Multiscale Study of Shape-Memory Behavior of Semicrystalline Polyurethane Nanocomposites Doped with Silica Nanoparticles Based on Coarse-Grained Molecular Dynamics Simulation

Abstract

The thermo-mechanical behavior of shape-memory polyurethane (SMPU)-silica nanocomposites is studied. We propose a coarse-grained (CG) molecular dynamics (MD) model and capture atomic-level interactions, focusing on the interfacial region between the polymer matrix and nanoparticles. The shape-memory performances are evaluated according to the hard segment content (HSC) of the SMPU matrix and the weight percentage of nanoparticles. The study reveals that elevated silica contents trigger nanoparticle clustering, degrading the shape recovery. Additionally, HSC affects the matrix-nanoparticle compatibility and determines the degree of nanoparticle agglomeration and shape-memory properties. These findings contribute to designing deformations in semicrystalline shape-memory polymer nanocomposites and actuators.