A simulation method for the reaction process of nano-aluminothermic agents based on molecular dynamics

Abstract

This invention relates to a molecular dynamics-based simulation method for the reaction process of nano-aluminothermic agents, belonging to the field of energetic materials. The simulation method includes the following steps: establishing an initial model of the nano-aluminothermic agent reaction based on molecular dynamics simulation software; selecting a reaction force potential function that accurately describes the interatomic interactions of the nano-aluminothermic agent reaction; relaxing the system to achieve kinetic equilibrium at a certain temperature; simulating a thermally induced self-sustaining reaction under adiabatic conditions on the equilibrium nano-aluminothermic agent model; and obtaining detailed information about the entire nano-aluminothermic agent reaction explosion process based on the simulation data. This invention can simulate the microscopic molecular structure changes during the explosion process of nano-aluminothermic agent reactions using molecular dynamics and visualize the atomic structure process of the reaction explosion.

Description

Technical Field

[0001] This invention belongs to the field of energetic materials, specifically a simulation method for the reaction process of nano-aluminothermic agents based on molecular dynamics. Background Technology

[0002] Nano-aluminothermic fuels have advantages such as fast reaction rate, high energy release rate, short ignition delay time and low ignition temperature due to the close contact between fuel and oxidant interface and short diffusion distance. They have always been a research hotspot in the field of energetic materials.

[0003] The reaction initiation and explosion process of nano-thermite is extremely short, occurring on the picosecond scale. While current experimental methods have achieved nanometer-level time resolution, they can only observe partial reaction products at different stages, and the experimental costs are very high, making it difficult to observe the entire reaction initiation and explosion process of nano-thermite. Molecular dynamics methods have become an important research tool in condensed matter physics and materials science, used to study a wide variety of practical problems. Through molecular dynamics methods, the entire reaction initiation and explosion process of nano-thermite under thermal loading can be observed at the atomic level, simulating the microscopic molecular structure changes during the reaction and explosion, and visualizing the atomic structure processes of the reaction and explosion. Summary of the Invention

[0004] The purpose of this invention is to propose a simulation method for the reaction process of nano-aluminothermic agents based on molecular dynamics, which makes up for the inability of experiments to detect the complete reaction and explosion process of nano-aluminothermic agents and reduces experimental costs.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0006] A simulation method for the reaction process of nano-aluminothermic agents based on molecular dynamics, the simulation method comprising the following steps:

[0007] S1. Based on molecular dynamics simulation software, establish the initial model of the required microstructure of the nano-aluminothermic agent;

[0008] S2, select the reaction force potential function ReaxFF, which can accurately describe the interatomic interaction force of the nano-aluminothermic reaction, and set the parameters for molecular dynamics simulation;

[0009] S3, the initial model is dynamically relaxed under the NVT ensemble to achieve dynamic equilibrium at a certain temperature;

[0010] S4 simulates the thermally induced self-sustaining reaction under adiabatic conditions on the equilibrium nanothermal agent model, and obtains the dump atomic trajectory file, MSD root mean square displacement file, output file containing the system's time, temperature, volume, enthalpy, potential energy, kinetic energy, total energy and pressure in each state, RDF radial distribution function file, and SPECIES reaction product file corresponding to the nanothermal agent from redox reaction to complete explosion process.

[0011] S5 utilizes open-source visualization software to analyze data from dumped atomic trajectory files, obtaining dynamic structural information throughout the entire reaction-to-explosion process. A self-developed bonding analysis program further analyzes the dynamic atomic structure, revealing the evolution of the number of bonds between atoms over time during the reaction. Atomic diffusion rates at different reaction stages are calculated using Einstein's equations and MSD. By organizing data from other files and plotting curves, a detailed picture of the entire nano-aluminothermic reaction-explosion process can be obtained.

[0012] Furthermore, the microstructure includes layered structures and core-shell structures.

[0013] Furthermore, step S1 specifically includes:

[0014] Using LAMMPS molecular dynamics simulation software, regions of Al and metal oxides were delineated based on the microstructure of the nano-aluminothermic agent, and a lattice was established and filled with atoms using the lattice command.

[0015] Furthermore, the energy formula for the reaction force potential function ReaxFF in step S2 is:

[0016] E system =E bond +E over +E under +E lp +E val +E vdWaals +E Coulomb

[0017] Among them, the contribution E to the total energy system bond energies E bond Overcoordination energy correction value E over Undercoordination stability energy E under Energy E of a lone pair electron system lp Bond angle energy E val Van der Waals energy term E vdWaals and Coulomb energy term E Coulomb .

[0018] Furthermore, step S3 specifically includes:

[0019] The entire system of the reaction between nano-aluminothermic Al and metal oxides is maintained at the target temperature under the NVT ensemble. A state point is set at fixed time steps, and the fix print command in the in file is used to output the system's time, temperature, volume, enthalpy, potential energy, kinetic energy, total energy, and pressure in real time to the data file for each state. The data file data is imported into Origin, and the evolution curve of potential energy over time is plotted to determine whether the system has reached equilibrium and the optimal relaxation time. The restart command in the in file is used to output a binary restart file at regular time steps.

[0020] Furthermore, step S4 specifically includes:

[0021] The `in` file is used to read the `restart` file with the optimal relaxation time, and a thermally induced self-sustaining reaction simulation is performed under adiabatic conditions in the NVE ensemble. A state point is set at fixed time steps, and the `fix print` command in the `in` file outputs the system's time, temperature, volume, enthalpy, potential energy, kinetic energy, total energy, and pressure in real time to the `data` file for each state point. The `dump` command in the `in` file outputs the coordinates and charge of all atoms in the system at each state point to the `dump atom trajectory` file. The `compute msd` command in the `in` file calculates the root mean square displacement and saves the data to the `MSD` file. The `compute rdf` command in the `in` file calculates the radial distribution function and saves the data to the `RDF` file. The `fix reax / c / species` command in the `in` file outputs the types and quantities of reactants to the `SPECIES` file.

[0022] Furthermore, step S5 includes the following steps:

[0023] S51. Using the visualization software OVITO, the dump atomic trajectory file output by the LAMMPS molecular dynamics simulation is read to obtain a dynamic atomic structure evolution video of the entire reaction to explosion process.

[0024] S52, the dynamic atomic structure was further analyzed by a self-developed bonding analysis program, and the results were imported into Origin software to obtain the evolution curve of the number of bonds between atoms as a function of reaction time during the reaction process;

[0025] S53: Read the time and temperature data from the data file, import it into Origin software to plot the system temperature versus reaction time curve, and combine it with the bond number curve to analyze the reaction stage.

[0026] S54, read the MSD.txt file, where the first column is the time step, and the second, third, fourth, and fifth columns are the x, y, and z directions and the total mean square displacement, respectively. The diffusion coefficients of various atoms in the system at each reaction stage are obtained using Einstein relations: In the formula, MSD is the total mean square displacement;

[0027] S55, read the RDF at the transition time points between each reaction stage, draw the radial distribution function g(r) between atoms at different times, obtain the spatial distribution order of atoms at the transition time, and determine whether the reaction stage is a solid-solid reaction, a solid-liquid reaction, a liquid-gas reaction, or a gas-gas reaction.

[0028] S56, Read the SPECIES reaction product file and analyze the thermal decomposition gaseous products of the nano-aluminothermic agent during the explosion stage.

[0029] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0030] 1. This invention uses molecular dynamics to simulate the reaction process of nano-aluminothermic agents. By using open-source visualization software, the microscopic molecular structure changes during the reaction and explosion of nano-aluminothermic agents can be observed at the atomic level. This makes up for the inability of experiments to detect the complete reaction process and greatly reduces the experimental cost. It provides guidance for the design and preparation of safe and efficient new nano-energetic material systems.

[0031] 2. This invention avoids the computationally expensive first-principles molecular dynamics method, and selects the ReaxFF reaction force potential function that can accurately describe the reaction process of the nano-aluminothermic agent system, combined with the classical molecular dynamics method which has lower computational cost and can simulate longer time scales and larger sizes. Attached Figure Description

[0032] Figure 1 This is a flowchart of a simulation method for the reaction process of nano-aluminothermic agents based on molecular dynamics;

[0033] Figure 2 This is an initial model diagram of the Al@SiO2 core-shell structure according to a typical embodiment of the present invention, where a is a schematic diagram and b is an atomic diagram;

[0034] Figure 3 This is a graph showing the evolution of potential energy over time in determining whether the system has reached equilibrium during the relaxation process, as presented in this invention.

[0035] Figure 4 This is a partial schematic diagram of the adiabatic reaction of the nano-aluminothermic agent of the present invention from an in-file.

[0036] Figure 5 This is a snapshot of the Al@SiO2 reaction in the yz plane in Example 1 of the present invention;

[0037] Figure 6 This is a diagram of the main code of the self-compiled bond analysis program of this invention;

[0038] Figure 7 This is a graph showing the evolution of the number of Si-O, Al-O, and Si-Si bonds over time in Embodiment 1 of the present invention.

[0039] Figure 8 This is a graph showing the evolution of system temperature over time in Embodiment 1 of the present invention;

[0040] Figure 9 This is a diagram of the radial distribution function g(r) of the Al–Al(a), Si-O(b), Al-O(c), and Si-Si(d) pairs in Embodiment 1 of the present invention. Detailed Implementation

[0041] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0042] Example 1

[0043] like Figure 1 As shown, this embodiment of the invention provides a simulation method for the reaction process of nano-aluminothermic agents based on molecular dynamics, including the following steps:

[0044] S1. Based on molecular dynamics simulation software, establish an initial model of the required microstructure (in this embodiment, the Al / SiO2 core-shell structure is used as an example) for the nano-aluminothermic agent.

[0045] S2, select the reaction force potential function ReaxFF, which can accurately describe the interatomic interaction force of the nano-aluminothermic reaction, and set the parameters for molecular dynamics simulation;

[0046] S3, the initial model is dynamically relaxed under the NVT ensemble to achieve dynamic equilibrium at a certain temperature;

[0047] S4. Perform thermally induced self-sustaining reaction simulation on the equilibrium nano-aluminothermic agent model under adiabatic conditions to obtain the dump atomic trajectory file, MSD root mean square displacement file, output file containing system temperature and energy information, RDF radial distribution function file, and SPECIES reaction product file corresponding to the process of nano-aluminothermic agent from redox reaction to complete explosion.

[0048] S5 utilizes open-source visualization software to analyze data from dumped atomic trajectory files, obtaining dynamic structural information throughout the entire reaction-to-explosion process. A self-developed bonding analysis program further analyzes the dynamic atomic structure, revealing the evolution of the number of bonds between atoms over time during the reaction. Atomic diffusion rates at different reaction stages are calculated using Einstein's equations and MSD. By organizing data from other files and plotting curves, a detailed picture of the entire nano-aluminothermic reaction-explosion process can be obtained.

[0049] In this embodiment, step S1 specifically includes:

[0050] Using the modeling commands in LAMMPS software, an initial atomic structure model of core-shell Al@SiO2 nanoparticles was established, consisting of a face-centered cubic Al sphere as the core and a nanocrystalline quartz SiO2 shell of a certain thickness. Figure 2 As shown (a is a schematic diagram, b is an atomic diagram). It is placed at the center of a three-dimensional orthogonal cubic supercrystal, with a vacuum region within the box. Periodic boundary conditions are applied in all three directions, ensuring that the distance between the surfaces of two nano-aluminothermic particles is greater than [missing information]. To avoid interactions between nanoparticles, an appropriate time step is set, and the ReaxFF potential function is used to describe the interactions between atoms.

[0051] In this embodiment, steps S1 and S2 use the ReaxFF potential function to describe the interaction between atoms, and the specific energy formula is as follows:

[0052] E system =E bond +E over +E under +E lp +E val +E vdWaals +E Coulomb

[0053] Among them, the contribution E to the total energy system bond energies E bond Overcoordination energy correction value E over Undercoordination stability energy E under Energy E of a lone pair electron system lp Bond angle energy E val Van der Waals energy term E vdWaals and Coulomb energy term E Coulomb .

[0054] In this embodiment, step S3 specifically includes:

[0055] The entire Al@SiO2 nanothermite system was maintained at the target temperature under the NVT ensemble. A state point was set at fixed time steps, and the time, temperature, volume, enthalpy, potential energy, kinetic energy, total energy, and pressure of the system at each state were output to the data file in real time using the `fix print` command in the `in` file. The data from the data file was imported into Origin, and the evolution curve of the potential energy over time was plotted, such as... Figure 3 As shown, the relative error of the potential energy at t = 30 ps and 50 ps is 0.35%, which is lower than the structural stability criterion (potential energy fluctuation within 20 ps is less than 1.2%). Relaxation ends at t = 50 ps, ​​meaning the Al@SiO2 nanoparticles reach equilibrium at t = 50 ps. The structural stability criterion (potential energy fluctuation within 20 ps is less than 1.2%) is used to determine whether the system has reached equilibrium and the optimal relaxation time; the restart command in the IN file is used to output a binary restart file at regular time steps.

[0056] In this embodiment, step S4 specifically includes:

[0057] The `in` file is used to read the `restart` file with the optimal relaxation time, and a thermally induced self-sustaining reaction simulation is performed under adiabatic conditions in the NVE ensemble. A state point is set at fixed time steps, and the `fix print` command in the `in` file outputs the system's time, temperature, volume, enthalpy, potential energy, kinetic energy, total energy, and pressure in real time to the `data` file for each state point. The `dump` command in the `in` file outputs the coordinates and charge of all atoms in the system at each state point to the `dump atom trajectory` file. The `compute msd` command in the `in` file calculates the root mean square displacement and saves the data to the `MSD` file. The `compute rdf` command in the `in` file calculates the radial distribution function and saves the data to the `RDF` file. The `fix reax / c / species` command in the `in` file outputs the types and quantities of reactants to the `SPECIES` file. Related `in` files are shown below. Figure 4 As shown.

[0058] In this embodiment, step S5 includes the following specific sub-steps:

[0059] S51. By using the visualization software OVITO to read the dump atomic trajectory file output from the LAMMPS molecular dynamics simulation, a dynamic atomic structure evolution video of the entire reaction to explosion process can be obtained, with partial yz-plane reaction snapshots as shown below. Figure 5 As shown;

[0060] S52 uses a self-developed bonding analysis program to further analyze the dynamic atomic structure. The main bonding analysis program code is as follows: Figure 6 As shown, the results were imported into Origin software to obtain the evolution curve of the number of interatomic bonds as a function of reaction time during the reaction process, as shown in the figure. Figure 7 As shown;

[0061] S53 reads the time and temperature data from the data file, imports it into Origin software, and plots the system temperature versus reaction time curve, such as... Figure 8 As shown, the reaction stages are analyzed by combining the bond number curve;

[0062] S54, read the MSD.txt file, where the first column is the time step, and the second, third, fourth, and fifth columns are the x, y, and z directions and the total mean square displacement, respectively. The diffusion coefficients of various atoms in the system at each reaction stage are obtained using Einstein relations: In the formula, MSD is the total mean square displacement;

[0063] S55, read the RDF at the transition time points between each reaction stage, and plot the radial distribution function g(r) between atoms at different times, such as... Figure 9 As shown, the spatial distribution order of atoms at the transition time is obtained, and the reaction stage is determined to be a solid-solid reaction, a solid-liquid reaction, a liquid-gas reaction, or a gas-gas reaction.

[0064] S56, Read the SPECIES reaction product file and analyze the thermal decomposition gaseous products of the nano-aluminothermic agent during the explosion stage.

[0065] The above description is merely one embodiment of the present invention and is only used to illustrate the technical solution of the present invention, and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention are included within the scope of protection of the present invention.

Claims

1. A simulation method for the reaction process of nano-aluminothermic agents based on molecular dynamics, characterized in that, The simulation method includes the following steps: S1. Based on molecular dynamics simulation software, establish the initial model of the required microstructure of the nano-aluminothermic agent; S2, select the reaction force potential function ReaxFF, which can accurately describe the interatomic interaction force of the nano-aluminothermic reaction, and set the parameters for molecular dynamics simulation; S3, the initial model is dynamically relaxed under the NVT ensemble to achieve dynamic equilibrium at a certain temperature; S4 simulates the thermally induced self-sustaining reaction under adiabatic conditions on the equilibrium nanothermal agent model, and obtains the dump atomic trajectory file, MSD root mean square displacement file, output file containing the system's time, temperature, volume, enthalpy, potential energy, kinetic energy, total energy and pressure in each state, RDF radial distribution function file, and SPECIES reaction product file corresponding to the nanothermal agent from redox reaction to complete explosion process. S5 utilizes open-source visualization software to analyze data from dumped atomic trajectory files, obtaining dynamic structural information throughout the entire reaction-to-explosion process. A self-developed bonding analysis program further analyzes the dynamic atomic structure, revealing the evolution of the number of bonds between atoms over time during the reaction. Atomic diffusion rates at different reaction stages are calculated using Einstein's equations and MSD. By organizing data from other files and plotting curves, a detailed picture of the entire nano-aluminothermic reaction-explosion process can be obtained.

2. The simulation method for the reaction process of nano-aluminothermic agents based on molecular dynamics according to claim 1, characterized in that, The microstructures include layered structures and core-shell structures.

3. The simulation method for the reaction process of nano-aluminothermic agents based on molecular dynamics according to claim 1, characterized in that, Step S1 specifically involves: Using LAMMPS molecular dynamics simulation software, regions of Al and metal oxides were delineated based on the microstructure of the nano-aluminothermic agent, and a lattice was established and filled with atoms using the lattice command.

4. The simulation method for the reaction process of nano-aluminothermic agents based on molecular dynamics according to claim 1, characterized in that, The energy formula for the reaction force potential function ReaxFF in step S2 is: AND system =And bond +E over +E under +E lp +E val +E vdWaals +E Coulomb Among them, the contribution E to the total energy system bond energies E bond Overcoordination energy correction value E over Undercoordination stability energy E under Energy E of a lone pair electron system lp Bond angle energy E val Van der Waals energy term E vdWaals and Coulomb energy term E Coulomb .

5. The simulation method for the reaction process of nano-aluminothermic agents based on molecular dynamics according to claim 1, characterized in that, Step S3 specifically involves: The entire system of the reaction between nano-aluminothermic Al and metal oxides is maintained at the target temperature under the NVT ensemble. A state point is set at fixed time steps, and the fix print command in the in file is used to output the system's time, temperature, volume, enthalpy, potential energy, kinetic energy, total energy, and pressure in real time to the data file for each state. The data file data is imported into Origin, and the evolution curve of potential energy over time is plotted to determine whether the system has reached equilibrium and the optimal relaxation time. The restart command in the in file is used to output a binary restart file at regular time steps.

6. The simulation method for the reaction process of nano-aluminothermic agents based on molecular dynamics according to claim 1, characterized in that, Step S4 specifically involves: The `in` file is used to read the `restart` file with the optimal relaxation time, and a thermally induced self-sustaining reaction simulation is performed under adiabatic conditions in the NVE ensemble. A state point is set at fixed time steps, and the `fix print` command in the `in` file outputs the system's time, temperature, volume, enthalpy, potential energy, kinetic energy, total energy, and pressure in real time to the `data` file for each state point. The `dump` command in the `in` file outputs the coordinates and charge of all atoms in the system at each state point to the `dump atom trajectory` file. The `compute msd` command in the `in` file calculates the root mean square displacement and saves the data to the `MSD` file. The `compute rdf` command in the `in` file calculates the radial distribution function and saves the data to the `RDF` file. The `fix reax / c / species` command in the `in` file outputs the types and quantities of reactants to the `SPECIES` file.

7. The simulation method for the reaction process of nano-aluminothermic agents based on molecular dynamics according to claim 1, characterized in that, Step S5 includes the following steps: S51. Using the visualization software OVITO, the dump atomic trajectory file output by the LAMMPS molecular dynamics simulation is read to obtain a dynamic atomic structure evolution video of the entire reaction to explosion process. S52, the dynamic atomic structure was further analyzed by a self-developed bonding analysis program, and the results were imported into Origin software to obtain the evolution curve of the number of bonds between atoms as a function of reaction time during the reaction process; S53: Read the time and temperature data from the data file, import it into Origin software to plot the system temperature versus reaction time curve, and combine it with the bond number curve to analyze the reaction stage. S54, read the MSD.txt file, where the first column is the time step, and the second, third, fourth, and fifth columns are the x, y, and z directions and the total mean square displacement, respectively; obtain the diffusion coefficients of various atoms in the system at each reaction stage using Einstein relations: In the formula, MSD is the total mean square displacement; S55, read the RDF at the transition time points between each reaction stage, draw the radial distribution function g(r) between atoms at different times, obtain the spatial distribution order of atoms at the transition time, and determine whether the reaction stage is a solid-solid reaction, a solid-liquid reaction, a liquid-gas reaction, or a gas-gas reaction. S56, Read the SPECIES reaction product file and analyze the thermal decomposition gaseous products of the nano-aluminothermic agent during the explosion stage.

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