Shape memory polymers offer unique properties that are critical to the future of advanced materials. In an effort to effectively predict shape recovery, these studies utilized dynamic and static forces during dynamic mechanical analysis (DMA) to quantify shape memory effects (SME) in polymers. These studies identified the basis for glass transition temperature-based (Tg) SME and showed unique shape memory transitions that are macroscopically manifested by directional extension and subsequent retraction in thermoplastic and thermosetting polymers. While viscous components of the network at the onset of the Tg are responsible for material’s extension, the retractions result from stored conformational entropy as a result of crosslink density and/or chain entanglements. This behavior was quantified in terms of stored (ΔSS) entropic energy density, which combines stress and strain aspects of shape recovery. In contrast to traditional strain recovery and fixation ratios, the proposed approach encompass the maximum strain (εmax), stress (σSF at εmax), and energy storage (ΔSS) by considering polymer architecture, molecular weight, molecular weight distribution, and viscoelastic behavior, thus allowing quantitative assessments of the SME from a single DMA experiment. This concept can be extended to determine the SME in glassy and amorphous inorganic materials for any material that exhibits the Tg and the rubbery plateau above the Tg.

Quantitative predictions of shape memory effects in polymers

253rd National Meeting (2017)

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