Abstract
Thermoplastic polyurethanes (TPU) exhibit as multipurpose materials with diverse industrial applications. Meanwhile, owing to the brittleness and aging properties of neat TPU which severely limits its applications, the nanofillers were incorporated into the matrix to improve its physical properties. This can be attributed to the enriched interfacial interactions between the TPU moiety and the vastly reactive nanofiller hence the interpretation of interaction properties of the host-guest complex is highly constructive. Quantum mechanics-based molecular simulations was used to evaluate the structural, energetic, interaction nature, and mechanical properties of reinforced graphene oxide (GO) as potent nanofiller in the TPU matrix. Density functional theory-based calculations showed that TPU exhibited strong interaction with GO functional groups at the edge and on the surface, with interaction energies of − 35.303 and − 39.098 kcal/mol, respectively. The atominmolecule analysis indicated the existence of numerous hydrogen bonds between the GO nanofiller and TPU matrix in the nanocomposite. Reactive molecular dynamics simulations are used in the present study for the first time to examine the structural and mechanical properties of the TPU matrix and TPU/GO nanocomposite. Accuracy of reactive forcefield ReaxFF for physical and mechanical property estimations are validated against the reported experiments for the graphene system. It was found that the incorporation of GO (18 wt%) resulted in an increased Young’s modulus by about 34% (from 281 GPa for TPU to 378 GPa for TPU/GO). The charge analysis using the ReaxFF approach showed a significant charge transfer (3.483 e) from the TPU matrix to the GO skeleton. All these reveal the strong binding of GO to the TPU molecular chain in the nanocomposite, improving its physical and mechanical properties. Our comprehensive molecular simulations provide a well-grounded understanding of the interfacial interactions and mechanical properties of the nanofiller-reinforced polymer matrix. The present implemented computational methods and obtained results provide helpful information for the design and improvement of TPU/Graphene-based nanocomposites for potential applications in a new class of environmentally friendly shape memory materials.
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