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Shape Memory Behavior of 3D-Printed Biomedical Polyurethane with Room Temperature Transition

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Abstract:

Shape memory polymers (SMPs) can recover from a programmed temporary shape to their original configuration when exposed to an external stimulus, most commonly heat, making them attractive materials for soft actuation in functional and biomedical devices. Among them, thermoplastic polyurethanes (TPUs) display reliable shape-memory behavior under various conditions. The emergence of biomedical-grade TPUs and their compatibility with additive manufacturing provides new opportunities for fabricating customized components with tunable actuation capabilities. In this study, biomedical TPU filaments were processed via fused deposition modeling (FDM) to produce block-shaped specimens of controlled size and weight. The samples were mechanically deformed into a C-shaped geometry at room temperature, fixed in fridge at the temperature of –20 °C, and subsequently tested under constrained recovery at room conditions, using a universal testing machine. The recovery load has been measured for a time of 30 min. The results show that TPU-based SMPs can develop substantial recovery forces during shape restoration. The shape memory behavior has been modeled by using a logistic function, which has been able to identify a characteristic time, the same for all the samples despite their printing conditions and architecture. These findings highlight the potential of FDM-processed biomedical TPUs for compact soft-actuation systems requiring high force output.

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Periodical:

Materials Science Forum (Volume 1187)

Pages:

45-54

DOI:

https://doi.org/10.4028/p-GJcp8x

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Cite this paper

Online since:

April 2026

Authors:

Denise Bellisario*, Leandro Iorio, Alice Proietti, Dounia Noqra, Giorgio Patrizii, Fabrizio Quadrini, Loredana Santo

Keywords:

3D Printing, Biomedical Polyurethane, Shape Memory Polymers

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* - Corresponding Author

References

[1] R. Zende, V. Ghase, V. Jamdar, A review on shape memory polymers, Polym. Technol. Mater. 62 (2023) 467–485.

DOI: 10.1080/25740881.2022.2121216

Google Scholar

[2] Y. Zhu, J. Hu, Y. Liu, Shape memory effect of thermoplastic segmented polyurethanes with self-complementary quadruple hydrogen bonding in soft segments, Eur. Phys. J. E 28 (2009) 3-10.

DOI: 10.1140/epje/i2008-10395-2

Google Scholar

[3] F. Ji, J. Li, Y. Weng, J. Ren, Synthesis of PLA-based thermoplastic elastomer and study on preparation and properties of PLA-based shape memory polymers, Mater. Res. Express 7 (2020) 015315.

DOI: 10.1088/2053-1591/ab61a8

Google Scholar

[4] M. R. Pfau, K. G. McKinzey, A. A. Roth, M. A. Grunlan, PCL-based shape memory polymer semi-IPNs: the role of miscibility in tuning the degradation rate, Biomacromolecules 21 (2020) 2493–2501.

DOI: 10.1021/acs.biomac.0c00454

Google Scholar

[5] K. Kojio, M. Furukawa, Y. Nonaka, S. Nakamura, Control of mechanical properties of thermoplastic polyurethane elastomers by restriction of crystallization of soft segment, Materials 3(2010) 5097–5110.

DOI: 10.3390/ma3125097

Google Scholar

[6] A. Boubakri, N. Haddar, K. Elleuch, Y. Bienvenu, Impact of aging conditions on mechanical properties of thermoplastic polyurethane, Mater. Des. 31 (2010) 4194–4201.

DOI: 10.1016/j.matdes.2010.04.023

Google Scholar

[7] J. Datta, P. Kasprzyk, Thermoplastic polyurethanes derived from petrochemical or renewable resources: A comprehensive review, Polym. Eng. Sci. 58 (2018) E14 - E35.

DOI: 10.1002/pen.24633

Google Scholar

[8] A. Mishra, K. Seethamraju, J. Delaney, P. Willoughby, R. Faust, Long‐term in vitro hydrolytic stability of thermoplastic polyurethanes, J. Biomed. Mater. Res. Part A 103 (2015) 3798–3806.

DOI: 10.1002/jbm.a.35523

Google Scholar

[9] D. Cozzens, U. Ojha, P. Kulkarni, R. Faust, S. Desai, Long term in vitro biostability of segmented polyisobutylene‐based thermoplastic polyurethanes, J. Biomed. Mater. Res. Part A 95A (2010), 774–782.

DOI: 10.1002/jbm.a.32897

Google Scholar

[10] H.-Y. Mi, X. Jing, B. N. Napiwocki, B. S. Hagerty, G. Chen, L.-S. Turng, Biocompatible, degradable thermoplastic polyurethane based on polycaprolactone-block-polytetrahydrofuran-block-polycaprolactone copolymers for soft tissue engineering, J. Mater. Chem. B 5 (2017) 4137–4151.

DOI: 10.1039/c7tb00419b

Google Scholar

[11] R. Al Nakib, A. Toncheva, V. Fontaine, J. Vanheuverzwijn, J. Raquez, F. Meyer, Thermoplastic polyurethanes for bi-omedical application: A synthetic, mechanical, antibacterial, and cytotoxic study, J. Appl. Polym. Sci. 139 (2022).

DOI: 10.1002/app.51666

Google Scholar

[12] M.-S. M'Bengue, T. Mesnard, F. Chai, M. Maton, V. Gaucher, N. Tabary, M.-J. García-Fernandez, J. Sobocinski, B. Martel, N. Blanchemain, Evaluation of a medical grade thermoplastic polyurethane for the manufacture of an implantable medical device: the impact of FDM 3D-printing and gamma sterilization, Pharmaceutics 15 (2023) 456.

DOI: 10.3390/pharmaceutics15020456

Google Scholar

[13] S. Kumar, R. Singh, A.P. Singh, Y. Wei, Three-dimensional printed thermoplastic polyurethane on fabric as wearable smart sensors, Proc. Inst. Mech. Eng. Part L J. Mater. Des. Appl. 237 (2023) 1678–1692.

DOI: 10.1177/14644207221149693

Google Scholar

[14] S. Lepak-Kuc, B. Podsiadły, A. Skalski, D. Janczak, M. Jakubowska, A. Lekawa-Raus, Highly Conductive carbon nanotube-thermoplastic polyurethane nanocomposite for smart clothing applications and beyond, Nanomaterials 9 (2019) 1287.

DOI: 10.3390/nano9091287

Google Scholar

[15] P. Awasthi, S. S. Banerjee, Construction of stimuli-responsive and mechanically-adaptive thermoplastic elastomeric materials, Polymer (Guildf). 259 (2022) 125338.

DOI: 10.1016/j.polymer.2022.125338

Google Scholar

[16] Y. Zan, M. Piedrahita-Bello, S. E. Alavi, G. Molnár, B. Tondu, L. Salmon, A. Bousseksou, Soft actuators based on spin‐crossover particles embedded in thermoplastic polyurethane, Adv. Intell. Syst. 5 (2023).

DOI: 10.1002/aisy.202200432

Google Scholar

[17] C. Li, H. Xia, J. Yao, Q.-Q. Ni, Electrically induced soft actuators based on thermoplastic polyurethane and their actuation performances including tiny force measurement, Polymer (Guildf). 180 (2019) 121678.

DOI: 10.1016/j.polymer.2019.121678

Google Scholar

[18] O. Yasa, Y. Toshimitsu, M.Y. Michelis, L. Jones, M. Filippi, T. Buchner, R.K. Katzschmann, An overview of soft robotics, Annu. Rev. Control. Robot. Auton. Syst. 6 (2023) 1–29.

DOI: 10.1146/annurev-control-062322-100607

Google Scholar

[19] C. Lee, M. Kim, Y.J. Kim, N. Hong, S. Ryu, H.J. Kim, S. Kim, Soft robot review. Int. J. Control. Autom. Syst. 2017, 15, 3–15.

DOI: 10.1007/s12555-016-0462-3

Google Scholar

[20] F.B. Koehler, T.M. Sanderson, D.L. Safranski, K. Gall, V. Jaker, J. Orrock, C. Holshauser, 3D printing of thermoplastic polyurethane shape memory polymer, In CamX: Composites and Advanced Materials Expo (2015) 2231–2245.

Google Scholar

[21] L. Ritzen, V. Montano, S.J. Garcia, 3D printing of a self-healing thermoplastic polyurethane through FDM: from polymer slab to mechanical assessment, Polymers, 13(2) (2021) 305.

DOI: 10.3390/polym13020305

Google Scholar

[22] D. Rigotti, A. Dorigato, A. Pegoretti, 3D printable thermoplastic polyurethane blends with thermal energy storage/release capabilities, Mater. Today Commun 17 (2018). 54–60.

DOI: 10.1016/j.mtcomm.2018.03.009

Google Scholar

[23] D.B. Rahmatabadi, L. Brasileiro Quirino Brito, R. B. Cunha, P. Agrawal, G. de Figueiredo Brito, 4D printing of shape memory polyethylene terephthalate glycol/thermoplastic polyurethane (PETG/TPU) blends, J. Manuf. Process. 119 (2024) 596-608.

DOI: 10.1016/j.jmapro.2024.04.017

Google Scholar

[24] B. Peng, X. Wang, M. Zhang, Fused Filament Fabrication 4D Printing of a Highly Extensible, Shape-Memory and Self-Healing Polymer Blend, ACS Appl. Mater. Interfaces. 12(42), (2020) 47018–47027.

DOI: 10.1021/acsami.0c18618

Google Scholar

[25] I. Jung, K. Jung, Shape recovery properties of 3D printed re-entrant strip using shape memory thermoplastic polyurethane (SMTPU), Fash. Text. 10 (2023), 48.

DOI: 10.1186/s40691-023-00348-6

Google Scholar

[26] E.M. Arruda, M.C. Boyce, R. Jayachandran, Effects of strain rate, temperature and thermomechanical coupling on the finite strain deformation of glassy polymers, Mech. Mater, 19 (1995) 193–212.

DOI: 10.1016/0167-6636(94)00034-e

Google Scholar

[27] Y. Liu, K. Gall, M. L. Dunn, A. R. Greenberg, J. Diani, Thermomechanics of shape memory polymers: uniaxial experiments and constitutive modeling, Int. J. Plast22, (2006) 279–313.

DOI: 10.1016/j.ijplas.2005.03.004

Google Scholar

[28] J. Diani, B. Fayolle, P. Gilormini, A review on the thermomechanical behaviour of shape memory polymers, Eur. Polym. J48 (2012) 1387–1402.

Google Scholar

[29] T.D. Nguyen, H.J. Qi, F. Castro, K.N. Long, A thermoviscoelastic model for amorphous shape memory polymers: Incorporating structural and stress relaxation, Mech. Phys. Solids 56 (2008) 2792–2814.

DOI: 10.1016/j.jmps.2008.04.007

Google Scholar

[30] Y. Chen, D. C. Lagoudas, A constitutive theory for shape memory polymers. Part I: Large deformation thermomechanics, Mech. Phys. Solids 56 (2008) 1752–1765.

DOI: 10.1016/j.jmps.2007.12.005

Google Scholar

[31] H.J. Qi, T.D. Nguyen, F. Castro, C.M. Yakacki, R. Shandas, Finite deformation thermomechanical behavior of thermally induced shape memory polymers, Mech. Phys. Solids 56, (2008) 1730–1751.

DOI: 10.1016/j.jmps.2007.12.002

Google Scholar

[32] C. M. Yakacki, R. Shandas, D. Safranski, A. M. Ortega, K. Sassaman, K. Gall, Strong, tailored, biocompatible shape-memory polymer networks, Adv. Funct. Mater 18(2008) 2428–2435.

DOI: 10.1002/adfm.200701049

Google Scholar

[33] E. Ghobadi, M. Elsayed, R. Krause-Rehberg, H. Steeb, Demonstrating the influence of physical aging on the functional properties of shape-memory polymers, Polymers 10(2) (2018)107.

DOI: 10.3390/polym10020107

Google Scholar

[34] E.W. Weisstein, Logistic equation. In MathWorld—A Wolfram Web Resource. Retrieved February 11, 2026, from https://mathworld.wolfram.com/LogisticEquation.html.

Google Scholar

[35] L. Burratti, D. Bellisario, F. Quadrini, L. Iorio, L. Santo, 3D printing of soft actuators in nano-filled shape memory thermoplastic polyurethane, Mater. Res. Proc 54 (2025) 2047.

DOI: 10.21741/9781644903599-220

Google Scholar