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Explores thermomechanical response in acrylate-based polymers, indicating nanoparticle benefits for performance.
Shape memory polymer (SMP) nanocomposites demonstrate significantly enhanced functional capabilities relative to conventional SMPs, primarily due to the deliberate integration of nanoparticles. In this context, aluminum oxide nanoparticles (Al 2 O 3 NPs) emerge as highly effective reinforcements due to their exceptional mechanical robustness, thermal/chemical stability, compatibility with polymers, and widespread availability. This study aims to elucidate the role of Al 2 O 3 NPs in governing the thermomechanical response of acrylate-based SMPs, with particular emphasis on microstructural morphology and defect-mediated mechanisms. To this end, the SMP matrix is defined within a thermo-visco-hyperelastic constitutive framework, in which the material response is governed by the coupled contributions of thermal expansion, viscoelastic relaxation governed by the time-temperature superposition principle, and hyperelastic deformation. Based on micromechanical principles, a morphology-informed computational simulation is implemented to generate representative volume elements (RVEs), facilitating explicit representation of microstructural features and prediction of macroscopic behavior. Thermomechanical analysis is conducted using a finite element solver under cyclic stress-free shape recovery and stress reactivation at constant strain, following a five-step thermomechanical sequence comprising preheating, loading, cooling, unloading, and heating. The findings reveal that Al 2 O 3 NP content, geometry, and dispersion state, together with microstructural imperfections, significantly influence the shape memory behavior. Uniform dispersion of Al 2 O 3 NPs is shown to enhance shape memory behavior, with increased concentration and reduced size promoting improved actuation responsiveness. In contrast, agglomeration and voids are identified as detrimental to performance; however, their adverse effects can be partially mitigated through strategies such as cluster disruption and void size reduction.
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Moradi et al. (2026) studied this question.
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