Investigating the sliding behavior of graphene nanoribbons

TL;DR

This study develops a finite element model to analyze the sliding mechanics of graphene nanoribbons on substrates, revealing how boundary conditions, strain, and length influence interlayer interactions and energy dissipation.

Contribution

It introduces a calibrated FE model for GNR sliding behavior that aligns with MD simulations, highlighting critical length and strain parameters affecting interlayer mechanics.

Findings

Sliding behavior depends on GNR length and applied strain.

Critical GNR length for dissipation is approximately 10 nm.

Maximum transferable strain is between 0.59% and 1.15%.

Abstract

This work presents a Euler-Bernoulli beam finite element (FE) model to study the interlayer interaction mechanics of graphene nanoribbon (GNR) over a graphene substrate. The FE model is calibrated using molecular dynamics (MD) simulations employing the potential of Kolmogorov and Crespi. This study focuses mainly on the effect of boundary conditions on sliding behavior and strain transfer between layers when the substrate is subjected to uniform biaxial deformations. The interlayer shearing or sliding behavior is found to depend on the presence of critical parameters, namely, the applied strain to the substrate and the length of the GNR. The FE results indicate that the applied strain transferred from the substrate to the GNR varies linearly up to a critical value ec beyond which it decreases suddenly. Further, ec is found to appear beyond a critical GNR length, Le is approximately 14 nm. Furthermore, a length parameter Ld is approximately 10 nm is computed, beyond which the sliding of GNR is dissipative. Through FE simulations, it is also found that for a GNR length is greater than or equal to 17 nm, the edge pulling force saturates. Our results also highlight the importance of the inertia of GNR on its sliding for different boundary conditions. It is also concluded that the maximum strain that can be transferred to GNR lies between 0.59% and 1.15%. The results of the FE approach align with MD simulations within an error of approximately 10% that can be attributed to the choice of material parameters and the simulation setup.