| People | Locations | Statistics |
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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Aberoumand, Mohammad
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (11/11 displayed)
- 20244D printing and annealing of PETG composites reinforced with short carbon fiberscitations
- 2024Influence of Programming and Recovery Parameters on Compressive Behaviors of 4D‐Printed Biocompatible Polyvinyl Chloride or Vinyl–Poly(ε‐Caprolactone) Blendscitations
- 2024Effects of TPU on the mechanical properties, fracture toughness, morphology, and thermal analysis of 3D-printed ABS-TPU blends by FDMcitations
- 20244D printing of porous PLA-TPU structures: effect of applied deformation, loading mode and infill pattern on the shape memory performancecitations
- 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
- 2022A New Strategy for Achieving Shape Memory Effects in 4D Printed Two-Layer Composite Structurescitations
- 2021Mechanical Characterization of Fused Deposition Modeling (FDM) 3D Printed Partscitations
- 20214D Printing by Fused Deposition Modeling (FDM)citations
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article
Influence of Programming and Recovery Parameters on Compressive Behaviors of 4D‐Printed Biocompatible Polyvinyl Chloride or Vinyl–Poly(ε‐Caprolactone) Blends
Abstract
<jats:p>In this article, a new class of biocompatible shape‐memory polymers (SMPs) through blending pcolyvinyl chloride or vinyl (PVC) and poly(ε‐caprolactone) (PCL) is introduced. The compressive shape‐memory behaviors of 4D‐printed SMP PVC with 5 and 10 wt% of PCL are studied in detail. In this respect, a set of experiments are carried out to understand thermomechanical responses of PVC–PCL blends under various shape‐memory parameters like programming temperature, load‐holding time, applied strain, and recovery temperature. Dynamic mechanical thermal analysis and scanning electron microscope imaging are also performed to provide thermal and morphological analyses. It is found that by raising the recovery temperature from 45 to 65 °C, the shape recovery ratio increases from 5.63 to 7.92 MPa when the PVC–PCL10 is programmed via the hot‐programming (HP) protocol. The highest level of shape fixity (100%) and the best performance of stress relaxation are achieved for HP sample, while the highest shape recovery ratio (100%) is obtained for cold programming. By applying the load‐holding time, the amount of shape fixity can reach from 88.14% to 100%. Results of this research are expected to provide an insightful understanding of the shape‐memory behaviors of PVC–PCL and be instrumental for 4D printing and programming of shape‐adaptive structures like shape‐memory intervertebral cages as spinal support devices.</jats:p>