Probing the Influence of Surface Chemical Functionalization on Graphene Nanoplatelets-Epoxy Interfacial Shear Strength Using Molecular Dynamics

Abstract

In this work, a characterization study of the interfacial interaction between different types of graphene nanoplatelets and an epoxy matrix is computationally performed. To quantify the discrete mutual graphene–epoxy “interfacial interaction energy” (IIE) within the nanocomposite, molecular dynamics simulations with a reactive force field are performed on a localized model of the suggested nanocomposite. Pull-out molecular dynamics simulations are also performed to predict the interfacial shear strength between the two constituents. The results indicate a significant increase in interfacial adhesion of functionalized nanoplatelets with the hosting epoxy matrix relative to virgin graphene nanoplatelets. The obtained results also demonstrate a dramatic increase in the interfacial interaction energy (IIE) (up to 570.0%) of the functionalized graphene/epoxy nanocomposites relative to the unmodified graphene/epoxy nanocomposites. In the same context, the surface functionalization of graphene nanoplatelets with the polymer matrix leads to a significant increase in the interfacial shear strength (ISS) (up to 750 times). The reported findings in this paper are essential and critical to producing the next generation of lightweight and ultra-strong polymer-based nanocomposite structural materials.

Simple and convenient mapping of molecular dynamics mechanical property predictions of bisphenol-F epoxy for strain rate, temperature, and degree of cure

“…1 These relaxation processes can occur over a wide range of time periods spanning nanoseconds to years, but a significant portion of them occur over timescales associated with composite laminate processing and laboratory mechanical testing. Although all-atom MD simulations have been used over the last several decades to predict molecular structure and nano-scale properties of thermoset resins, [2][3][4][5][6][7][8][9][10][11][12][13][14][15][16] these simulations can only capture the thermoset network response over a nanosecond time scale, creating a significant discrepancy between simulated and laboratory timescales. Although coarsegrain simulation techniques [17][18][19][20][21] can be used to somewhat avert the time scale limitation over a broad range of frequencies, atomistic details often play a more significant role at higher frequencies.…”