Quantitative predictions of maximum strain storage in shape memory polymers (SMP)
| Autor: | Chris C. Hornat, Michele Senardi, Marek W. Urban, Sybrand van der Zwaag, Ying Yang, Marlies Nijemeisland, Christian Pattyn |
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| Rok vydání: | 2020 |
| Předmět: |
Materials science
Polymers and Plastics Polymers 02 engineering and technology 010402 general chemistry 01 natural sciences Viscoelasticity Materials Chemistry Composite material Mechanical energy chemistry.chemical_classification business.industry Organic Chemistry Dynamic mechanical analysis Shape-memory alloy Polymer 021001 nanoscience & nanotechnology 0104 chemical sciences Shape memory Shape-memory polymer Quantitative determination chemistry 0210 nano-technology business Glass transition Thermal energy |
| Zdroj: | Polymer, 186 |
| ISSN: | 0032-3861 |
| DOI: | 10.1016/j.polymer.2019.122006 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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