Method for designing alloy for alloy tritium target, computer readable storage medium and alloy design device

Abstract

The invention provides a method for designing an alloy for an alloy tritium target. The method comprises the following steps that S1, the element composition of the alloy is determined, and an alloy model is obtained; s2, obtaining a first stability data set of the alloy model; s3, the stability of the alloy model is judged, and when data in the first stability data set meet respective preset standards, an alloy tritium model is obtained based on the alloy model; s4, obtaining a second stability data set of the alloy tritide model; s5, the stability of the alloy tritium model is judged, and when data in the second stability verification data set meet respective preset standards, tritium storage capacity analysis is conducted on the alloy tritium model; and S6, when the tritium storage capacity analysis result meets a preset value, completing the design to obtain the alloy for the alloy tritium target.

Description

Technical Field

[0001] The present invention relates to the field of novel alloy material design, and in particular to a method for designing an alloy for an alloy tritium target, a computer-readable storage medium and an alloy design device. Background Art

[0002] The tritium target is one of the core components of the high-current multiplier driven pulsed neutron source (14MeV). The deuterium-tritium (DT) fusion neutron source can simulate the neutron irradiation environment in a fusion reactor and is an important means to carry out scientific experiments related to fusion energy technology, such as tritium breeding, energy extraction, material activation and damage, and radiation protection. The tritium titanium target is currently the most successful tritium target for accelerator-driven neutron sources, with a theoretical tritium storage density of 9.68×10 22 / cm 3 (The theoretical tritium-titanium atomic ratio is 2:1—TiT2). Affected by the metal film preparation process and tritium adsorption process, the actual tritium-titanium target atomic ratio is below 1.8 (TiT 1.8 ). At present, the specific neutron yield of accelerator-driven neutron sources is ~10 11 n / s / mA, much lower than the DT fusion ignition neutron radiation field (10 17-19 n / s / cm 2 ), which is mainly limited by the density of tritium on the target.

[0003] In order to obtain a neutron irradiation environment close to the real DT fusion ignition, it is necessary to develop a new type of tritium target with a high tritium loading density. Summary of the invention

[0004] In view of this, the main purpose of the present invention is to provide an alloy M for tritium target. a N b The method of the present invention designs a tritium target alloy with a high tritium loading density based on theoretical calculation, provides theoretical guidance for the preparation of the alloy, and saves experimental costs.

[0005] To this end, the present invention provides a method for designing an alloy for an alloy tritium target, comprising the following steps:

[0006] S1, determining the element composition of the alloy and obtaining an alloy model, wherein the element composition of the alloy is M a N b , M represents the first alloying element, N represents the second alloying element, a and b represent the atomic numbers of the first alloying element and the second alloying element, respectively;

[0007] S2, obtaining a first stability data set of the alloy model;

[0008] S3, determining the stability of the alloy model, wherein when the data in the first stability data group meets respective predetermined standards, obtaining an alloy tritide model based on the alloy model, wherein the element composition of the alloy tritide is: M a N b T y , T is tritium, y is the number of atoms of tritium, or

[0009] When at least one data in the first stability data group does not meet the predetermined standard of the data, return to step S1;

[0010] S4, obtaining a second stability data set of the alloy tritide model;

[0011] S5, determining the stability of the tritiated alloy model, wherein when the data in the second stability verification data group meets respective predetermined standards, performing tritium storage capacity analysis on the tritiated alloy model, or

[0012] When at least one data in the second stability verification data group does not meet the predetermined standard of the data, return to step S1;

[0013] S6, when the tritium storage capacity analysis result meets the predetermined value, completing the design to obtain the alloy for the alloy tritium target, or

[0014] When the tritium storage capacity analysis result does not meet the predetermined value, the process returns to step S1.

[0015] In some embodiments, obtaining the alloy model includes:

[0016] Construct a series of initial alloy unit cell structures with lower energy;

[0017] The initial alloy unit cell structure is structurally optimized, and the unit cell structure with the lowest energy is obtained as the alloy model.

[0018] In some embodiments, the first stability data set includes first thermodynamic stability data, first kinetic stability data, and first thermal stability data.

[0019] In some embodiments, the first thermodynamic stability data is obtained by calculating the formation energy E of the alloy model. f Preferably, the formation energy of the alloy model is calculated using formula (1),

[0020]

[0021] In the formula, E(M a N b) represents the total energy of the alloy model, E(M) and E(N) are the energies of a single M atom and a single N atom in the bulk phase of the alloy model, respectively;

[0022] The first dynamic stability data is obtained by calculating the phonon vibration frequency in the lattice of the alloy model, and preferably, the phonon spectrum is obtained according to the phonon vibration frequency in the lattice of the alloy model; or

[0023] The first thermal stability data is obtained by calculating the energy change value and the root mean square displacement of the alloy model at a predetermined temperature within a predetermined time period under the NVT ensemble.

[0024] In some embodiments, obtaining an alloy tritium model based on the alloy model comprises:

[0025] Constructing a series of initial alloy tritiated unit cell structures with lower energy;

[0026] The initial alloy tritiated unit cell structure is structurally optimized, and a unit cell structure with the lowest energy is obtained as the alloy tritiated unit model.

[0027] In some embodiments, the second stability data set includes second thermodynamic stability data, second kinetic stability data, and second thermal stability data.

[0028] In some embodiments, the second thermodynamic stability data is obtained by calculating the tritiation enthalpy change of the alloy model;

[0029] Preferably, based on the tritiation reaction equation of the alloy model shown in formula (2), the tritiation enthalpy change of the alloy model is calculated using the following formula (3):

[0030]

[0031]

[0032] In formula (3), E(M a N b T y ), E(M a N b ) and E(T2) represent the total energy of the alloy tritide model, the total energy of the alloy model and the energy of the gas phase T2, respectively;

[0033] The second dynamic stability data is obtained by calculating the phonon vibration frequency in the lattice of the alloy tritide model, and preferably, the phonon spectrum is obtained according to the phonon vibration frequency in the lattice of the alloy tritide model; or

[0034] The second thermal stability data is obtained by calculating the energy change value and root mean square displacement of the alloy tritium at a predetermined temperature within a predetermined time period under the NVT ensemble. Preferably, the first thermal stability data includes simulating the energy and root mean square displacement of the alloy at a predetermined temperature under the NVT ensemble.

[0035] In some embodiments, the performing tritium storage capacity analysis on the tritiated alloy model comprises:

[0036] Calculate the tritium atom density of the alloy tritide model; preferably, the tritium atom density is calculated using the following formula (4):

[0037]

[0038] In the formula, ρ V represents the tritium atom density of the alloy tritiated model, N(T) is the number of tritium atoms in the unit cell of the alloy tritiated model, V(M a N b T y ) is the unit cell volume of the alloy tritide model;

[0039] More preferably, the tritium storage capacity analysis of the tritium alloy model further comprises:

[0040] calculating the lattice expansion rate of the alloy tritide model;

[0041] Preferably, the lattice expansion rate is calculated using the following formula (5):

[0042]

[0043] Where △V / V represents the lattice expansion rate, V(M a N b ) is the unit cell volume of the alloy model, V(M a N b T y ) is the unit cell volume of the alloy tritide model.

[0044] The present invention also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the above method are implemented.

[0045] The present invention also provides an alloy design device, wherein the alloy is used for alloy tritium target by storing tritium, and the device comprises: a processor and a memory for storing a computer program that can be run on the processor, wherein the processor executes the steps of the above method when running the computer program.

[0046] The method of the present invention designs a new alloy material for a tritium target by utilizing computing resources based on first principles, density functional theory, etc., comprehensively considering factors such as the thermodynamic and kinetic stability of the alloy material and the alloy tritiated product formed after tritium loading, as well as the tritium loading capacity of the alloy and the lattice expansion of the alloy after tritium loading, and designs a new alloy material with stable properties and high tritium loading density. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 A flowchart of a method of the present invention according to an embodiment is shown. DETAILED DESCRIPTION

[0048] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in combination with the embodiments of the present invention and the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0049] Throughout the specification, unless otherwise specifically stated, the terms used herein should be understood as meanings commonly used in the art. Therefore, unless otherwise defined, all technical and scientific terms used herein have the same meanings as those generally understood by those skilled in the art to which the present invention belongs. In the event of a conflict, the present specification takes precedence.

[0050] It should be noted that, in the embodiments of the present invention, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a method or device including a series of elements includes not only the elements explicitly stated, but also other elements not explicitly listed, or also includes elements inherent to the implementation of the method or device. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the existence of other related elements in the method or device including the element.

[0051] The tritium titanium target in the prior art is affected by the metal film preparation process and the tritium adsorption process. The actual tritium titanium target atomic ratio is below 1.8, which limits the specific neutron yield of the accelerator driven neutron source. Therefore, it is necessary to develop a new tritium target with a high tritium density. However, the development of a new tritium target alloy through experimental research usually consumes a large amount of raw materials, and the research on the tritium loading performance of the alloy involves radioactive nuclides, which has problems such as harsh experimental conditions and high experimental difficulty. Therefore, a fast, economical and environmentally friendly design method for alloy tritium targets is needed.

[0052] In view of this, the present invention provides a method for designing an alloy for an alloy tritium target. The method of the present invention can quickly and efficiently design a series of new alloy tritium target materials with stable structures and good tritium loading performance through theoretical calculations, which can save experimental consumables and is environmentally friendly.

[0053] The method of the present invention comprises the following steps:

[0054] S1, determining the element composition of the alloy and obtaining an alloy model, wherein the element composition of the alloy is M a N b , M represents the first alloying element, N represents the second alloying element, a and b represent the atomic numbers of the first alloying element and the second alloying element, respectively;

[0055] S2, obtaining a first stability data set of the alloy model;

[0056] S3, determining the stability of the alloy model, wherein when the data in the first stability data group meets respective predetermined standards, obtaining an alloy tritide model based on the alloy model, wherein the element composition of the alloy tritide is: M a N b T y , T is tritium, y is the number of atoms of tritium, or

[0057] When at least one data in the first stability data group does not meet the predetermined standard of the data, return to step S1;

[0058] S4, obtaining a second stability data set of the alloy tritide model;

[0059] S5, determining the stability of the tritiated alloy model, wherein when the data in the second stability verification data group meets respective predetermined standards, performing tritium storage capacity analysis on the tritiated alloy model, or

[0060] When at least one data in the second stability verification data group does not meet the predetermined standard of the data, return to step S1;

[0061] S6, when the tritium storage capacity analysis result meets the predetermined value, completing the design to obtain the alloy for the alloy tritium target, or

[0062] When the tritium storage capacity analysis result does not meet the predetermined value, the process returns to step S1.

[0063] Figure 1 FIG. 2 shows a flowchart of a method of the present invention according to an embodiment. Figure 1 As shown, step S1 determines the element composition of the alloy and obtains the alloy model, wherein the element composition of the alloy is M a Nb , M represents the first alloy element, N represents the second alloy element, a and b represent the atomic number of the first alloy element and the second alloy element, respectively. The alloy model presents a variety of structures depending on the composition and proportion of the alloy. It can be understood that the lower the energy of the alloy model, the better its structural stability. In some embodiments, step S1 obtains one or more alloy models with lower energy.

[0064] In one embodiment, step S1 of obtaining the alloy model includes:

[0065] Construct a series of initial alloy unit cell structures with lower energy;

[0066] The initial alloy unit cell structure is structurally optimized, and the unit cell structure with the lowest energy is obtained as the alloy model.

[0067] To obtain a series of initial alloy unit cell structures, for example, alloy models with different alloy components and proportions can be built based on crystallographic theory, or structure prediction software (such as Crystal structure AnaLYsis by Particle Swarm Optimization (CALYPSO) structure prediction software) can be used to predict the alloy structures with different alloy components and proportions. For example, CALYPSO structure prediction software searches for the global optimal point on the potential energy surface based on the chemical ratio and external conditions. For example, for M a N b , specify the alloying elements (M and N) and the proportions (a and b) in the input file as needed to search for the global optimal point. In the structural search process of the CALYPSO software, no less than 30 different structures will be generated in each generation of the structure prediction process. In the initial stage of the search, the first generation of structures is randomly generated based on symmetry. Subsequently, starting from the second generation, the 60% of structures with the lowest energy are selected, and the local particle swarm optimization algorithm (LPSO) is used to further evolve these structures. At the same time, the remaining 40% of the structures are supplemented by random generation. Among them, the local structure optimization and energy calculation of each generation can be performed by DFT calculation using the VASP program. In order to obtain a stable alloy structure, it is necessary to perform more refined structural optimization and total energy calculation on the alloy structure built or predicted to screen and obtain a stable alloy structure. Alloy structure optimization and total energy calculation can be achieved based on density functional theory (DFT) calculations, for example, a software package based on first principles (Vienna Ab-initio Simulation Package, VASP) can be used.

[0068] For example, when a=3 and b=1, a series of initial unit cell structures with low energy of M3N1 are predicted by CALYPSO structure prediction software, such as face-centered cubic structure, body-centered cubic structure, close-packed hexagonal structure, triclinic structure, monoclinic structure, etc. The unit cell structures predicted by CALYPSO are sorted from low to high by energy, and for the first few structures with similar energy, these structures are further optimized to determine the alloy structure with the lowest energy. The VASP software package is used to perform structural optimization and total energy calculation on these initial unit cell structures based on density functional theory, and the unit cell structure with the lowest energy is obtained as the alloy model.

[0069] like Figure 1 As shown, step S2 obtains a first stability data set of the alloy model.

[0070] According to one embodiment, the first stability data set includes first thermodynamic stability data, first kinetic stability data and first thermal stability data.

[0071] According to one embodiment, the first thermodynamic stability data is obtained by calculating the formation energy E of the alloy model. f The formation energy of the alloy model reflects the heat absorption of the elements of the corresponding alloy during the formation of the alloy, and can be used to evaluate the difficulty of synthesizing a certain alloy in the experiment and its thermodynamic stability relative to the stable single substance. f The more negative it is, the more thermodynamically stable the alloy material is and the easier it is to synthesize.

[0072] In one embodiment, the formation energy E of the alloy model f Using formula (1) to calculate,

[0073]

[0074] In the formula, E(M a N b ) represents the total energy of the alloy model, E(M) and E(N) are the energies of a single M atom and a single N atom in the bulk phase of the alloy model, respectively.

[0075] In the present invention, the total energy E(M a N b ) can be calculated by, for example, a software package based on first principles (VASP), and the energies of individual M atoms and N atoms can be obtained by, for example, the VASP software package or reference books.

[0076] In one embodiment, the formation energy E of the alloy model fis less than 0, the first thermodynamic stability data meets its predetermined standard; or the formation energy E of the alloy model f If the value is greater than or equal to 0, the first thermodynamic stability data does not meet the predetermined standard.

[0077] For example, the unit cell structure with the lowest energy obtained in step S1 is used as the alloy model M3N1, and the formation energy E of the alloy model M3N1 is f Calculated using formula (1-1),

[0078]

[0079] Wherein, E(M3N1) represents the total energy of the alloy model, E(M) and E(N) are the energies of a single M atom and a single N atom in the bulk phase of the alloy model, respectively. E(M3N1) is the total energy of the unit cell structure with the lowest energy calculated by the VASP software package based on density functional theory in the above step S1, and E(M) and E(N) are also calculated by the VASP software package. The formation energy E of the alloy model M3N1 is calculated. f is less than 0, then the first thermodynamic stability data of the alloy model meets its predetermined standard.

[0080] In one embodiment, the first kinetic stability data is obtained by calculating the phonon vibration frequency in the lattice of the alloy model. In one embodiment, the phonon spectrum is obtained according to the phonon vibration frequency in the lattice of the alloy model.

[0081] In solid materials, lattice vibrations are caused by interactions between atoms, and these vibrations can be described by phonon spectra. The phonon spectrum reflects the characteristics of the lattice vibration mode, including the relative positions and interactions between atoms, and can be used to analyze the lattice vibration properties of crystals and study the stability, thermal expansion and other properties of materials. The absence of imaginary frequencies in the phonon spectrum indicates that the solid material is dynamically stable.

[0082] In one embodiment, the phonon vibration frequency of the alloy model can be, for example, based on density functional perturbation theory (DFPT), by processing the unit cell structure and force constant information of the alloy model obtained in step S1 with the help of Phonopy software to solve the vibration frequency of the phonons in the lattice of the alloy model. The phonon spectrum obtained according to the phonon vibration frequency in the lattice of the alloy model can be performed by data processing software known in the art. In one embodiment, the predetermined standard of the first kinetic data is that there is no imaginary frequency in the phonon spectrum.

[0083] Exemplarily, the unit cell structure with the lowest energy obtained in step S1 is used as the alloy model M3N1, and the crystal structure force constant information obtained by the DFT calculation of the alloy model M3N1 is processed using the Phonopy software to obtain the phonon frequency of the lattice, thereby drawing a curve of the phonon frequency changing with the wave vector, that is, the phonon spectrum. From the phonon spectrum, it is observed that there is no spectrum data for the part where the vertical axis frequency is lower than 0, which means that the phonon spectrum has no imaginary frequency, that is, the first kinetic stability data of the alloy model M3N1 meets its predetermined standard.

[0084] In one embodiment, the first thermal stability data is obtained by simulating the energy and root mean square displacement of the alloy model at a predetermined temperature and within a predetermined time period under an NVT ensemble.

[0085] Thermal stability verification is based on the change of atomic trajectories, energy changes and structural changes in the material under specific conditions. The ab initio molecular dynamics (AIMD) method is used to calculate the energy change value and root mean square displacement of the alloy model at a constant temperature within a predetermined time under the NVT (fixed number of particles, volume and temperature) ensemble. Within the simulated time range, the energy of the alloy model tends to be stable, and the displacement gradually tends to be stable, without significant violent fluctuations, indicating that the model has good thermal stability. In one embodiment, if the energy change value of the alloy model is less than 10% within a predetermined time, the material is considered to have passed the thermal stability verification. The first stability verification can determine whether the alloy model is stable and easy to synthesize, as well as its stability under specific conditions, so that the alloy can adapt to a specific accelerator-driven neutron source environment.

[0086] In the present invention, in the NVT ensemble, N represents the number of atoms in the alloy model, V represents the volume of the alloy model, and T represents the simulated temperature. The number of atoms in the alloy model is determined according to the elemental composition of the alloy model, the volume of the alloy model is the volume of the unit cell structure with the lowest energy of the alloy model obtained in the above step S1, and the temperature can be determined according to the actual working environment temperature of the designed alloy tritium target. In one embodiment, the predetermined temperature is set to below 550K. In one embodiment, the predetermined time period is 10ps.

[0087] Exemplarily, the unit cell structure with the lowest energy obtained in step S1 is used as the alloy model M3N1. VASP software is used to set the NVT ensemble based on the AIMD method. The atomic motion, interaction and structural stability of the alloy model within the predetermined temperature of 550K and the predetermined time of 10ps are obtained to obtain the data of alloy energy and root mean square displacement changing with time. By observing whether the energy tends to be stable, whether the displacement gradually tends to be stable, and whether significant and violent fluctuations occur within the predetermined time range. The case where the energy change value is less than 10% indicates that the material has good thermal stability. Figure 1 As shown, in step S3, the stability of the alloy model is determined, wherein when the data in the first stability data group meets the respective predetermined standards, an alloy tritide model is obtained based on the alloy model, wherein the element composition of the alloy tritide is: M a N b T y , T is tritium, y is the number of tritium atoms, or when at least one data in the first stability data set does not meet the predetermined standard of the data, return to step S1.

[0088] The tritium storage process of the alloy used for the alloy tritium target is represented by the tritium reaction equation shown in equation (2).

[0089]

[0090] In one embodiment, constructing an alloy tritium model based on the alloy model comprises:

[0091] Constructing a series of initial alloy tritiated unit cell structures with lower energy;

[0092] The initial alloy tritiated unit cell structure is structurally optimized, and a unit cell structure with the lowest energy is obtained as the alloy tritiated unit model.

[0093] Based on the above tritiation reaction equation, a series of initial alloy tritiated unit cell structures with different numbers of tritium atoms can be obtained based on the alloy model. The initial alloy tritiated unit cell structure can be obtained using the same software and method as the method for obtaining the alloy model in step S1, which will not be repeated herein. The initial alloy tritiated unit cell structure is structurally optimized, and the unit cell structure with the lowest energy is obtained as the alloy tritiated model. The same software and method as the method for structurally optimizing the initial alloy unit cell structure in step S1 can be used to obtain the alloy tritiated unit cell structure, which will not be repeated herein.

[0094] Exemplarily, the alloy tritiated model is obtained based on the alloy model that the data in the first stability data group obtained in step S3 meet the respective predetermined standards. When the number of tritium atoms y=1, the alloy tritiated is M3N1T1; when y=2, the alloy tritiated is M3N1T2; when y=3, the alloy tritiated is M3N1T3; no objection to the elemental composition of the alloy tritiated is listed here, and the technical personnel in this field can easily obtain the elemental composition of these alloy tritiated. Based on the elemental composition of the above-mentioned alloy tritiated, the CALYPSO structure prediction software is used to predict the initial unit cell structure of a series of alloy tritiated with lower energy. Then, the VASP software package is used to optimize the structure and calculate the total energy of the initial unit cell structure of these alloy tritiated based on density functional theory, and the unit cell structure with the lowest energy is obtained as the alloy tritiated model.

[0095] like Figure 1 As shown, step S4, obtaining a second stability data set of the alloy tritide model.

[0096] In one embodiment, the second stability data set includes second thermodynamic stability data, second kinetic stability data, and second thermal stability data.

[0097] In one embodiment, the second thermodynamic stability data is obtained by calculating the tritiation enthalpy change ΔH of the alloy tritiated model. The tritiated enthalpy ΔH reflects the heat absorbed or released during the tritiated reaction of the alloy to form the alloy tritiated. The tritiated enthalpy change ΔH of the alloy tritiated model is negative (ΔH<0), indicating that the tritiated reaction is an exothermic reaction, indicating that the alloy tritiated model is a thermodynamically stable unit cell structure. On the contrary, the tritiated enthalpy ΔH is positive (ΔH>0), indicating that the tritiated reaction is an endothermic reaction, indicating that the alloy tritiated model is not thermodynamically stable.

[0098] In one embodiment, based on the tritiation reaction equation of the alloy model shown in formula (2), the tritiation enthalpy change of the alloy tritiated model is calculated using the following formula (3):

[0099]

[0100] In formula (3), E(M a N b T y ), E(M a N b ) and E(T2) represent the total energy of the alloy tritiated model, the total energy of the alloy model and the energy of the gas phase T2, respectively, and y represents the number of tritium atoms in the alloy tritiated model. In the present invention, the total energy of the alloy tritiated model (E(M a N b T y )), the total energy of the alloy model (E(M a N b )) and the energy of gas phase T2 (E(T2)) can be calculated by, for example, a first-principles-based software package (VASP) or obtained by consulting a reference book.

[0101] In one embodiment, if the tritiation enthalpy change ΔH of the alloy tritiated model is <0, then the second thermodynamic stability data meets its predetermined standard; or, if the tritiated enthalpy change ΔH of the alloy tritiated model is ≥0, then the second thermodynamic stability data does not meet its predetermined standard.

[0102] In one embodiment, the second kinetic stability data is obtained by calculating the phonon vibration frequency in the lattice of the alloy tritiated model. In one embodiment, the phonon spectrum is obtained according to the phonon vibration frequency in the lattice of the alloy tritiated model. In one embodiment, the phonon vibration frequency of the alloy tritiated model can be, for example, based on density functional perturbation theory (DFPT), with the help of Phonopy software to process the unit cell structure and force constant information of the alloy tritiated model obtained in step S3, and solve the vibration frequency of the phonon in the lattice of the alloy tritiated model. The phonon spectrum obtained according to the phonon vibration frequency in the lattice of the alloy tritiated model can be performed by data processing software known in the art. In one embodiment, the predetermined standard of the second kinetic data is that there is no imaginary frequency in the phonon spectrum.

[0103] In one embodiment, the second thermal stability data is obtained by calculating the energy and root mean square displacement of the alloy model at a predetermined temperature within a predetermined time period under an NVT ensemble.

[0104] Thermal stability verification is based on the change of atomic trajectory, energy change and structural change in the material under specific conditions. The ab initio molecular dynamics (AIMD) method is used to calculate the energy change value and root mean square displacement of the alloy tritide at a constant temperature within a predetermined time under the NVT (fixed number of particles, volume and temperature) ensemble. Within the simulated time range, the energy of the alloy tritide model tends to be stable, and the displacement gradually tends to be stable, without significant violent fluctuations, indicating that the model has good thermal stability. In one embodiment, within a predetermined time, the energy change value of the alloy tritide model is less than 10%, and the alloy tritide is considered to pass the thermal stability verification. The second stability verification can determine whether the alloy tritide model is stable and easy to synthesize, as well as its stability under specific conditions.

[0105] In one embodiment, the second thermal stability data includes energy and root mean square displacement of the alloy tritide model at a predetermined temperature under the NVT ensemble.

[0106] In one embodiment, the second thermal stability data is obtained by simulating the atomic motion, interaction and structural stability of the alloy tritiated model at a constant temperature under the NVT ensemble using the ab initio molecular dynamics method. The ab initio molecular dynamics (AIMD) method is used to simulate the atomic motion, interaction and structural stability of the alloy tritiated at a constant temperature under the NVT (fixed number, volume and temperature) ensemble. By analyzing the simulated atomic trajectories, energy changes and structural changes, it is revealed whether the alloy tritiated can maintain a stable structure at a specified temperature.

[0107] In the NVT ensemble, N represents the number of atoms in the alloy tritide model, V represents the volume of the alloy tritide model, and T represents the simulated temperature. The number of atoms in the alloy tritide model is determined according to the elemental composition of the alloy tritide model, the volume of the alloy tritide model is the volume of the unit cell structure with the lowest energy of the alloy tritide model obtained in the above step S3, and the temperature can be determined according to the actual working environment temperature of the designed alloy tritium target. In one embodiment, the predetermined temperature is set to below 550K. In one embodiment, the predetermined time is 10ps.

[0108] like Figure 1 As shown, step S5, judging the stability of the alloy tritium model, wherein, when the data in the second stability verification data group meets the respective predetermined standards, performing tritium storage capacity analysis on the alloy tritium model, or, when at least one data in the second stability verification data group does not meet the predetermined standard of the data, returning to step S1.

[0109] When the data in the second stability verification data group meets the respective predetermined standards, the tritium storage capacity analysis of the alloy tritide model is performed. By analyzing the tritium storage capacity of the alloy tritide, it is determined whether the alloy can approach the real DT fusion ignition neutron irradiation environment and has a high tritium storage density.

[0110] In one embodiment, the tritium storage capacity analysis includes calculating the tritium atom density of the alloy tritide model; wherein the tritium atom density is calculated using the following formula (4):

[0111]

[0112] In the formula, ρ V represents the tritium atom density of the alloy tritiated model, N(T) is the number of tritium atoms in the alloy tritiated unit cell, V(M a N b T y ) is the unit cell volume of the alloy tritide. In the present invention, the unit cell volume V(M a N b T y ) can be calculated by the lattice parameters of the tritium alloy configuration optimized based on DFT theory. Based on the calculation results of tritium atom density, alloy materials with high tritium storage density can be screened.

[0113] In one embodiment, the tritium atom density of the alloy tritiated model is greater than the tritium atom density of the titanium tritiated model, and the tritium storage capacity analysis result of the alloy tritiated model meets the predetermined value.

[0114] In one embodiment, the tritium storage capacity analysis further includes calculating the lattice expansion rate of the alloy tritide model; wherein the lattice expansion rate is calculated using the following formula (5):

[0115]

[0116] Where △V / V represents the lattice expansion rate, V(M a N b ) is the alloy unit cell volume, V(M a N b T y ) is the unit cell volume of the corresponding alloy tritide. In the present invention, the alloy unit cell volume V(M a N b ) and the unit cell volume V(M a N b T y ) can be calculated by the lattice parameters of the tritium alloy configuration obtained by DFT theory optimization. By calculating the lattice expansion rate, the structural changes of the alloy during the tritium storage process can be analyzed, and the alloy material suitable for the tritium target can be selected. If the lattice expansion rate is small, the tritium storage density of the corresponding alloy is small and the tritium storage capacity is limited. If the lattice expansion rate is large, the crystal structure of the corresponding alloy will change greatly after tritium storage, and problems such as crystal pulverization are prone to occur.

[0117] like Figure 1 In step S6, when the tritium storage capacity analysis result meets the predetermined value, the design is completed to obtain the alloy for the alloy tritium target, or when the tritium storage capacity analysis result does not meet the predetermined value, return to step S1.

[0118] Those skilled in the art can screen out alloy materials suitable for use as tritium targets under neutron radiation conditions based on the tritium atom density and lattice expansion rate of the alloy tritium compound. The alloy for tritium targets obtained by the method of the present invention can be prepared under experimental conditions using techniques such as magnetron sputtering. The prepared new alloy material for tritium targets has a tritium density higher than that of metallic titanium, which can effectively increase the specific neutron yield of the neutron source driven by a high-current multiplier. Increasing the neutron flux can better simulate the deuterium-tritium fusion neutron radiation field environment and shorten the irradiation time of materials for fusion reactors. In addition, the new alloy material for tritium targets obtained by the present invention can also effectively increase the life of tritium targets, reduce the number of times the tritium targets are replaced, and simplify the irradiation operation process, all of which can effectively save energy and improve the irradiation efficiency of neutron sources.

[0119] The present invention also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the above method are implemented.

[0120] The present invention also provides an alloy design device, wherein the alloy is used for an alloy tritium target by storing tritium, and the device comprises: a processor and a memory for storing a computer program that can be run on the processor,

[0121] Wherein, the processor is used to execute the steps of the above method when running the computer program.

[0122] The above description is only a preferred embodiment of the present invention, and does not limit the patent scope of the present invention. All equivalent structural changes made by using the contents of the present invention specification and drawings under the inventive concept of the present invention, or directly / indirectly applied in other related technical fields are included in the patent protection scope of the present invention.

Claims

1. A method for designing an alloy for an alloy tritium target, characterized in that The following steps are involved: S1, determining the element composition of the alloy and obtaining an alloy model, wherein the element composition of the alloy is M a N b , M represents the first alloying element, N represents the second alloying element, a and b represent the atomic numbers of the first alloying element and the second alloying element, respectively; S2, obtaining a first stability data set of the alloy model; S3, determining the stability of the alloy model, wherein when the data in the first stability data group meets respective predetermined standards, obtaining an alloy tritide model based on the alloy model, wherein the element composition of the alloy tritide is: M a N b T y , T is tritium, y is the number of atoms of tritium, or When at least one data in the first stability data group does not meet the predetermined standard of the data, return to step S1; S4, obtaining a second stability data set of the alloy tritide model; S5, determining the stability of the tritiated alloy model, wherein when the data in the second stability verification data group meets respective predetermined standards, performing tritium storage capacity analysis on the tritiated alloy model, or When at least one data in the second stability verification data group does not meet the predetermined standard of the data, return to step S1; S6, when the tritium storage capacity analysis result meets the predetermined value, completing the design to obtain the alloy for the alloy tritium target, or When the tritium storage capacity analysis result does not meet the predetermined value, the process returns to step S1.

2. The method according to claim 1, wherein: The obtaining of the alloy model comprises: Construct a series of initial alloy unit cell structures with lower energy; The initial alloy unit cell structure is structurally optimized, and the unit cell structure with the lowest energy is obtained as the alloy model.

3. The method according to claim 1 or 2, wherein: The first stability data set includes first thermodynamic stability data, first kinetic stability data, and first thermal stability data.

4. The method according to claim 3, wherein: The first thermodynamic stability data is obtained by calculating the formation energy E of the alloy model. f Preferably, the formation energy of the alloy model is calculated using formula (1), In the formula, E(M a N b ) represents the total energy of the alloy model, E(M) and E(N) are the energies of a single M atom and a single N atom in the bulk phase of the alloy model, respectively; The first dynamic stability data is obtained by calculating the phonon vibration frequency in the lattice of the alloy model, and preferably, the phonon spectrum is obtained according to the phonon vibration frequency in the lattice of the alloy model; or The first thermal stability data is obtained by calculating the energy and root mean square displacement of the alloy model at a predetermined temperature and within a predetermined time period under the NVT ensemble.

5. The method according to claim 1, wherein: The obtaining of the alloy tritide model based on the alloy model comprises: Constructing a series of initial alloy tritiated unit cell structures with lower energy; The initial alloy tritiated unit cell structure is structurally optimized, and a unit cell structure with the lowest energy is obtained as the alloy tritiated unit model.

6. The method according to claim 1 or 4, wherein: The second stability data set includes second thermodynamic stability data, second kinetic stability data, and second thermal stability data.

7. The method according to claim 6, wherein: The second thermodynamic stability data is obtained by calculating the tritiation enthalpy change of the alloy model; Preferably, based on the tritiation reaction equation of the alloy model shown in formula (2), the tritiation enthalpy change of the alloy model is calculated using the following formula (3): In formula (3), E(M a N b T y ), E(M a N b ) and E(T2) represent the total energy of the alloy tritide model, the total energy of the alloy model and the energy of the gas phase T2, respectively; The second dynamic stability data is obtained by calculating the phonon vibration frequency in the lattice of the alloy tritide model, and preferably, the phonon spectrum is obtained according to the phonon vibration frequency in the lattice of the alloy tritide model; or The second thermal stability data is obtained by calculating the energy and root mean square displacement of the alloy tritium at a predetermined temperature within a predetermined time period under the NVT ensemble. Preferably, the first thermal stability data includes simulating the energy and root mean square displacement of the alloy at a predetermined temperature under the NVT ensemble.

8. The method according to claim 1, wherein: The tritium storage capacity analysis of the tritium alloy model comprises: Calculate the tritium atom density of the alloy tritide model; preferably, the tritium atom density is calculated using the following formula (4): In the formula, ρ V represents the tritium atom density of the alloy tritiated model, N(T) is the number of tritium atoms in the unit cell of the alloy tritiated model, V(M a N b T y ) is the unit cell volume of the alloy tritide model; More preferably, the tritium storage capacity analysis of the tritium alloy model further comprises: calculating the lattice expansion rate of the alloy tritide model; Preferably, the lattice expansion rate is calculated using the following formula (5): Where △V / V represents the lattice expansion rate, V(M a N b ) is the unit cell volume of the alloy model, V(M a N b T y ) is the unit cell volume of the alloy tritide model.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to claims 1 to 8 are implemented.

10. An alloy design device, wherein the alloy is used for alloy tritium target by storing tritium, characterized in that: The device comprises: a processor and a memory for storing a computer program that can be run on the processor, Wherein, when the processor is used to run the computer program, it executes the steps of the method described in claims 1 to 7.

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