journal article·2026-07Open access

4D printing of PETG/TPU shape memory nanocomposites reinforced with carbon nanotubes (CNTs) and carbon black (CB)

Sahar Khorooty, Mahdi Khajepour, Mohammad Amin Yousefi, Davood Rahmatabadi, Majid Baniassadi, Mostafa Baghani

Abstract

4D printing of shape memory polymers (SMPs) enables time-programmed function, and conductive fillers are promising additives for improving thermomechanical performance and potentially enabling future electrothermal activation. In this study, the effect of carbon-based nanoparticles, including carbon black (CB) and carbon nanotubes (CNTs), on a PETG/TPU (70/30) blend was investigated using formulations reinforced with CB or CNT at 6 wt% and a hybrid CB3%/CNT3%. The mechanical properties, dynamic mechanical thermal analysis (DMTA), printability, morphology, and shape memory behavior of the nanocomposites were investigated. The neat PETG/TPU showed UTS 26.22 MPa and elongation 7.9%; the elastic modulus was essentially unchanged by adding nanoparticles. Among the nanocomposites, CB6% provided the best overall balance, with UTS 26.63 MPa, elongation 7.67%, and 92% recovery in 19 s (fixity 100%). CNT6% exhibited lower strength but higher ductility (elongation roughly doubled versus the neat blend) with recovery close to CB6%. The CB3%/CNT3% hybrid showed the weakest mechanical response and the lowest recovery. microstructural properties supported these trends: CB showed more uniform dispersion and fewer interlayer voids; CNT was broadly similar but slightly rougher; the hybrid displayed more defects. Overall, 6 wt% CB is identified as the most balanced composition for PETG/TPU when mechanical integrity, printability, and rapid thermally induced shape recovery are required. 6 wt% CNT is suitable where additional deformability is desired, while the equal-ratio hybrid should be avoided unless dispersion is improved.
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Research context

OpenAlex topics: Polymer composites and self-healing · Advanced Materials and Mechanics · Additive Manufacturing and 3D Printing Technologies

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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