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Multiscale Modeling of the Self-Organization Polymer Nanocomposites

YAYINLAR

Multiscale Modeling of the Self-Organization Polymer Nanocomposites

02.12.2023

Abstract
Controlling interfacial interactions is essential for the preparation of successful polymer matrix composites with enhanced properties. The performance of the polymers can be improved by 2D Material additives such as MXene, graphene and graphene oxide (GO) additives by achieving strong adhesion and uniform dispersion in the polymer matrix.
In the first part of this study, Density Functional Theory and molecular dynamics simulations were used to investigate interaction energies and Young’s Modulus values for epoxy resin and polyurethane based nanocomposites with graphene and graphene oxide additives. Improvement in the interaction energies was studied by control of the epoxy-amine ratio in epoxy resin and hard-soft segment type/ratio in polyurethanes, type and amount of oxygen-containing functional groups on the GO and mass percentage of filler. The objective of this study is to demonstrate the role of the amount and type of functional groups on the interaction energy and Young’s Modulus, and to determine effect of functional group on GO to maximize interaction with matrix.
In the second part, conducting polymers (CP)-2D material nanocomposites, that are ideal candidates for organic electronics such as sensors, photovoltaic cells and supercapacitors, were studied theoretically. The origin of self-organization, self-assembly and self-alignment of CPs on the 2D surface was not known at molecular level which limit their electronic applications. To understand the general rules and parameters for self-organization and self-alignment such as the presence of any directional preference of the conducting polymers on the 2D materials such as graphene and graphene oxide; first principle methods and molecular dynamics simulation studies were performed. To establish the principles of the self-organization on 2D materials, common CPs and representative molecules was selected from the experimental literature and structural optimizations were performed by using accurate first principle methods. We demonstrated that the origin of the self-alignment differences between conducting polymers can be explained based on the pi-stacking, structural patterns of 2D materials and distance fitting on these patterns.

Multiscale Modeling of the Self-Organization Polymer Nanocomposites

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