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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Petrov, R. H. | Madrid |
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| Azevedo, Nuno Monteiro |
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Baghani, Mostafa
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Topics
Publications (6/6 displayed)
- 20244D Printing of Magneto‐Thermo‐Responsive PLA/PMMA/Fe<sub>3</sub>O<sub>4</sub> Nanocomposites with Superior Shape Memory and Remote Actuationcitations
- 2024Effects of TPU on the mechanical properties, fracture toughness, morphology, and thermal analysis of 3D-printed ABS-TPU blends by FDMcitations
- 20234D Printing‐Encapsulated Polycaprolactone–Thermoplastic Polyurethane with High Shape Memory Performancescitations
- 2023Development of Pure Poly Vinyl Chloride (PVC) with Excellent 3D Printability and Macro‐ and Micro‐Structural Propertiescitations
- 2023Shape memory performance assessment of FDM 3D printed PLA-TPU composites by Box-Behnken response surface methodologycitations
- 20234D Printing of Polyvinyl Chloride (PVC): A Detailed Analysis of Microstructure, Programming, and Shape Memory Performancecitations
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article
Shape memory performance assessment of FDM 3D printed PLA-TPU composites by Box-Behnken response surface methodology
Abstract
<jats:title>Abstract</jats:title><jats:p> In this paper, for the first time, the role of manufacturing parameters of fused deposition modeling (FDM) on the shape memory effect (SME) is investigated by design of experiments. PLA-TPU blend with a weight composition of 30:70% is processed by melt mixing and then extruded into 1.75 mm filaments for 3D printing via FDM. SEM images reveal that TPU droplets are distributed in the PLA matrix, and the immiscible matrix-droplet morphology is evident. Box-Behnken design (BBD), as an experimental design of the response surface method (RSM), is implemented to fit the model between variables and responses. The shell, infill density, and nozzle temperature are selected as variables, and their effects on loading stress, recovery stress, shape fixity, and shape recovery ratio are studied in detail. An analysis of variance (ANOVA) is applied to estimate the importance of each printing parameter on the output response and assess the fitness of the presented model. The ANOVA results reveal the high accuracy of the model and the importance of the parameters. Infill density and nozzle temperature had the greatest and least roles on shape memory properties, respectively. Also, the values of shape fixity and shape recovery were obtained in the ranges of 58–100% and 53–91%, respectively. Despite many researches on 4D printing of PLA, low ductility at room temperature and high stress relaxation rate are its weakness, which are covered by adding TPU in this research. Due to the lack of similar outcomes in the specialized literature, this paper is likely to fill the gap in the state-of-the-art problem and supply pertinent data that are instrumental for FDM 3D printing of functional shape memory polymers with less material consumption.</jats:p>