Quantitative predictions of maximum strain storage in shape memory polymers (SMP)

Chris C. Hornat, Marlies Nijemeisland, Michele Senardi, Ying Yang, Christian Pattyn, Sybrand van der Zwaag, Marek W. Urban

Research output: Contribution to journalArticleScientificpeer-review

2 Citations (Scopus)

Abstract

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 (Tg) and melting (Tm) 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 Tg-based SMPs when deformed near their Tg. 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 (νj), 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 (ε-storemax) can be accurately predicted using junction density (νj) and shape memory factor (SMF), the latter accounting for the contribution of chemical makeup.

Original languageEnglish
Article number122006
Number of pages5
JournalPolymer
Volume186
DOIs
Publication statusPublished - 2020

Keywords

  • Polymers
  • Quantitative determination
  • Shape memory

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