Fused Filament Fabrication 4D Printing of a Highly Extensible, Self-Healing, Shape Memory Elastomer Based on Thermoplastic Polymer Blends

Abstract

A polymer blend with high extensibility, exhibiting both shape memory and self-healing, was 4D printed using a lowcost fused filament fabrication (FFF, or fused deposition modeling, FDM) 3D printer. The material is composed of two commercially available commodity polymers, polycaprolactone (PCL), a semicrystalline thermoplastic, and polystyrene-block-poly(ethylene-cobutylene)-block-polystyrene (SEBS), a thermoplastic elastomer. The shape memory and self-healing properties of the blends were studied systematically through thermo-mechanical and morphological characterization, providing insight into the shape memory mechanism useful for tuning the material properties. In 3D-printed articles, the orientation of the semi-crystalline and micro-phaseseparated domains leads to improvement of the shape memory property and extensibility of this material compared to compression-molded samples. By controlling the orientation of the printed fibers, we achieved a high strain at break over 1200%, outperforming previously reported flexible 4D-printed materials. The selfhealing agent, PCL, enables the material to heal scratches and cracks and adhere two surfaces after annealing at 80 °C for 30 min. The high performance, multi-functionality, and potential scalability make it a promising candidate for a broad spectrum of applications, including flexible electronics, soft actuators, and deployable devices.

Weldable and Reprocessable Shape Memory Epoxy Vitrimer Enabled by Controlled Formulation for Extrusion‐Based 4D Printing Applications

“…To select a representative material for 4D printing from our series of samples, the printability was investigated by inspecting the quality by extrusion of the material using a filament extruder at 190 °C. [ 43 ] D1.30_T15.0 and D1.45_T17.5, which exhibited unsatisfactory continuous extrusion owing to slow stress relaxation, had rough surfaces and exhibited low filament quality due to melt fracture during processing, as shown in Figure a and Figure S4, Supporting Information, respectively. D1.15_T17.5 and D1.30_T12.0 did not allow filaments capable of shape retention to be fabricated because of their low storage modulus at 190 °C (<0.2 MPa), and exhibited liquid‐like flow behavior under extrusion conditions.…”

Polymer 4D printing: Advanced shape‐change and beyond

“…Hence, the object is healed, and retains its shape memory function thanks to the SMP nature of the bulk polymer matrix. This method of using PCL as a self‐healing agent in SMP 4D printing has been demonstrated for DIW, 122 DLP 137 and FDM 128 …”

“…The Tango™ and Vero™ series of commercial SMPs from Stratasys® are especially popular 12,51,65,66,68–70,75,77,78,81,83–91 . Common 4D printable polymers which have shown shape memory effects include polylactic acid (PLA), 55,57,63,82,92–113 polycaprolactone (PCL), 57,59,64,79,80,106,114,115 polyurethane (PU), 54,116–125 polyester (PE), 126,127 polystyrene (PS), 113,128 acrylonitrile butadiene styrene (ABS), 113,129 high impact polystyrene (HIPS), 113 polyamide, 130 and polyvinyl alcohol (PVA) 56,131 . There are also many acrylate monomers which have been polymerized during the 3D printing process to make SMPs such as butyl acrylate, 122 tert ‐butyl acrylate, 132–135 benzyl methacrylate, 136,137 lauryl acrylate, 138 methyl acrylate, 139 isobornyl acrylate (IBOA), 123,139–143 acrylic acid, 52 bisphenol‐A glycerolate dimethacrylate, 72 bisphenol A diglycidyl ether diacrylate, 123,144 trimethylolpropane triacrylate, 140 ethylene glycol phenyl ether acrylate, 141 2‐ethyl hexyl acrylate, 143 2‐phenoxyethyl acrylate, 142 and soybean oil epoxidized acrylate, 60 as well as acrylate crosslinkers such as di(ethylene glycol) diacrylate, 133–137 bisphenol A ethoxylate dimethacrylat...…”

Shape memory elastomers: A review of synthesis, design, advanced manufacturing, and emerging applications

“…In some works, the printed specimens produced by these techniques exhibit better shape memory and mechanical properties compared with the samples made using casting or molding techniques 34 . Currently, 3D/4D printed SMEs are utilized in many novel engineering designs and emerging applications, such as flexible electronics, soft actuators, and deployable devices 35,36 …”

“…34 Currently, 3D/4D printed SMEs are utilized in many novel engineering designs and emerging applications, such as flexible electronics, soft actuators, and deployable devices. 35,36 Machine learning (ML) is another contemporary technology that has gained more attention in material design since its first development in 1959. 37 This class of artificial intelligence (AI) technologies has been used for modeling novel materials with the desired property for a variety of purposes, such as superalloys for ultra-supercritical power plants, 38 shape memory alloys (SMAs), 39 and new solid catalytic materials.…”