A Multi-Scale Coupled Simulation Method for Irradiation Damage of Energetic Materials

Abstract

This invention belongs to the field of materials property simulation technology and discloses a multi-scale coupled simulation method for irradiation damage of energetic materials. This method integrates first-principles calculations, Monte Carlo simulations, molecular dynamics, and accelerated molecular dynamics calculations. By cascading and coupling these simulation techniques at different scales and utilizing parallel computing technology, it overcomes the limitations of single-scale simulations in existing technologies, enabling long-term, large-scale simulations of energetic materials under irradiation conditions, from atomic-scale defect generation to microstructure characterization. This invention solves the limitation of single-scale simulations in existing technologies for irradiation damage simulation of energetic materials and is applicable to irradiation damage simulation of energetic materials.

Description

Technical Field

[0001] This invention relates to the field of material property simulation technology, and in particular to a multi-scale coupled simulation method for irradiation damage of energetic materials. Background Technology

[0002] Energetic materials are substances that, when subjected to sufficient external stimuli, rapidly release large amounts of heat and gas through their own redox reactions. During their use, they face numerous environmental challenges, among which irradiation is one of the most severe. Irradiation conditions can negatively impact the performance of energetic materials. Because energetic materials are high-power energy-releasing materials involving chemical reactions, they are highly sensitive to the external environment. Irradiation damage experiments are difficult, time-consuming, procedurally complex, and costly. Therefore, combining limited, targeted experimental results with computer simulation technology is the primary method for studying the irradiation damage and aging mechanisms of energetic materials.

[0003] Current research on energetic material simulation mainly focuses on simulating decomposition mechanisms at the microscale. While multi-scale coupling methods for irradiating metallic materials have been established, the damage mechanisms of energetic materials differ significantly from those of metallic materials due to intermolecular chemical reactions. Therefore, analytical methods for metallic materials cannot be effectively applied to energetic materials. Currently, no simulation method or cross-scale simulation system for irradiation damage of energetic materials has been developed. Furthermore, the lack of a potential function for irradiation simulation makes it unclear how to set up a molecular dynamics physical model for the irradiation chemical reactions of energetic materials. The properties of the data to be analyzed and the calculations lack clear references, thus hindering the simulation of damage and aging mechanisms of energetic materials under irradiation. Summary of the Invention

[0004] This invention aims to provide a multi-scale coupled simulation method for irradiation damage of energetic materials, addressing the limitations of existing single-scale simulations in irradiation damage simulation of energetic materials. The method integrates multiple computational techniques, including first-principles calculations, Monte Carlo simulations, molecular dynamics, and accelerated molecular dynamics, by cascading and coupling these simulation techniques at different scales. Utilizing parallel computing technology, it overcomes the limitations of single-scale simulations, enabling long-term, large-scale simulations of energetic materials under irradiation conditions, from atomic-scale defect generation to microstructure characterization.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] S1. First Principles Calculation: The initial force field for describing short-range interactions between atoms in molecular dynamics is constructed using the DFT calculation method, and the constructed initial force field is verified.

[0007] S2, Monte Carlo step: Simulate physical processes through random sampling, using a large number of random numbers to simulate the transport process of particles in the medium, thereby obtaining the energy distribution of secondary particles, which are used as the initial input parameters for molecular dynamics simulation;

[0008] S3. Molecular Dynamics Step: Initialize the system and, based on the initial force field determined in step S1 and the secondary particle parameters determined in step S2, use molecular dynamics methods and the initial force field to simulate the cascade collision process initiated by secondary particles. Simulate multiple times under the same initial conditions and determine key information by analyzing the simulation results.

[0009] S4, Accelerated Molecular Dynamics Step: Based on the molecular dynamics simulation in step S3, and using the key data energy obtained from the molecular dynamics calculation in step S3, the defect atoms are accelerated to overcome the energy barrier by continuously raising the atomic potential energy, thus extending the microsecond-level simulation timescale of molecular dynamics to more than days.

[0010] Step S1 specifically involves: using the energy and force calculated by DFT as a benchmark, comparing the energy and force predicted by DFT and ReaxFF potential energy, smoothly connecting the Ziegler-Biersack-Littmark repulsive potential energy (ZBL potential) and ReaxFF potential energy, minimizing the residual and RSS to determine the optimal parameters in the transition region, thereby generating an initial force field for describing short-range interactions between atoms in molecular dynamics, and verifying the initial force field after construction.

[0011] Step S2 specifically involves: using the Geant4 program to simulate the transport process of neutrons in the material, obtaining the energy spectrum and coordinate distribution of secondary particles, determining the percentage and energy range of secondary particles, and determining the energy value with the highest probability. The obtained secondary particle information is used as the initial input for molecular dynamics simulation.

[0012] Step S3 specifically involves: initializing the system, specifying the incident direction and energy of the primary displaced atom based on the initial force field determined in step S1 and the secondary particle parameters determined in step S2, setting the initial coordinates, velocity, and neighboring atom information for the atom, using molecular dynamics methods, simulating the cascade collision process triggered by the secondary particles using the initial force field, and performing multiple simulations under the same initial conditions, determining key information through in-depth statistical analysis of the molecular dynamics simulation results.

[0013] Furthermore, the verification in step S1 includes verification of equilibrium properties and verification of high-energy collisions.

[0014] Furthermore, in step S3, the system is initialized, and detailed system parameters, including system parameters, temperature, and pressure, are set.

[0015] Furthermore, the key information in step S3 includes initial defect distribution, key data energy, changes in mechanical properties, microstructure evolution, chemical products, and reaction pathways.

[0016] Furthermore, in step S4, the defect atoms can be accelerated to overcome the energy barrier by using high-temperature simulation.

[0017] The beneficial effects of the technical solution are as follows: The method of this invention couples four simulation methods of different scales: first-principles calculation (DFT), Monte Carlo (MC), molecular dynamics (MD), and accelerated molecular dynamics (AMD). With the help of parallel computing technology, it can break through the limitations of a single scale and realize long-term, large-scale, and relatively accurate computer simulation of the radiation interaction, atomic-scale defect generation, defect evolution process, and microstructure characterization of energetic materials under irradiation. This enables a deeper understanding of the irradiation damage mechanism of energetic materials, predicts the performance changes of energetic materials after irradiation, and provides a convenient and efficient scientific means for the design and performance prediction of energetic materials. Attached Figure Description

[0018] Figure 1 This is a flowchart of the simulation method of the present invention;

[0019] Figure 2 This is a flowchart of the first-principles calculations of the present invention;

[0020] Figure 3 This is a flowchart of the Monte Carlo steps of the present invention;

[0021] Figure 4 This is a flowchart of the molecular dynamics steps of the present invention;

[0022] Figure 5 This is a flowchart of the accelerated molecular dynamics steps of the present invention; Detailed Implementation

[0023] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments:

[0024] This invention proposes a multi-scale coupled simulation method for irradiation damage to energetic materials, aiming to overcome the limitations of single simulation methods by comprehensively utilizing multiple computational simulation techniques. This method integrates first-principles calculations, Monte Carlo methods, molecular dynamics methods, and accelerated molecular dynamics methods to leverage their respective advantages at different time and spatial scales. The specific flowchart is shown below. Figure 1 As shown.

[0025] First, using first principles, the atomic pairs of carbon, hydrogen, oxygen, and nitrogen elements are... Potential energy and force within a certain distance are calculated and fitted using the ReaxFF-lg potential function and the ZBL potential function to construct a new ReaxFF-lg / ZBL force field to describe the process of high-energy collisions between atoms in molecular dynamics, resulting in energy transfer and collision cascades.

[0026] The Monte Carlo method was used to simulate the interaction between irradiated particles and atoms in energetic materials, and the energy distribution of different types of primary displaced atoms (PKAs), such as C, H, O, and N atoms, in the displacement cascade process was calculated. The calculation results can provide a theoretical basis for setting the energy range of PKAs in molecular dynamics.

[0027] Molecular dynamics simulations were used to simulate the cascade collision process induced by PKA, a key step in understanding the microscopic damage mechanism of energetic materials under irradiation. The initial defect trajectory results generated by the molecular dynamics simulation were used as the input file for accelerated molecular dynamics (AMD). The cohesive energy and bond energy data obtained by MD simulation were used to set acceleration parameters (such as temperature, acceleration barrier, and cutoff distance) and start the accelerated molecular dynamics simulation.

[0028] This coupling method enables the simulation of energetic materials from atomic-scale defects to microstructures on a large spatiotemporal scale, achieving accurate prediction of performance changes of energetic materials under service conditions. This not only improves the accuracy of the simulation but also expands the temporal and spatial scope of the simulation, providing a strong theoretical foundation and predictive tool for the design and performance optimization of energetic materials.

[0029] The specific implementation process is as follows; the specific parameters can be adjusted according to your own situation:

[0030] First-principles calculation (DFT) steps:

[0031] 1. The interaction energy and force of each pair of C, H, O and N atoms (a total of 10) at short distances are calculated using non-spin polarized density functional theory. Fourier transform is used to calculate the PAW potential, and the FFT grid points are increased to help the GGA (generalized gradient approximation) calculation converge.

[0032] 2. Using first-principles calculations as a reference standard, a new ReaxFF-lg / ZBL force field is constructed. By minimizing the sum of squared residuals, the optimal parameters of the transition region [R1,R2] are determined. The ZBL potential energy and the ReaxFF-lg potential energy are smoothly connected to improve the description of short-range interactions between atoms in energetic materials.

[0033] 3. Verification of equilibrium properties. The cell parameters and equation of state of the energetic material in equilibrium were calculated using first-principles calculations and compared with those of ReaxFF-lg / ZBL and ReaxFF-lg force field. The results show that ReaxFF-lg / ZBL is very close to the experimental results in describing the equilibrium properties of the energetic material and is superior to ReaxFF-lg force field.

[0034] 4. High-energy particle collision verification. The displacement cascades induced by the modified ReaxFF-lg / ZBL force field were compared and verified with the results of first-principles molecular dynamics. The results show that the ReaxFF-lg / ZBL force field describes the energy transfer in high-energy collisions in a more consistent manner with the first-principles calculations.

[0035] The flowchart for first-principles calculations is as follows: Figure 1 As shown.

[0036] Monte Carlo (MC) steps:

[0037] 1. Particle Transport Model Setup. The Geant4 program was used to simulate the neutron transport process in C4H8N8O8 material. During the simulation of neutron incidence into the target, a hemispherical incidence method was used to simulate a point source. Since the neutron energy was set to 0.1 MeV, the pre-compiled physics model FTFP.BERT.HP was selected. This model can effectively simulate the interaction between neutrons and matter within an energy range from 0.025 eV to 20 MeV. Specifically, it achieves accurate simulation of inelastic hadron-nucleus processes by integrating the Fritiof-parton (FTF) model, the Bertini model, and the Precompound model. Meanwhile, for the elastic scattering of protons and neutrons, the G4ChipsElasticModel was adopted. This model utilizes the Kossov parameterized cross section and combines it with a high-precision neutron model and cross section to describe the elastic scattering, inelastic scattering, trapping and fission behavior at low energies in detail. Finally, the energy distribution and density distribution results of PKA were successfully obtained.

[0038] 2. Secondary particle generation. Prepare a sample with a volume of 2.5 × 3.25 × 3 cm. 3 Models of energetic materials (such as octogen, HMX) were constructed, and their negative y-axis (i.e., b-axis) direction was determined. The neutron source energy was set to 0.1 MeV, and the neutron incident direction was set to the negative y-axis. The interaction between the neutrons and the atoms within the model was analyzed over a period of 10... 6 The simulation yielded the energy and coordinate distributions of 168,900 primary off-site atoms (PKA).

[0039] 3. Determining the energy of secondary particles. Based on the energy distribution data, a probability density curve is obtained by fitting a probability density function, and the most probable energy value corresponding to the probability density curve is selected as the energy of the secondary particles.

[0040] Monte Carlo process flowchart as follows Figure 2 As shown.

[0041] Molecular dynamics (MD) steps:

[0042] 1. Construct an initial model of the energetic material to obtain the types of atoms and their initial coordinates;

[0043] 2. Initialize system settings and atomic information, including system, temperature, pressure, incident direction and energy of the first lattice atom (PKA) to be dislodged by a neutron, initial coordinates of the atom and neighboring atoms, etc.

[0044] 3. Define the force field and parameters. To better describe the short-range interatomic forces, a ReaxFF-lg / ZBL force field is used for molecular dynamics simulations. Simultaneously, based on Nordlund's friction model, the electron blocking effect is considered. When the kinetic energy of an atom exceeds the threshold energy (Ec), the atom experiences a frictional force proportional to its velocity during injection, as shown in the following equation:

[0045]

[0046] To match the energy loss of the electron (the Ec value used in the simulation was tested to be 9 eV), the scaling parameter β can be obtained by calculating a linear fitting function of particle velocity versus electron stopping energy using SRIM.

[0047] 4. Energy Minimization. The conjugate gradient (CG) algorithm is used to relax the energetic material model in order to find the lowest energy configuration of the system, with an energy tolerance of 10. -6 kcal / mol.

[0048] 5. Equilibrium System. The Nose-Hoover thermostat method was used to perform a 10 ps relaxation under a 300 K canonical ensemble (NVT) with a time step of 0.1 fs. Subsequently, the energetic material model was relaxed for 60 ps under an NPT ensemble to eliminate internal stress and bring the system to thermodynamic equilibrium. After relaxation, the stability of the structure was assessed, and the potential energy and density curves were evaluated for convergence. If equilibrium was reached, the model could be used for the next step of cascade process simulation.

[0049] 6. Cascade Process Simulation. In the displacement cascade simulation, selected PKA atoms are randomly distributed within the PKA region on one side of the simulation box. To increase the probability of collisions with other atoms, the movement direction of the PKA atoms is set to point towards the center of the box, and in each case, only one PKA atom is triggered and tracked at a time. A layer with a thickness of [thickness missing] is set on the outermost layer of the simulation box. The cooling layer has an internal cascaded collision region. The cascaded collision region is simulated under a microcanonical ensemble (NVE), while the cooling layer is simulated under an NVT ensemble by velocity scaling to allow energy dissipation, thereby eliminating spurious pressure waves reflected from boundary cells and ultimately cooling to the target temperature of 300K. Furthermore, to avoid the influence of PKA on the cooling layer, out-of-place atoms are removed once they reach this region; the time step is set to 10. -5 The values ​​of fs and 0.1fs are automatically adjusted to ensure that the maximum displacement distance and maximum energy transfer are less than 0.1fs within a time step. And 0.1 kcal / mol. After the system was annealed to 300 K, it was further subjected to NPT relaxation for 30 ps with a fixed time step of 0.1 fs to obtain a model without internal stress.

[0050] 7. For each PKA energy condition, a PKA will be randomly selected, and the simulation process will be repeated 8-10 times under the same initial conditions to obtain statistical results.

[0051] 8. Information Collection and Analysis. During the cascade collision process, the system dynamics and thermodynamics information are statistically analyzed every 20 fs. The molecular types and compositions of the products are identified, analyzed, and statistically analyzed according to the minimum bond order of different molecules to provide detailed information on the chemical reactions during the cascade process.

[0052] A flowchart of the molecular dynamics steps is as follows: Figure 3 As shown.

[0053] Accelerated Molecular Dynamics (AMD) Steps:

[0054] The initial defect structure ultimately generated by molecular dynamics, the chemical bond lengths in the statistical system, and the system potential energy.

[0055] 1. Set the acceleration parameters. Set the atomic critical displacement distance to 10% of the acceleration barrier parameter; set the critical distance increment to 5% of the atomic critical displacement distance; set the acceleration time to 10. 15 fs.

[0056] 2. Initiate accelerated molecular dynamics simulation. Read the initial defect trajectory generated by the MD simulation, and use LAMMPS to perform accelerated molecular dynamics simulation according to the parameters set in step 1. Set the relaxation temperature to 300K, the initial time step to 1fs, and enable barrier lifting acceleration. The acceleration time is obtained through transition state theory.

[0057]

[0058] Among them, t total This represents the acceleration time, where n is the number of acceleration simulations performed, and t is the acceleration time. MD It is the simulation time in each accelerated simulation, V is the acceleration barrier, and k is the acceleration potential barrier. b It is Boltzmann's constant, and T is the simulation temperature. Under this simulation setting, relaxation simulation continues until the preset acceleration time is reached.

[0059] The above descriptions are merely embodiments of the present invention, and common knowledge regarding specific technical solutions or characteristics is not elaborated upon here. It should be noted that those skilled in the art can make various modifications and improvements without departing from the technical solutions of the present invention, and these should also be considered within the scope of protection of the present invention. These modifications and improvements will not affect the effectiveness of the implementation of the present invention or the practicality of the patent. The scope of protection claimed in this application should be determined by the content of its claims, and the specific embodiments described in the specification can be used to interpret the content of the claims.

Claims

1. A multi-scale coupled simulation method for irradiation damage of energetic materials, characterized in that, Includes the following steps: S1. First-principles calculations: The initial force field for describing short-range interactions between atoms in molecular dynamics is constructed using the DFT calculation method, and the constructed initial force field is verified. S2, Monte Carlo step: Simulate physical processes through random sampling, using a large number of random numbers to simulate the transport process of particles in the medium, thereby obtaining the energy distribution of secondary particles, which are used as the initial input parameters for molecular dynamics simulation; S3. Molecular Dynamics Step: Initialize the system and, based on the initial force field determined in step S1 and the secondary particle parameters determined in step S2, use molecular dynamics methods and the initial force field to simulate the cascade collision process triggered by secondary particles. Simulate multiple times under the same initial conditions and determine key information by analyzing the simulation results. S4, Accelerated Molecular Dynamics Step: Based on the molecular dynamics simulation in step S3, and using the key data energy and defect structure obtained from the molecular dynamics calculation in step S3, the defect atoms are accelerated to overcome the energy barrier by continuously raising the atomic potential energy, thus extending the microsecond-level simulation timescale of molecular dynamics to more than days. Specifically, step S1 involves: using the energy and force calculated by DFT as a benchmark, comparing the energy and force predicted by DFT and ReaxFF potential energy, smoothly connecting the Ziegler-Biersack-Littmark repulsive potential energy with the ReaxFF potential energy, minimizing the residual sum to determine the optimal parameters in the transition region, thereby generating an initial force field for describing short-range interactions between atoms in molecular dynamics, and verifying the initial force field after construction; Step S2 specifically involves: using the Geant4 program to simulate the transport process of neutrons in the material, obtaining the energy spectrum and coordinate distribution of secondary particles, determining the percentage and energy range of secondary particles, and determining the energy value with the highest probability. The obtained secondary particle information is used as the initial input for molecular dynamics simulation. Step S3 specifically involves: initializing the system, specifying the incident direction and energy of the primary displaced atom based on the initial force field determined in step S1 and the secondary particle parameters determined in step S2, setting the initial coordinates, velocity, and neighboring atom information for the atom, using molecular dynamics methods, simulating the cascade collision process triggered by the secondary particles using the initial force field, and performing multiple simulations under the same initial conditions, determining key information through in-depth statistical analysis of the molecular dynamics simulation results.

2. The multi-scale coupled simulation method for irradiation damage of energetic materials according to claim 1, characterized in that: The verification in step S1 includes equilibrium property verification and high-energy collision verification.

3. The multi-scale coupled simulation method for irradiation damage of energetic materials according to claim 1, characterized in that: In step S3, the system is initialized, and detailed system parameters, including system parameters, temperature, and pressure, are set.

4. The multi-scale coupled simulation method for irradiation damage of energetic materials according to claim 1, characterized in that: The key information in step S3 includes the initial defect distribution, key data energy, changes in mechanical properties, microstructure evolution, chemical products, and reaction pathways.

5. The multi-scale coupled simulation method for irradiation damage of energetic materials according to claim 1, characterized in that: In step S4, the defect atoms can also be accelerated to overcome the energy barrier by using high-temperature simulation.

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