Significantly improving electro‐activated shape recovery performance of shape memory nanocomposite by self‐assembled carbon nanofiber and hexagonal boron nitride

Abstract

This study presents two effective approaches to significantly improve the electro‐thermal properties and electro‐activated shape recovery performance of shape memory polymer (SMP) nanocomposites that are incorporated with carbon nanofibers (CNFs) and hexagonal boron nitrides (h‐BNs), and show Joule heating triggered shape recovery. CNFs were self‐assembled and deposited into buckypaper form to significantly improve the electrical properties of SMP and achieve the shape memory effect induced by electricity. The h‐BNs were either blended into or self‐assembled onto CNF buckypaper to significantly improve the thermally conductive properties and electro‐thermal performance of SMPs. Furthermore, the shape recovery behavior and temperature profile during the electrical actuation of the SMP nanocomposites were monitored and characterized. It was found that a unique synergistic effect of CNFs and h‐BNs was presented to facilitate the heat transfer and accelerate the electro‐activated shape recovery behavior of the SMP nanocomposites. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014, 131, 40506.

Review of Progress in Shape Memory Epoxies and Their Composites

“…This buckypaper is not only an efficient reinforcement but enables the electro-activated triggering (Joule heating) of SM at the same time. This possibility was explored by the group of Leng [ 140 , 141 , 142 ] who coated or impregnated the buckypaper with SMEP. In order to improve the heat conductivity of the buckypaper or the corresponding nanocomposites BN was also incorporated or blended into the EP, respectively.…”

Thermoset shape memory polymers and their composites

“…Recently, to improve the functionality of SMEPs, many types of additives and partners have been introduced into shape memory epoxy systems, including polyether (Merline et al, 2008), polymethyl methacrylate nanofibers (Iyengar et al, 2013), surface-modified TiO 2 nanoparticles (Iijima et al, 2009), montmorillonite (Liu et al, 2011), glass fiber fabrics (Fejos et al, 2012), magnetite nanoparticles (Puig et al, 2012), carbon black (Liang and Yun, 2013; Wei et al, 2013b; Yun and Liang, 2012), carbon nanofibers (CNFs) (Ding et al, 2014; Dong et al, 2013), glass fiber (Wei et al, 2013a), SiO 2 (Dong et al, 2015b; Dong and Ni, 2015), graphene oxide (Lu et al, 2014b), reduced graphene oxide paper (Wang et al, 2015b), carbon nanotube (CNT)/graphene aerogels (Liu et al, 2015), multi-walled CNTs (MWCNTs) (Yu et al, 2015), and CNF/hexagonal boron nitride (Lu et al, 2014a, 2015). In particular, the addition of sodium dodecyl sulfate (SDS) into the SMEP system allowed us to successfully achieve water-induced shape memory recovery (Wang et al, 2014b).…”

Epoxy shape‐memory polymer reinforced by thermally reduced graphite oxide: Influence of processing techniques

“…However, pure SMPs are not suitable for some practical applications (for example, aerospace engineering) that require improved mechanical strength, higher thermal stability, and stronger shape recovery force. Therefore, SMPs filled with various reinforcement particles (such as SiC, nanoclay, carbon black, carbon nanotubes, graphene, and hybrid fillers,) were prepared and measured in order to meet the requirements. Among these fillers, carbonaceous materials are superior to the others because of their high surface areas and excellent mechanical, thermal, and electrical properties .…”

“…Therefore, SMPs filled with various reinforcement particles (such as SiC, nanoclay, carbon black, carbon nanotubes, graphene, and hybrid fillers,) were prepared and measured in order to meet the requirements. Among these fillers, carbonaceous materials are superior to the others because of their high surface areas and excellent mechanical, thermal, and electrical properties . The reported SMP composites filled by carbonaceous fillers focused on SMPU composites and PS‐SMP composites, while carbon‐filled ESMP has been barely studied.…”