A Molecular Dynamics Study of Energy Minimization in Mono- and Bilayer Graphene Structures

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A Molecular Dynamics Study of Energy Minimization in Mono- and Bilayer Graphene Structures Tatva Kabat¹ 1The Academy for Math, Science, and Engineering, Rockaway, New Jersey, USA

---------------------------------------------------------------------***--------------------------------------------------------------------to graphene’s high aspect ratio and two-dimensionality, it Abstract - In current materials science research, graphene

can also be used as a building block for other carbonbased nanostructures like fullerenes or carbon nanotubes [4]. Graphene’s wide range of applications like highperformance composites and flexible electronics are all rooted in its atomic configuration, which has led to various research efforts trying to understand graphene’s structural stability under various conditions.

remains at the forefront of current studies due to its potential applications in future healthcare, electronics, and construction industries. This study aims to utilize energy minimization in order to determine stable configurations of monolayer and bilayer graphene, showing that altering atomic properties such as bond length and bilayer gap distance would generate more stable configuration of graphene structures, indicated with minimizing the inner potential energy of each graphene structure. By conducting simulations using the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS), atomic interactions were modeled within graphene structures (all under the AIREBO potential). Graphene structures were visualized using OVITO and plot data extracted from simulation log files via Python. Simulations were tested with varying bond lengths from 1.20-1.70 Å and bilayer gap distances 2.00 Å and 4.00 Å to observe convergence behavior of the structures as they evolved in our simulations. The results confirmed that the optimal bond length for monolayer graphene is approximately 1.42 Å, while bilayer systems consistently minimized to an interlayer spacing near 3.48 Å, with those values aligning with existing theoretical and experimental literature. This study aims to show how changes on the atomic level can greatly enhance the stability of graphene structures and its results can be used to optimize graphene for future applications in nanotechnology and advanced materials science.

As previously mentioned, each carbon atom in a graphene sheet is sp² hybridized, forming three rigid σbonds with adjacent carbon atoms and one π-bond contributing to delocalized electron mobility across the sheet [1,2]. This configuration of atoms creates a symmetrical hexagonal lattice characterized by an ideal C– C bond length of 1.42 Å, a value confirmed through both experimental methods and computational simulations [1,5]. The C-C bond length directly affects both the energetic stability of a graphene system and also its mechanical performance, making it a primary target in energy minimization studies like ours [6,7].

Minor deviations from this ideal bond length of 1.42 Å increase system energy due to bond strain. Defects such as Stone–Wales transformations or vacancies in a graphene sheet further elevate system potential energy and degrade material properties, often by 4.8–7 eV depending on the defect [4,8]. Edge terminations such as hydrogensaturated edges in graphene nanoflakes help reduce total energy and suppress unwanted mid-gap states, since unsaturated or disordered edges destabilize the structure [6].

Key Words: Materials Science, Graphene, Molecular Dynamics, LAMMPS, Energy Minimization

1.INTRODUCTION

These previous research findings show the importance of atomic-scale factors such as bond length, hybridization, edge termination, and defects in graphene’s stability.

These basic properties establish the energetic foundation for larger graphene systems, like bilayer graphene, where interlayer spacing and sheet orientation create more complex energetic challenges.

Graphene is a single-atom thick sheet of carbon atoms arranged in a two-dimensional hexagonal lattice, and its physical characteristics such as exceptional electrical and thermal conductivity, mechanical and tensile strength, and optical transmittance make it one of the most researched materials in modern materials science [1,2]. The study of these individual properties have been widely studied since graphene’s isolation in 2004.

Bilayer graphene (BLG) introduces more complexity through interlayer van der Waals (vdW) forces, weak attractive forces between atoms close together, and stacking orientation (how layers are stacked on top of each other). Experimental and computational tests have determined the ideal BLG gap to be around 3.35 Å, found

Due to graphene’s strong in-plane σ-bonds and delocalized π-electrons, formed as a result of the material’s sp² hybridized carbon atoms, it has broad structural and electronic behavior [1,3]. Furthermore, due

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2. METHODS AND RESULTS

in graphite and supported by molecular dynamics (MD) studies using AIREBO and similar force fields [7,9,10].

Precisely controlling this BLG gap in MD studies is necessary in order to maximize graphene’s high electronic and thermal performance during studies [11].

2.1 Simulations and Trials All MD simulations for our trials were performed using the LAMMPS software package. Input script files, atomic data files, and the AIREBO potential files were provided by NJIT researchers. For The simulations modeled both monolayer and bilayer graphene and data files were generated/modified using MATLAB. All simulations utilized the “metal” function for units in LAMMPS to report energy in eV, distance in Å, and time in picoseconds with the function being common for MD simulations involving carbon-based materials. The boundary was set to the “p p p” function and was used to create periodic boundaries in all directions (x,y,z). Finally, the atom style was set as “atomic” to specify that each atom had no charge or intrinsic attributes aside, ensuring normal carbon atoms were used for each trial.

Aside from its hexagonal lattice structure, graphene’s properties are also a result of its delocalized π-electron system and the two-dimensional arrangement of its carbon atoms. These characteristics, particularly the delocalized π-electron system, allow for efficient charge transport, thermal conductivity, and mechanical performance in graphene, making it a versatile candidate for next-gen materials [1,2]. One such use comes in graphene’s flexibility and conductivity, fueling its applications in sensors, transparent electrodes, and other optoelectronic technology [2]. Another comes in graphene’s high specific surface area and structural stability under various conditions, making it useful for future supercapacitor and battery electrode development [12,13]

For the monolayer trials, sheets of 400 carbon atoms were generated each with varying x and y positions based on the bond length of the trial. Z positions were kept constant to maintain two-dimensionality. Each simulation was run for 10,000 timesteps, and atomic positions as well as thermodynamic properties for the sheet were updated every 100 steps in the log file.

To fully understand graphene’s energetic stability at the atomic level, especially within BLG systems, computational molecular dynamics (MD) simulations provide both an accurate and alternative approach to experimental trials.

Unlike purely analytical models, MD simulations for the tracking of atomic trajectories over time and the analysis of the energy minimization process, lattice changes, and intermolecular interactions under various mechanical and thermal conditions. The Adaptive Intermolecular Reactive Empirical Bond Order (AIREBO) potential has become popular in modeling carbon-based materials in particular, as it not only captures covalent bonding, but also nonbonded interactions like vdW forces [5,14]. The AIREBO potential’s ability to simulate both intra and interlayer carbon interactions make it ideal for investigating both monolayer and bilayer graphene systems.

For the bilayer trials, two sheets with 100 carbon atoms each were generated with x and y positions of two atoms being identical for the stacking of the sheets in an AA format. The z positions of each sheet were varied depending on the initial BLG gap distance. The AIREBO potential was applied using the “pair_style airebo” and “pair_coeff” commands to model the interatomic forces and weak van der Waals interactions accurately. For the simulations, the simulation box was made flexible using the “box/relax” fix to allow for out-of-plane relaxation and to minimize internal stress without applying external pressure. A variable was defined to track the minimum and maximum z-positions of all carbon atoms, and a custom “thermo_style” output was used to monitor the system’s potential energy, temperature, and vertical (zdirection) gap during each run.

Our study aims to identify energy-minimized configurations of mono- and bilayer graphene by testing varying bond lengths and interlayer spacing configurations in MD simulations. We hypothesized that each graphene system would converge toward a specific structural configuration corresponding to the lowest potential energy, adjusting its atomic characteristics in order to reach its most stable state. Our results confirmed the atomic properties of graphene such as an approximate 1.42 Å C-C bond length and a 3.48 Å BLG gap distance, demonstrating that graphene's stability can be computationally verified and optimized. Along with its discoveries, the results of our study could provide important insights for the continued development of graphene-based materials in nanotechnology and advanced engineering applications.

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2.2 Data Visualization and Graphing To visualize both the monolayer and bilayer structures, the .cfg files from each simulation were input into the Open Visualization Tool software (OVITO). OVITO allowed for the visualization of the dump data from the LAMMPS trials, and playing through the .cfg files showed the expansion/compression of bond lengths and BLG gap distance in the structures.

Graphs for each trial were generated by extracting the data from the .log files generated by each LAMMPS trial.

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Python scripts were run on VS Code with the OS, NumPy, and Matplotlib libraries in order to graph trends.For the monolayer trials, data extracted from the .log files from the energy minimization and dynamic bond length relaxation trials was plotted to generate potential energy (eV) vs bond length (Å) and bond length (Å) vs. step graphs. Similarly, for the bilayer trials, data extracted from the .log files from the energy minimization and convergence analysis trials were plotted to generate potential energy (eV) vs. bilayer gap distance (Å) and bilayer gap distance (Å) vs. step graphs.

All scripts and simulation files used for our research have been uploaded to GitHub and are accessible to replicate our results at: Chart 1: Potential energy vs. bond length in monolayer graphene

https://github.com/tatvakabat/A-Molecular-DynamicsStudy-of-Energy-Minimization-in-Mono--and-BilayerGraphene-Structures

To verify the experimental bond length of 1.42 Å identified in the static energy minimization trials, we performed dynamic bond length relaxation simulations using LAMMPS. Starting once again from initial bond lengths of 1.20-1.70 Å (in 0.1 Å increments), each graphene sheet was put into a molecular dynamics relaxation simulation over time. The AIREBO force field was once again used to model for realistic C–C bonding behavior, while interatomic interactions were updated dynamically as the system evolved toward equilibrium.

2.3 Results To test our hypothesis, we conducted various energy minimization trials of both monolayer and bilayer graphene systems, setting initial characteristics such as bond length and BLG gap distance and allowing each system to relax towards its most stable configuration, minimizing the potential energy of the system.

During each simulation, the system was allowed to relax under the NVE ensemble (constant number of particles, volume, and energy), with in-plane box relaxation enabled in the x and y directions, allowing the lattice itself to contract or expand in response to internal stress from non-equilibrium bond lengths. Atomic positions and other properties (pressure, potential energy, bond distances) were tracked in each system at regular intervals.

To identify the most energetically favorable bond length in a monolayer graphene sheet, a series of energy minimization trials were conducted in LAMMPS. The Adaptive Intermolecular Reactive Empirical Bond Order (AIREBO) potential was selected to model covalent C–C bonding and nonbonded interactions within the graphene lattice. Structures were initialized with varying bond lengths, with a fixed z-coordinate for two-dimensionality, between 1.20 Å to 1.70 Å, and the system was allowed to relax under a convergence tolerance of 1e-8 for energy and 1e-9 for force.

The changing of bond lengths over simulation steps demonstrates clear convergent behavior across all initial configurations towards graphene’s ideal bond length of 1.42 Å (Chart 2). When visualized in OVITO, the sheet with a starting bond length of 1.20 Å expanded towards the ideal bond length of 1.42 Å (Figure 1). Similarly, for the starting bond length of 1.7 Å, we saw the compression of carbon atoms in the graphene sheet to reach the ideal bond length of 1.42 Å (Figure 2). This behavior in both sheets confirms that graphene’s bonding energetics favor this equilibrium spacing, where internal stress is minimized for a stable structure.

The resulting potential energy values from each structure after every trial was plotted as a function of bond length, with the potential energy steeply decreasing from 1.20 Å, reaching a minimum near 1.40–1.42 Å before increasing again at longer bond lengths (Chart 1). This parabolic energy profile reflects the balance between repulsive interactions at short distances and weakened bonding at extended distances with the minimum indicating the bond length at which the system reaches its most energetically favorable and stable configuration.

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approximately –1490 eV, despite beginning at different energy states (Chart 3). The system initialized at 4.00 Å began at a lower potential energy (–1488 eV), while the 2.00 Å system started at a much higher energy (–700 eV), due to interlayer compression and increased repulsion, and by the end of the simulation, both structures approached an interlayer spacing near 3.40–3.50 Å, confirming this range as the energetically minimized configuration (Chart 3).

Chart 2: Bond length relaxation during energy minimization

Chart 3: Potential energy convergence in bilayer graphene with different initial gaps= Similar to the monolayer trials, a convergence analysis was used to confirm the ideal bilayer spacing observed in the energy minimization trials, tracking the BLG gap over the course of the simulation steps. Two BLG systems with initial vertical gaps of 2.00 Å and 4.00 Å were simulated to determine how each structure changed as it approached equilibrium spacing under the AIREBO potential.

Figure 1: Expansion of monolayer graphene from a compressed state (1.2 Å)

Both systems dynamically adjusted their interlayer spacing and ultimately converged toward a common value of approximately 3.40 Å, consistent with the energy minimization results (Chart 4). The structure initialized at 4.00 Å began closer to this equilibrium value and reached it significantly faster. In contrast, the 2.00 Å system required ~5,000 additional steps to reach the same final spacing, due to its initially compressed configuration and higher potential energy (Chart 4). This was once again consistent with the energy minimization trial, as the initial 4.00 Å gap was much closer to the equilibrium gap of 3.40 Å (0.60 Å off equilibrium) compared to the initial 2.00 Å gap (1.6 Å off equilibrium).

Figure 2: Compression of monolayer graphene from an extended state (1.7 Å) To find the BLG gap distance that corresponded to the most energetically favorable state, similar energy minimization simulations were once again conducted using LAMMPS, this time using BLG structures. Two graphene bilayer systems were initialized with gaps of 2.00 Å and 4.00 Å between the graphene sheets, chosen to evaluate convergence from both compressed and extended starting geometries. The AIREBO potential was used to account for covalent intralayer bonding and weak interlayer van der Waals interactions.

OVITO was used again to visualize these simulations, and for the trial with a starting BLG gap of 2.00 Å, we saw the expansion of the gap between the graphene sheets due to interlayer compression which caused repulsive forces to push the sheets apart for a more favorable energetic state (Figure 3). For the simulation with a starting BLG gap of 4.00 Å, we saw the compression of the sheets via attractive forces to reach the most energetically favorable state in the structure (Figure 4).

During our energy minimization trials, both systems converged to similar final potential energies of

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toward an interlayer spacing of approximately 3.40- 3.50 Å, once again validating our assumption that structural stability corresponds to energy minimization and falling in line with existing literature.

The results of our study show the direct relationship between graphene’s structural stability and its internal energy, dependent on the structure’s atomic properties. In the monolayer trials, energy minimization simulations resulted in a parabolic trend in potential energy, with a minimum occurring at a bond length of approximately 1.42 Å. This value aligns closely with established theoretical and experimental studies, confirming that even small deviations from the equilibrium bond length (indicated by the 0.10 Å incremental changes) result in substantial increases in system energy due to internal bond strain [1,5]. These findings also reflect the observations of strong σ-bond dominance and delocalized π-electron behavior that stabilize graphene’s hexagonal lattice [2].

Chart 4: Bilayer gap relaxation over simulation steps

Our BLG simulations similarly demonstrated that interlayer gap distance plays a critical role in determining total system energy. Structures initialized at 2.00 Å and 4.00 Å both relaxed toward an equilibrium gap of ~3.40 Å, a value supported by prior literature [9]. Interestingly, the system initialized at 4.00 Å not only started closer to this value but also reached convergence faster than the system initialized at 2.00 Å, suggesting that a small deviation from equilibrium in either direction influences both initial energetic favorability and the speed of structural relaxation. These trends once again prove the importance of atomic arrangement in maintaining low-energy, stable graphene configurations. Furthermore, the importance of the initial gap distance on how the structure evolved is supported by high-velocity impact simulations, where even small changes in stacking geometry significantly impact dynamic response and energy absorption [8].

These similarities reinforce the understanding that atomic-scale arrangement in both in-plane and interlayer geometry is necessary in creating energetically favorable graphene systems.

Figure 3: Expansion of bilayer graphene from an initial 2.0 Å gap

Figure 4: Compression of bilayer graphene from an initial 4.0 Å gap

Although our study successfully identified ideal structural configurations in monolayer and bilayer graphene, our results were limited in some regards. All of our simulations were performed using ideal, pure graphene at 0 K, without incorporating temperature fluctuations, external forces, or defects in modified structures that can occur in the real world. Additionally, all simulations were carried out using the AIREBO potential, which while widely used, has known limitations in modeling longrange London dispersion forces and can oversimplify certain external interactions in bilayer systems. Future research in the field may benefit from hybrid or alternate force fields for more accurate results, especially in BLG systems. Another limitation was the scope of BLG

3. CONCLUSIONS Our study’s goal was to determine the most stable atomic configurations of monolayer and bilayer graphene through energy minimization in MD simulations. We hypothesized that for each structure, there would be a specific C-C bond length and BLG gap that minimized the potential energy of the systems, and that simulations would naturally reach these values to stabilize the structure. The data from our monolayer trials confirmed that a bond length of 1.42 Å was consistently reached regardless of initial configuration, supporting our hypothesis and aligning with previous studies. Similarly, our bilayer graphene systems initialized at both 2.00 Å and 4.00 Å gaps relaxed

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configurations tested. Our study also only utilized AAstacked bilayer configurations, whereas AB or twisted bilayers can display different energetic behavior. Finally, although our research examined structural relaxation under energy minimization, it did not explore timedependent changes or deformation under strain, which are essential in many engineering applications for graphene.

Journal of Science: Advanced Materials and Devices, vol.

5, March 2020, pp.

10-29, https://doi.org/10.1016/j.jsamd.2020.01.006.

[2]

A. R. Urade, I. Lahiri, K. S. Suresh, “Graphene Properties, Synthesis and Applications: A Review,” JOM, vol. 75, October 2022, pp. 614-630, https://doi.org/10.1007/s11837-022-05505-8.

Despite these limitations, the findings of our research contribute valuable data to the growing understanding of graphene's structural energetics. The results of our study provide an understanding into the behavior of graphene at the atomic level and its stability under various atomic conditions. By computationally verifying the bond length of ~1.42 Å and bilayer gap of ~3.40 Å as energetically favorable configurations, our results reinforce discoveries for the development of future graphene-based materials.

These figures not only align with experimental data and prior literature but also provide tested parameters for future trials in materials design and MD simulations, particularly for applications requiring structural stability such as sensors, nanoelectronics, or composite reinforcement.

[3]

T. Luo, Q. Wang, “Effects of Graphite on Electrically Conductive Cementitious Composite Properties: A Review,” Materials, vol. 14, August 2021, pp. 4798, https://doi.org/10.3390/ma14174798.

[4]

R. Soave, F. Cargoni, M. I. Trioni, “Thermodynamic Stability and Electronic Properties of Graphene Nanoflakes,” C, vol. 10, January 2024, pp. 5, https://doi.org/10.3390/c10010005.

[5]

G. Yang, L. Li, W. B. Lee, M. C. Ng, “Structure of graphene and its disorders: a review,” Science and technology of advanced materials, vol. 19, Aug. 2018, pp.

613-648, https://doi.org/10.1080/14686996.2018.1494493.

In BLG systems, the importance of initial configurations for efficient convergence toward minimum-energy spacing could prove important in future studies of BLG, where layer deposition or intercalation plays a crucial role. These insights strengthen the foundation for applying graphene in advanced technologies and contribute to ongoing efforts to implement its unique properties into future technologies in aerospace, medicine, and electronics.

[6]

T. Yusaf, A. S. F. Mahamude, K. Farhana, W. S. W. Harun, K. Kadirgama, D. Ramasamy, M. K. Kamarulzaman, S. Subramonian, S. Hall, H. A. Dhahad, “A Comprehensive Review on Graphene Nanoparticles: Preparation, Properties, and Applications,” Sustainability, vol. 14, September 2022, pp. 12336, https://doi.org/10.3390/su141912336.

[7]

A. E. Galashev, O. R. Rakhmanova, “Mechanical and thermal stability of graphene and graphene-based materials,” Physics-Uspekhi, vol. 57, October 2014, pp.

970-989 https://doi.org/10.3367/ufnr.0184.201410c.1045.

[8]

Y. Qiu, Y. Zhang, A. S. Ademiloye, Z. Wu, “Molecular dynamics simulations of single-layer and rotated double-layer graphene sheets under a high velocity impact by fullerene,” Computational Materials Science, vol.

182, September 2020, pp.

109798, https://doi.org/10.1016/j.commatsci.2020.109798.

[9]

Y. Huang, X. Li, H. Cui, Z. Zhou, “Bi-layer Graphene: Structure, Properties, Preparation and Prospects,” Current Graphene Science, vol. 2, 2018, pp. 97-105, https://doi.org/10.2174/2452273202666181031120 115.

Through the findings of our study, we were able to demonstrate that energy minimization is an effective method for identifying optimal bond lengths and interlayer spacings in graphene systems. This research supports the continued use of MD simulations in atomicscale materials design and encourages further investigations that include defects and alternative structures to more accurately represent real-world materials.

ACKNOWLEDGEMENT I would like to acknowledge my mentors, Professor Dibakar Datta and PhD candidate Rumana Hasan at NJIT for guiding me through the research process and providing support whenever I encountered hardship.

Their support and guidance was vital in my research process, and I thank them for all their help.

[10] P. He, Y. Zhang, Z. Wang, P. Min, Z. Deng, L. Li, L. Ye, Z.

Yu, H. Zhang, “An energy-saving structural optimization strategy for high-performance multifunctional graphene films,” vol. 222, March 2024, pp.

118932, https://doi.org/10.1016/j.carbon.2024.118932.

REFERENCES [1]

S. K. Tiwari, S. Sahoo, N. Wang, A. Huczko, “Graphene research and their outputs: Status and prospect,”

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[11] N. R Abdullah, H. O. Rashid, C. Tang, A. Manolescu, V.

Gudmundsson, “Role of interlayer spacing on electronic, thermal and optical properties of BNcodoped bilayer graphene: Influence of the interlayer and the induced dipole-dipole interactions,” Journal of Physics and Chemistry of Solids, vol. 155, August 2021, pp.

110095, https://doi.org/10.1016/j.jpcs.2021.110095.

[12] P. K. Sahoo, N. Kumar, A. Jena, S. Mishra, C. Lee, S. Lee,

S. Park, “Recent progress in graphene and its derived hybrid materials for high-performance supercapacitor electrode applications,” RSC Advances, vol. 14, January 2024, pp.

1284-1303, https://doi.org/10.1039/D3RA06904D. [13] N. Mushahary, A. Sarkar, F. Basumatary, S. Brahma, B.

Das, S. Basumatary, “Recent developments on graphene oxide and its composite materials: From fundamentals to applications in biodiesel synthesis, adsorption, photocatalysis, supercapacitors, sensors and antimicrobial activity,” Results in Surfaces and Interfaces, vol. 15, May 2024, pp. 100225, https://doi.org/10.1016/j.rsurfi.2024.100225.

[14] C.

P Herrero, R. Ramírez, “Elastic properties and mechanical stability of bilayer graphene: molecular dynamics simulations,” The European Physical Journal B, vol.

96, November 2023, https://doi.org/10.1140/epjb/s10051-023-00616-w.

[15] Z. Wang, H. Zhang, X. Sun, Y. Huo, “Molecular dynamics

study on the mechanical behavior of vertically aligned γ-graphdiyne-graphene heterostructures under tension,” Materials Today Communications, vol. 37, December 2023, pp.

107465, https://doi.org/10.1016/j.mtcomm.2023.107465.

[16] Y. Zhang, Y. Qiu, F. Niu, A. S. Ademiloye, “Molecular

dynamics simulation of perforation of graphene under impact by fullerene projectiles,” Materials Today Communications, vol. 31, June 2022, pp. 103642, https://doi.org/10.1016/j.mtcomm.2022.103642.

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