Investigating the sliding behavior of graphene nanoribbons

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 (2005). This study focuses mainly on the effect of boundary conditions on the sliding behavior, and on the strain transfer between layers when the substrate is subjected to uniform biaxial deformations. The interlayer sliding behavior is found to depend on the presence of critical parameters, namely, the length of the GNR and the applied strain to the substrate. The FE results indicate that the applied strain transferred from the substrate to the GNR varies linearly up to a critical value ϵ c beyond which it decreases suddenly. Further, ϵ c is found to appear beyond a critical GNR length, L e ≈ 14 nm. Furthermore, a length parameter L d ≈ 10 nm is computed, beyond which the sliding of GNR is dissipative. Through FE simulations, it is also found that for a GNR length ≥ 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.

Authors

Institutions

Publication Details

Journal
Carbon
Published
2025-11-13
DOI
https://doi.org/10.1016/j.carbon.2025.121056
Primary Topic
Graphene research and applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Investigating the sliding behavior of graphene nanoribbons

Roger A. Sauer, Shakti S. Gupta, Gulab Singh Yadav, Aningi Mokhalingam
Carbon
Graphene research and applications
article

Investigating the sliding behavior of graphene nanoribbons

Roger A. Sauer, Shakti S. Gupta, Gulab Singh Yadav, Aningi Mokhalingam
article en

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 (2005). This study focuses mainly on the effect of boundary conditions on the sliding behavior, and on the strain transfer between layers when the substrate is subjected to uniform biaxial deformations. The interlayer sliding behavior is found to depend on the presence of critical parameters, namely, the length of the GNR and the applied strain to the substrate. The FE results indicate that the applied strain transferred from the substrate to the GNR varies linearly up to a critical value ϵ c beyond which it decreases suddenly. Further, ϵ c is found to appear beyond a critical GNR length, L e ≈ 14 nm. Furthermore, a length parameter L d ≈ 10 nm is computed, beyond which the sliding of GNR is dissipative. Through FE simulations, it is also found that for a GNR length ≥ 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.

CarbonVol. 247
Indian Institute of Technology Guwahati (IN), Gdańsk University of Technology (PL), University of Gdańsk (PL), Ruhr University Bochum (DE), Maulana Azad National Institute of Technology (IN), Indian Institute of Technology Kanpur (IN)
Openalex Percentile: Top 72%
Graphene research and applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.