Thermo-mechanical viscoelastic characterization and modeling of 4D printed shape memory polymers
The majority of existing literature focuses on the characterization and modeling of conventionally synthesized shape memory polymers (SMPs). This work presents a detailed systematic thermo-viscoelastic characterization framework required for modeling 4D printed structures. Initially, the thermal properties were investigated to understand the behavior of the 4D-printed SMP under varying temperatures. Subsequently, thermo-viscoelastic experiments were conducted at various strain rates under tension and compression, covering temperature ranges from 25°C to 65°C. These tests revealed a strong dependency of mechanical behavior on both time and temperature. The stress-strain plots of the test temperature below the glass transition temperature demonstrated a clear yield point followed by a post-yield stress-softening. Under room temperature testing, a lower failure strain of ∼4 % was recorded at the fastest strain rate of 0.1/s. Moreover, temperature sweep, stress relaxation, creep, coefficient of thermal expansion (CTE) and strain-controlled shape memory tests were performed using a dynamic mechanical analyzer (DMA). A shape fixity of ∼97 % and a recovery ratio of ∼99 % was obtained in the shape memory tests. Finally, the experimental results were successfully utilized to calibrate a thermo-viscoelastic model from the literature. The shape memory effects were predicted with reasonable agreement with the test data. The findings of this study can be used in the development of complex, intricate 4D structures, providing deeper insights into their design. • Thermo-viscoelastic characterization of 4D-printed shape memory polymer was conducted. • Isothermal tensile and compression tests were performed at various strain rates. • Stress relaxation, creep, and shape memory cyclic characterization were carried out. • Experimental characterization was utilized in thermo-viscoelastic constitutive modeling. • Stretch recovery ratio was accurately predicted in comparison to thermo-mechanical tests.
Authors
- Siddhesh S. Kulkarni
- Israr Ud Din
- Kamran A. Khan (ORCID: https://orcid.org/0000-0003-1817-6947)
Institutions
- Khalifa University of Science and Technology (AE)
Publication Details
- Journal
- Polymer Testing
- Published
- 2025-01-16
- DOI
- https://doi.org/10.1016/j.polymertesting.2025.108708
- Citations
- 10
- Primary Topic
- Polymer composites and self-healing
- Type
- article
- Field-Weighted Citation Impact
- 6.07
Funders
- Khalifa University of Science, Technology and Research