Future Prospects: Shape Memory Features in Shape Memory Polymers and Their Corresponding Composites

Abstract

Shape memory polymers and their related composites are formally known as SMPs and SMPCs have been classified as innovative categories of smart materials, in which they affected by a particular stimulus and consequently memorize the original shape. As one of the most vital feature of shape memory characteristics, Shape Memory Effect (SME) that been attracted significant attention from the shape memory researchers and scientists. On the other hands, there are abundant approaches can be implemented to actuate the SMPs and SMPCs deformation, whereby the features of the electro-or thermal response associated with the structural changes are predominant. In this chapter, a particular emphasis on how the incorporation of micro/nano-fillers and particles or fibers do affect in the SMP matrices, which it is intentionally carried out to improve the mechanical properties and their related shape memory features of various types of shape memory polymers. In the summary, the shape memory effect is been sustained to be an intrinsic feature for the SMPs and based on this property, the implementation of the SMPs have covered a wide range of applications according to the required functions and performances.

Recent trends in thermo‐responsive elastomeric shape memory polymer nanocomposites

“…The TPU‐based SMP films are also used for shape memory study which contains 1, 3, and 5 weight percent of GO, rGO, and GO:rGO nanoplatelets had exceptional shape memory capability. The composites containing 5 weight percent of hybrid GO:rGO produced the best results, with R f increasing from 94% for pure TPU to 99.1% and R r improving from 86% for clean TPU to 96.7% in the case of the TPU/GO:rGO‐5 sample 208 . The sonication caused agglomerations of graphene platelets to break apart and form smaller aggregates.…”

“…The composites containing 5 weight percent of hybrid GO:rGO produced the best results, with R f increasing from 94% for pure TPU to 99.1% and R r improving from 86% for clean TPU to 96.7% in the case of the TPU/GO:rGO-5 sample. 208 The sonication caused agglomerations of graphene platelets to break apart and form smaller aggregates. The suspension was then mixed with DMF solution.…”

Polímeros com memória de forma: características, tipos e aplicações

“…De forma geral, a taxa de fixação (%) corresponde ao quanto o polímero fixou da deformação aplicada sobre uma tensão constante acima da temperatura de transição do polímero, enquanto que a taxa de retorno (%) corresponde ao quanto o polímero retornou ao seu estado inicial após reaquecido acima de sua temperatura de transição (Figura 1). A Figura 1 exemplifica uma programação padrão para avaliar o efeito memória de forma nos polímeros, a etapa (1) consiste em submeter o polímero a um aquecimento acima da temperatura de transição e simultaneamente aplicar uma tensão para que o polímero se deforme, posteriormente, o polímero é submetido a um resfriamento a uma temperatura abaixo de sua transição (etapa 2) resultando no congelamento da tensão aplicada onde é avaliada a taxa de fixação, consecutivamente, o polímero é novamente aquecido acima de sua temperatura de transição e observa-se seu retorno, e por fim, é calculado a taxa de retorno (%), sendo 100% se o polímero retornar completamente ao seu formato original, quanto menor for a taxa de retorno (%), menor é o efeito memória de forma que o polímero apresenta (Xia et al, 2020;Wang et al, 2017;Hardy et al, 2016;Li et al, 2015;Saud et al, 2019). 2.2 TEORIA TERMO-VISCOELÁSTICA Uma maneira de compreender o efeito memória de forma em polímeros se dá através da teoria termo-viscoelástica.…”

Shape-Memory Polymer Nanocomposites of Poly(ε-caprolactone) with the Polystyrene-block-polybutadiene-block-polystyrene-tri-block Copolymer Encapsulated with Metal Oxides

“…Meanwhile, the final angle (θ f ) of the sample was recorded. The temporary shape retention rate ( R f ), shape-memory recovery speed ( R s ), and shape recovery rate ( R r ) were also calculated using the following equations derived from Figure . ,,, …”