Molecular dynamics simulation method for constructing graphene fibers by graphene sheets

Abstract

The invention relates to a molecular dynamics simulation method for constructing graphene fibers by graphene sheets, and belongs to the technical field of graphene material simulation. A simulation model of graphene fibers is constructed by graphene sheets, and a virtual molecular dynamics simulation test is adopted to replace a traditional experimental process, so that the defects of an experiment in time and space scales are overcome. According to the method, through molecular dynamics simulation, the arrangement, combination and curling behaviors of graphene sheets in the fiber are deeply disclosed, and a theoretical basis is provided for optimizing the microstructure and performance of the graphene fiber.

Description

Technical Field

[0001] This patent relates to the field of graphene material simulation technology, in particular to a molecular dynamics simulation method for constructing graphene fibers and a model of graphene fibers obtained by this method. Background Art

[0002] Graphene has excellent optical, electrical, and mechanical properties and has important application prospects in materials science, micro-nano processing, energy, biomedicine, and drug delivery. It is considered a revolutionary material for the future. Due to its excellent mechanical, electrical, and thermal properties, graphene fibers have great application potential in the fields of aerospace, electronics, energy, and aviation. On the basis of maintaining high performance, the cost of graphene fibers is lower than that of traditional high-performance fibers, and China has made great breakthroughs in this field, being free from the constraints and embargoes of the international market, providing the possibility for large-scale applications. Currently, the process of experimentally preparing graphene fibers is complex, costly, and it is difficult to deeply explore all the relationships between structure and properties at the microscopic level.

[0003] Compared with laboratory preparation, molecular dynamics simulation, as an important research method in the field of materials, can not only provide atomic-scale details but also has the advantages of being able to study complex systems and flexibly control parameters. And on the premise of ensuring the authenticity of the simulation, the cost of the process is less.

[0004] As a material widely used in high-tech fields, the structure of traditional carbon fibers is similar to "chain-chain entanglement", which leads to a small crystal region and many grain boundary defects, thus resulting in poor heat insulation. Through molecular dynamics simulation, it is relatively easy to complete the construction of new "sheet-sheet interlocking assembly" graphene fibers. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide a molecular dynamics simulation method for constructing graphene fibers from graphene sheets, so as to deeply understand the arrangement, combination, and curling methods of graphene sheets in the fibers and provide a theoretical basis for optimizing the microscopic structure and properties of the fibers.

[0006] To solve the above technical problems, the present invention adopts the following technical solutions:

[0007] A molecular dynamics simulation method for constructing graphene fibers from graphene sheets, the method comprising the following steps:

[0008] S1: Place multiple graphene sheets of the same size in a simulation box in a parallel arrangement, and introduce randomness at specific positions to construct an initial microscopic structure model of the graphene fiber.

[0009] S2: Set the initial parameters of the initial microstructure model, including the spatial dimension of the microstructure model, the system unit of the microstructure model, the boundary conditions of the microstructure model, and the potential function between atoms in the microstructure model.

[0010] S3: After ensuring the stability of the initial conditions of the simulation, perform relaxation in the canonical ensemble of constant particle number, constant pressure, and constant temperature to ensure the stability of the initial microstructure; subsequently, in the canonical ensemble of constant particle number, constant volume, and constant temperature, apply compression to all graphene sheets through a cylindrical constraint and gradually shrink the cylindrical constraint to simulate the curling and binding behavior of graphene sheets in the fiber.

[0011] S4: Perform melting and quenching processes on the simulation system in the canonical ensemble of constant particle number, constant volume, and constant temperature to accelerate the fusion of graphene sheets and further stabilize the fiber structure.

[0012] S5: Perform final relaxation in the canonical ensemble of constant particle number, constant pressure, and constant temperature to ensure zero pressure on the parallel alignment axis and output the final atomic coordinate information.

[0013] Compared with the prior art, the present application has the following advantages: Through molecular dynamics simulation, it is possible to reveal the arrangement, binding, and curling behavior of graphene sheets in the fiber at the atomic scale, providing theoretical guidance for optimizing the microstructure of the fiber. The simulation process is flexible and controllable, capable of quickly exploring the effects of different construction conditions (such as temperature, pressure, number of sheets, etc.) on the properties of graphene fibers, reducing the cost of experimental trial and error. This method can predict the mechanical properties of graphene fibers, providing important references for practical applications. Brief Description of the Drawings

[0014] Figure 1 is a schematic flow chart of the present invention;

[0015] Figure 2 is a schematic diagram of a graphene sheet;

[0016] Figure 3 is a schematic diagram of the initial microstructure model for constructing graphene fibers;

[0017] Figure 4 is a schematic diagram of the compressed model;

[0018] Figure 5 is a schematic diagram of the completed graphene fiber model. Detailed Embodiments

[0019] The present application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0020] See Figure 1As shown in the figure, an embodiment of the present application discloses a molecular dynamics simulation method for constructing graphene fibers from graphene sheets, including:

[0021] S1: According to the lattice constant of graphene, a microscopic structure model of multiple graphene sheets of the same size is constructed through the Large-scale Atomic Molecular Massively Parallel Simulator (LAMMPS) software. The size and shape of the graphene sheets can be set according to actual needs. After construction, it is output in the form of a data file for subsequent calling. Multiple graphene sheets of the same size are placed in a simulation box in a parallel arrangement, and randomness is introduced at specific positions to construct an initial microscopic structure model of the graphene fiber. After construction, it is output in the form of a data file for subsequent calling.

[0022] S2: Set the initial parameters of the initial microscopic structure model; the initial parameters include the spatial dimension of the microscopic structure model, the system unit of the microscopic structure model, the boundary conditions of the microscopic structure model, and the potential function between atoms in the microscopic structure model; among them, the potential function between atoms in the microscopic structure model uses the Adaptive Intermolecular Reactive Empirical Bond Order potential function (AIREBO), which is an improved potential function used to describe the interaction between atoms in carbon-based materials (such as graphene, carbon nanotubes, etc.). It consists of multiple parts, including short-range covalent bond interactions, long-range van der Waals interactions, and torsional interactions. Its expression is:

[0023] In the formula is the REBO potential, which describes short-range covalent bond interactions; is the Lennard-Jones potential, which describes long-range van der Waals interactions; is the torsional potential, which describes the interaction related to the torsional angle.

[0024] The REBO potential function is:

[0025] In the formula, r ij is the distance between atom i and atom j, V R (r ij ) is the repulsive potential, which describes the repulsive force between atoms, V A (r ij ) is the attractive potential, which describes the attractive force between atoms, b ij is the bond order function, which is used to dynamically adjust the bond strength and depends on the local environment of atom i and atom j.

[0026] The expression of the bond order function b ij is:

[0027] wherein and describe the contributions of the σ bond and the π bond respectively, is a correction term for the bond order, used to describe many-body effects.

[0028] The Lennard-Jones potential function is as follows:

[0029] where ∈ ij is the depth of the potential well, representing the strength of the interaction, and σ ij is the equilibrium distance between atom i and atom j. The potential function is as follows:

[0030] where φ ijkl is the dihedral angle between atoms i, j, k, and l, and V n is the amplitude of the torsional potential, is the reference value of the dihedral angle.

[0031] To ensure the smoothness of the potential function, the AIREBO potential introduces a cutoff function S(r) to smoothly cut off the interaction when the distance r reaches a certain value. The expression of the cutoff function is:

[0032] where r max and r min are the upper and lower limits of the cutoff distance.

[0033] S3: After ensuring the stability of the initial conditions of the simulation, relaxation is carried out in the canonical ensemble (NPT) with constant particle number, constant pressure, and constant temperature to ensure the stability of the initial microstructure. Among them, the stability of the initial conditions is achieved by initializing the atomic velocities, eliminating the overall angular momentum of the system, and performing energy minimization to eliminate the unreasonable stress in the initial microstructure; relaxation under NPT conditions is to balance along the parallel axis direction to ensure the stability and uniformity of the initial microstructure, and at the same time calculate the center coordinates and initial radius of the system to prepare for the subsequent compression process. Under the canonical ensemble (NVT) with constant particle number, constant volume, and constant temperature, compression is applied to all graphene sheets by means of a cylindrical constraint and gradually reducing the cylindrical constraint to simulate the curling and binding behavior of graphene sheets in the fiber; among them, the cylindrical constraint uses the fix indent instruction, and the size after the cylindrical constraint compression depends on the situation, and at the same time the cylindrical constraint should include all graphene sheets. In both the relaxation and compression processes, the coordinate positions of each atom are output every 100 time steps, and the atomic position information obtained from the molecular dynamics simulation is used to display the entire dynamic process of the simulation through OVITO software.

[0034] S4: Melting and quenching processes are carried out on the simulation system in the canonical ensemble with constant particle number, constant volume, and constant temperature to accelerate the fusion of graphene sheets and further stabilize the fiber structure. Among them, in the melting stage, in the canonical ensemble with constant particle number, constant volume, and constant temperature, the system is gradually heated from room temperature (290K - 300K) to a high temperature (1150K - 1250K) to simulate the structural relaxation of graphene fibers at high temperatures and maintain for a certain time at high temperature to further stabilize the fiber structure; in the quenching stage, in the canonical ensemble with constant particle number, constant volume, and constant temperature, the system is gradually cooled from a high temperature (1150K - 1250K) to room temperature (290K - 300K) to simulate the formation of the final structure of the fiber during the cooling process. A short-term equilibrium is carried out on the system at room temperature to ensure the stability of the fiber structure. In each stage of the relaxation process, the coordinate positions of each atom are output every 100 time steps, and the atomic position information obtained from the molecular dynamics simulation is used to display the entire dynamic process of the simulation through OVITO software.

[0035] S5: Final relaxation is carried out in the canonical ensemble with constant particle number, constant pressure, and constant temperature to ensure zero pressure on the parallel alignment axis. Record the microstructure and performance parameters of the fiber, output the final atomic coordinate information for subsequent analysis. In both the equilibrium and relaxation processes, the coordinate positions of each atom are output every 100 time steps, and the atomic position information obtained from the molecular dynamics simulation is used to display the entire dynamic process of the simulation through OVITO software.

[0036] The following will take the molecular dynamics simulation example of constructing graphene fibers with 8 graphene sheets as an example to specifically illustrate a molecular dynamics simulation method for constructing graphene fibers from graphene sheets, including:

[0037] S1: Use the LAMMPS software to construct the microscopic structure model of the graphene sheet and the initial microscopic structure of the graphene fiber, specifically including:

[0038] Modeling is carried out through the graphene unit cell, and its lattice constant is The a lattice vector and the positions of the basis atoms are a1(3, 0, 0), a2(0, 1.732, 0), a3(0, 0, 2.357), basis1(0, 0, 0), basis2(0.333, 0, 0), basis3(0.5, 0.5, 0), basis4(0.833, 0.5, 0); the size and shape of the graphene sheet can be set according to actual needs. In this example, a complete single-layer graphene sheet with a length in the x-axis direction of and a width in the y-axis direction of is used, as shown in Figure 2 After the above 8 graphene sheets are constructed and saved, the data file is output. Use the read_data instruction to read the 8 graphene sheets into a box, with random positions but in a parallel arrangement, to construct the initial microscopic structure of the graphene fiber. After construction, the data file is saved and output. In this example, parallel in the x direction is used, as shown in Figure 3 shown.

[0039] S2: Set the initial parameters of the microscopic structure model in LAMMPS, specifically including:

[0040] (1) Set the unit of the model system to the metal unit system (metal);

[0041] (2) Set the spatial dimension of the model to 3D;

[0042] (3) Set the boundary conditions to be periodic boundaries (p boundaries) in the x, y, and z directions;

[0043] (4) Adopt the adaptive intermolecular reactive empirical bond order potential function (AIREBO), which is an improved potential function used to describe the interactions between atoms in carbon-based materials (such as graphene, carbon nanotubes, etc.). It consists of multiple parts, including short-range covalent bond interactions, long-range van der Waals interactions, and torsional interactions. Its expression is:

[0044] In the formula, is the REBO potential, which describes short-range covalent bond interactions; is the Lennard-Jones potential, which describes the long-range van der Waals interaction; is the torsional potential, which describes the interaction related to the torsional angle.

[0045] The REBO potential function is:

[0046] where r ij is the distance between atom i and atom j, and V R (r ij ) is the repulsive potential, which describes the repulsive force between atoms, and V A (r ij ) is the attractive potential, which describes the attractive force between atoms, and b ij is the bond order function, which is used to dynamically adjust the bond strength and depends on the local environment of atom i and atom j.

[0047] The bond order function b ij has the following expression:

[0048] where and describe the contributions of the σ bond and π bond respectively, and is the correction term for the bond order, which is used to describe the many-body effect.

[0049] The Lennard-Jones potential function is:

[0050] where ∈ ij is the depth of the potential well, representing the strength of the interaction, and σ ij is the equilibrium distance between atom i and atom j.

[0051] The potential function is:

[0052] where φ ijkl is the torsional angle between atom i, atom j, atom k, and atom l, and V n is the amplitude of the torsional potential, and is the reference value of the torsional angle.

[0053] To ensure the smoothness of the potential function, the AIREBO potential introduces a cutoff function S(r), which is used to smoothly cut off the interaction when the distance r reaches a certain value. The expression of the cutoff function is:

[0054] where r max and rmin are the upper and lower limits of the truncation distance.

[0055] (5) Read the data file of the initial microstructure for constructing graphene fibers built in the first step.

[0056] S3: Ensure the stability of the initial conditions of the simulation, specifically including:

[0057] Initialize the atomic velocity (300K);

[0058] Eliminate the overall angular momentum of the system;

[0059] Minimize the energy.

[0060] Relax in the canonical ensemble of constant particle number, constant pressure, and constant temperature, specifically including:

[0061] Define the step size in the relaxation process as 0.001 ps;

[0062] Define the relaxation time as 50000 steps, and according to the relaxation time step, the entire relaxation time is 50 ps;

[0063] Define the relaxation temperature as 300K to simulate the real environment;

[0064] Define the ensemble used in the relaxation process as the canonical ensemble of constant particle number, constant pressure, and constant temperature (NPT), and control the pressure in the x-axis direction;

[0065] Define to output the coordinate positions of each atom every 100 steps.

[0066] Calculate the center coordinates and initial radius of the system. Under the canonical ensemble of constant particle number, constant volume, and constant temperature (NVT), apply compression to the system through cylindrical constraints and gradually shrink the cylindrical constraints. The compressed model is as Figure 4 shown. The specific compression process includes:

[0067] Define to calculate the center coordinates and initial radius of the system, which should include all graphene sheets;

[0068] Define the step size in the process of relaxation and compression as 0.001 ps;

[0069] Define the relaxation and compression time as 32700 steps, and according to the time step, the entire compression time is 32.7 ps;

[0070] Define the relaxation and compression temperature as 300K to simulate the real environment;

[0071] Define the ensemble used in the relaxation process as the canonical ensemble of constant particle number, constant volume, and constant temperature (NVT);

[0072] The cylindrical constraint in the compression process is defined using the fix indent command;

[0073] Define the calculation of the reduction rate of the radius of the cylindrical constraint as

[0074] Define the calculation of the final radius after the system compression is completed. In this example, it is

[0075] Define to output the coordinate positions of each atom every 100 steps.

[0076] S4: Perform the melting and quenching processes on the simulation system under the canonical ensemble of constant particle number, constant volume, and constant temperature. Specifically, it includes:

[0077] Define the step size in the melting and quenching processes as 0.001 ps;

[0078] Define the heating time as 50,000 steps. According to the time step, the total heating time is 50 ps;

[0079] Define the heating temperature as rising from room temperature of 300 K to high temperature of 1200 K to simulate the melting process;

[0080] Define the high-temperature holding time as 50,000 steps. According to the time step, the total high-temperature holding time is 50 ps;

[0081] Define the cooling temperature as dropping from high temperature of 1200 K to room temperature of 300 K to simulate the quenching process;

[0082] Define the cooling time as 50,000 steps. According to the time step, the total cooling time is 50 ps;

[0083] Define the short equilibrium time at room temperature as 10,000 steps. According to the time step, the short equilibrium time is 50 ps;

[0084] Define the ensemble used as the canonical ensemble of constant particle number, constant volume, and constant temperature (NVT);

[0085] Define to output the time, temperature, energy, and the coordinate positions of each atom every 100 steps;

[0086] S5: Perform the final relaxation under the conditions of constant particle number, constant pressure, and constant temperature (NPT) to ensure zero pressure on the x-axis. The graphene fiber model obtained after the final relaxation is as Figure 5 shown. The specific process of the final NPT relaxation includes:

[0087] Define the step size in the relaxation process as 0.001 ps;

[0088] Define the relaxation time as 200,000 steps, and according to the time step of relaxation, the total relaxation time is 200 ps;

[0089] Define the ensemble adopted as the canonical ensemble (NPT) with constant number of particles, constant pressure, and constant temperature to ensure zero pressure on the x-axis;

[0090] Define to output time, temperature, energy, and the coordinate positions of each atom every 100 steps.

[0091] Define to output the final graphene fiber model.

[0092] Through the above steps, the following conclusions can be drawn, specifically including:

[0093] By constructing a microscopic structure model of graphene sheets, setting initial parameters, and performing processes such as relaxation, compression, melting, and quenching under different canonical ensembles (NPT, NVT), the simulation construction of graphene fibers is finally realized. This method deeply reveals the arrangement, bonding, and curling behaviors of graphene sheets in the fibers through molecular dynamics simulation, providing a theoretical basis for optimizing the microscopic structure and properties of graphene fibers. The simulation process is flexibly controllable, can quickly explore the influence of different construction conditions on the properties of graphene fibers, reduce the cost of experimental trial and error, and provide an important reference for practical applications. The simulation process is implemented through the LAMMPS software, and dynamic display and analysis are carried out through the OVITO software, further enhancing the practicality and operability of this method.

[0094] The above shows and describes the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. What is described in the above embodiments and the specification is only the principle of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements all fall within the scope of the present invention claimed.

Claims

1. A molecular dynamics simulation method for constructing graphene fibers from graphene sheets, characterized in that: The following steps are involved: S1: Multiple graphene sheets of the same size are placed in parallel in a simulation box, and randomness is introduced in the specific positions to construct the initial microstructure model of graphene fibers; S2: setting the initial parameters of the initial microstructure model, including the spatial dimension of the microstructure model, the system unit of the microstructure model, the boundary conditions of the microstructure model, and the potential function between atoms in the microstructure model; S3: After ensuring the stability of the initial conditions of the simulation, relaxation is performed under a canonical ensemble of equal particle number, equal pressure, and equal temperature to ensure the stability of the initial microstructure; then, under a canonical ensemble of equal particle number, equal volume, and equal temperature, compression is applied to all graphene sheets by gradually reducing the cylindrical constraint to simulate the curling and bonding behavior of graphene sheets in the fiber; S4: The simulation system is melted and quenched under a canonical ensemble of equal particle number, equal volume, and equal temperature to accelerate the fusion of graphene sheets and further stabilize the fiber structure; S5: Perform final relaxation under a canonical ensemble of equal particle number, equal pressure, and equal temperature to ensure zero pressure on the parallel arrangement axes and output the final atomic coordinate information.

2. The molecular dynamics simulation method for constructing graphene fibers from graphene sheets according to claim 1, characterized in that: In step S1, the microstructure model of the graphene sheet is constructed according to the lattice constant of graphene.

3. The molecular dynamics simulation method for constructing graphene fibers from graphene sheets according to claim 1, characterized in that: In step S2, the system unit of the microstructure model is the metal unit system; the spatial dimension of the microstructure model is 3D; and the boundary conditions of the microstructure model in the x, y, and z directions are all periodic boundaries.

4. The molecular dynamics simulation method for constructing graphene fibers from graphene sheets according to claim 1, characterized in that: In step S2, the potential function adopts an adaptive intermolecular reactivity empirical bond order potential function, which is composed of multiple parts, including short-range covalent bond interactions, long-range van der Waals interactions, and torsional interactions, and its expression is: In the formula is the REBO potential, describing the short-range covalent bond interaction; is the Lennard-Jones potential, describing the long-range van der Waals interaction; is the torsion potential, describing the torsion angle-dependent interaction; The REBO potential function is: Where r ij is the distance between atoms i and j, V R (r ij ) is the repulsive potential, describing the repulsive force between atoms, V A (r ij ) is the attractive potential, describing the attraction between atoms, b ij is the bond order function, which is used to dynamically adjust the bond strength, depending on the local environment of atoms i and j; Key order function b ij The expression is: In the formula and Describe the contribution of σ bonds and π bonds respectively, is a correction term for the bond order, used to describe multi-body effects; The Lennard-Jones potential function is: Where ∈ ij is the potential well depth, which indicates the strength of the interaction, σ ij is the equilibrium distance between atoms i and j; Said The potential function is: Where φ ijkl is the torsion angle between atoms i, j, k, and l, V n is the amplitude of the torsional potential, is the reference value of the torsion angle.

5. The molecular dynamics simulation method for constructing graphene fibers from graphene sheets according to claim 4, characterized in that: In order to ensure the smoothness of the potential function, the AIREBO potential introduces a truncation function S(r) to smoothly cut off the interaction when the distance r reaches a certain value; the expression of the truncation function is: where r max and r min are the upper and lower limits of the cutoff distance.

6. The molecular dynamics simulation method for constructing graphene fibers from graphene sheets according to claim 1, characterized in that: In step S3, the stability of the initial conditions is achieved by initializing the atomic velocity, eliminating the overall angular momentum of the system, and performing energy minimization to eliminate unreasonable stress in the initial microstructure.

7. The molecular dynamics simulation method for constructing graphene fibers from graphene sheets according to claim 1, characterized in that: In step S3, the cylindrical constraint applies compression to the system by gradually reducing the constraint radius, simulating the curling and bonding behavior of the graphene sheet.

8. The molecular dynamics simulation method for constructing graphene fibers from graphene sheets according to claim 1, characterized in that: In step S4, the melting and quenching process includes: Melting stage: gradually heat the system from room temperature (290K-300K) to high temperature (1150K-1250K) and maintain it at high temperature for a certain period of time; Quenching stage: The system is gradually cooled from high temperature (1150K-1250K) to room temperature (290K-300K) and briefly equilibrated at room temperature.

9. The molecular dynamics simulation method for constructing graphene fibers from graphene sheets according to claim 1, characterized in that: The simulation process of the method is implemented by LAMMPS software, and dynamically displayed and analyzed by OVITO software.

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