoelasticity, and chemical composition effects on maximum deformability, and enables predictions of the magnitude of shape memory properties across a wide variety of polymers. These studies demonstrate that the maximum storable strain (epsilon-store(max)) can be accurately predicted using junction density (nu(j)) and shape memory factor (SMF), the latter accounting for the contribution of chemical makeup.

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