A Study of Morphology Formation Mechanism of Graphene Oxide Nanofillers in Polyurethane Matrix under Flow

Recent mesoscale computational techniques have efficiently built the relationship between microstructure and macroscopic properties of materials. This work presents an implementation of mesoscopic DPD (Dissipative Particle Dynamics) simulation to investigate the coalescence and dispersion of GO (graphene oxide) nanofillers in TPU (thermoplastic polyurethane) matrix under various processing conditions. The exfoliated morphology of GO agglomeration was discovered by increasing the shear rate over 20 s^-1. It was eligible to match the laboratory data. Except for the shear flow, the dispersion state of nanofillers was also dominated by the oxidation density. Changes from intercalation to exfoliation of GO only existed with a 40% oxidation degree at a favorable shear rate. The higher oxidation density surface of GO nanosheets adsorbed more TPU rigid segments. They created larger gaps in the agglomerates and resulted in the exfoliation eventually, as Herman’s orientation factor of attached polymer chains increased from -0.45 to 0 through raising Flory-Huggins χ parameters between GO and TPU. These surface-covered nanofillers were speculated to be the morphological origin of experimentally observed dispersion in processing. Additionally, the machine learning technique was applied to extend this consequence to a versatile phase diagram fitting into broader nanocomposite systems. Our findings can be employed as a guidance to design and fabricate polymeric nanocomposites.