Experimentally guided MD simulation to enhance the shape memory behavior of polymer-based nanocomposites: Towards elaborating the underlying mechanism

• Published in: Composites. Part A, Applied science and manufacturing Vol. 138; p. 106055
• Main Authors: Amini, Mohammad, Hasheminejad, Kourosh, Montazeri, Abbas
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.11.2020
• Subjects: A. Graphene; A. Polymer–matrix composites (PMCs); A. Smart materials; Molecular dynamics simulations; A. Polymer–matrix composites (PMCs); Molecular dynamics simulations; A. Smart materials; A. Graphene
• ISSN: 1359-835X; 1878-5840
• DOI: 10.1016/j.compositesa.2020.106055

[Display omitted] We have probed the shape memory characteristics of Poly (D, L-lacticacid) matrix infused with graphene sheets via a combined numerical-experimental approach. Firstly, the shape memory behavior of the synthesized nanocomposite samples is inspected utilizing the DMA technique. It is demonstrated that despite the monotonic increase of the shape fixity ratio with the nanofiller loading, there exists a peak in the values of shape recovery at the optimum value of graphene content. In good agreement with our experimental measurements, molecular dynamics simulation approach yields the same optimum amount of graphene content. To explore the underlying mechanism, we further proceed to numerically analyze the variations of the conformational entropy, potential energy, and the radius of gyration during the whole procedure. The results reveal that while the shape fixity is significantly affected by both the potential energy and entropy changes, the shape recovery is only under the influence of the conformational entropy.