Method for reconstructing energy surface of vacancy-helium-hydrogen complex and storage medium

Abstract

This invention discloses a method and storage medium for reconstructing the energy surface of vacancy-helium-hydrogen complexes. The main steps include: S1, calculating the energy of small complex clusters; S2, analyzing the formation energies of vacancy-helium and vacancy-hydrogen complexes with respect to p2 and p3, respectively; S3, selecting a suitable univariate function to fit the relationship between cluster energy and p2 and p3 at a given p1; S4, fitting the relationship between the univariate function parameters and p1; and S5, calculating the energy of arbitrary clusters and defect energy levels. This method reconstructs the energy surface of vacancy-helium-hydrogen complexes based on a class of univariate functions, enabling high-precision reproduction of the energy and energy levels of defect clusters. This reconstruction method not only accurately describes the energy of defect clusters within a known computational set but also provides a good description of the energy and energy level trends of clusters outside the computational set, exhibiting excellent extrapolation properties.

Description

Technical Field

[0001] This invention belongs to the field of nuclear material irradiation damage simulation technology, specifically relating to a method and storage medium for reconstructing the energy surface of vacancies and helium-hydrogen complexes based on a class of univariate functions. Background Technology

[0002] High-energy particles (fission products, fission neutrons, or gamma rays, etc.) bombard atoms on a crystal lattice, creating defects. The nuclear reactions then produce transmutated elements. The process of point defects and transmutated elements generated by radiation is called irradiation damage. The changes in the macroscopic properties of materials caused by these point defects and transmutated elements are called the material irradiation effect. Because experimental research on the material irradiation effect is limited by high experimental costs, long experimental times, and the difficulty in observing the microscopic structure of atoms after irradiation, computer simulation has always been one of the effective methods for studying the material irradiation effect.

[0003] When materials are irradiated with high-energy neutrons in a fusion environment, point defects and small defect clusters, such as vacancies (V) and their clusters (V), are generated in the materials. p1 The defects further diffuse and aggregate, forming large clusters of vacancy and helium-hydrogen defect complexes, such as vacancy-helium complexes (V0). p1 He p2 ), Vacancy-hydrogen complex (V p1 H p3 ), Vacancy and helium-hydrogen complex (V p1 He p2 H p3 Currently, multi-scale simulation methods are often used to study the generation, aggregation, and dissolution processes of these irradiation defects, as well as their impact on the macroscopic properties of materials.

[0004] Specifically, when using multi-scale methods to simulate microstructure evolution, the first step is usually to calculate the properties of defect interactions, such as the formation energy of the aforementioned complex and its partial derivatives with respect to the number of point defects (defect energy levels). However, due to current computational limitations, it is often only possible to calculate the structure and energy of clusters smaller than a certain size, while multi-scale simulations actually require the properties of defect clusters over a considerably large size range; furthermore, the properties of defect complexes are high-dimensional functions of the number of point defects (e.g., Vc). p1 He p2 V p1 H p3 These are bivariate functions of p1, p2 and p1, p3 respectively, while V p1 He p2 H p3 (This is a ternary function of p1, p2, and p3). Therefore, it is necessary to develop effective methods to model the energy of vacancies and helium-hydrogen complexes, and then extrapolate the properties of small-sized clusters to clusters of arbitrary sizes.

[0005] Currently, for unary vacancy clusters (V) p1 A 2 / 3 power relationship between cluster energy and p1 has been established based on capillary law, which describes the trend of defect cluster energy variation with p1 quite well. However, there is no good modeling method for binary and ternary complexes. For example, simply choosing a two-dimensional function for surface fitting often only describes the computational dataset well, but the extrapolation results in a poor description of the energy of large clusters, thus limiting the use of multi-scale simulation methods to study the synergistic effect of vacancies and helium-hydrogen. Summary of the Invention

[0006] In view of this, the present invention needs to provide a method for reconstructing the energy surface of a vacancy and helium-hydrogen complex. This method is based on a class of univariate functions to reconstruct the energy surface of a vacancy and helium-hydrogen complex, for V p1 He p2 and V p1 H p3 For the formation energy, given p1, a univariate function that satisfies the trend of formation energy variation with p2 or p3 is selected to describe the formation energy of the complex. Then, the relationship between the parameters of this univariate function and p1 is fitted, thereby reproducing the energy and energy levels of the defect clusters with high accuracy. This reconstruction method can not only describe the energy of defect clusters within the known computational set well, but also describe the trend of energy and energy levels of clusters outside the computational set very well, exhibiting good extrapolation properties.

[0007] To achieve the above objectives, the present invention adopts the following technical solution:

[0008] This invention first provides a method for reconstructing the energy surface of a vacancy and a helium-hydrogen complex, comprising the following steps:

[0009] S1. Calculate the energy of small complex clusters, where the small complex cluster refers to a vacancy-helium complex V. p1 He p2 and vacancy-hydrogen complex V p1 H p3 Where 50≤p1≤200, p2≤p1, p3≤p1;

[0010] S2. Analyze the vacancy-helium complex V separately. p1 He p2 Vacancy-hydrogen complex V p1 H p3 The formation potential changes with p2 and p3;

[0011] S3. Select a suitable univariate function to fit the relationship between cluster energy and p2 and p3 when p1 is given;

[0012] S4. Fit the relationship between the parameters of a univariate function and the change of p1;

[0013] S5. Calculate the energy of any cluster and the defect energy level.

[0014] In a further embodiment, step S1 includes the following steps:

[0015] S11, Calculate the small cluster V p1 Configuration and formation energy;

[0016] S12, in small clusters V p1 Based on this, calculate the vacancy and helium complex V separately. p1 He p2 and vacancy-hydrogen complex V p1 H p3 Configuration and energy.

[0017] In a further embodiment, in step S11, the small cluster V p1 The configuration and formation can invoke a cluster ground state configuration calculation method based on differential evolution.

[0018] In a further embodiment, in step S12, for the vacancy-helium complex V p1 He p2 He's alternative position is the empty position V. p1 The lattice position of each vacancy; for the vacancy-hydrogen complex V p1 H p3 The alternative position for H is the empty position V. p1 Each empty space in the area is surrounded by 24 tetrahedral gaps;

[0019] Each time a new He or H is added, follow the V procedure. p1 He p2+1 =V p1 He p2 +He1, V p1 H p3+1 =V p1 H p3 +H1 is added based on the previous configuration;

[0020] After each addition, static relaxation is performed to optimize the configuration;

[0021] After calculating all possible positions, place He or H in the position with the lowest energy.

[0022] In a further embodiment, in step S3, for the vacancy-helium complex V p1 He p2 The chosen univariate function is the Boltzmann function; for the vacancy-hydrogen complex V p1 H p3 The chosen univariate function is an elliptic curve function.

[0023] In a further embodiment, in step S3:

[0024] For vacancy-helium complex V p1 He p2 Given p1, the Boltzmann function is chosen to describe the formation energy of the complex:

[0025] ,

[0026] Where B is of the form of The Boltzmann function, where the independent variable x represents the variable p1. BP(p1) Let dx represent the Boltzmann function, where the function parameters [A1, A2, x0, dx] are all functions of p1, A1 and A2 are the minimum and maximum values ​​of the function, respectively, x0 represents the center of the function, and dx represents the time constant that controls the rate of increase of the function.

[0027] In a further embodiment, in step S3:

[0028] For the vacancy-hydrogen complex V p1 H p3 Given p1, choose an elliptic curve function to describe the formation energy of the complex:

[0029] ,

[0030] Where E is of the form of A function, where the independent variable x represents the variable p1. This represents an elliptic function, where the function parameters [A, B, C] are all functions of p1.

[0031] In a further embodiment, step S4 includes the following steps:

[0032] S41. Fit all p1s to the selected univariate function to obtain the data of the univariate function changing with p1;

[0033] S42. Select the polynomial fitting step S41 to fit the relationship between the univariate function parameters and p1.

[0034] In a further embodiment, step S5 includes the following steps:

[0035] S51. For a given arbitrary cluster V p1 He p2 V p1 H p3 The expression fitting the relationship between the selected univariate function parameters and p1 is called, and the corresponding function parameters of the univariate function are calculated.

[0036] S52. Call the selected unary function to calculate the energy of the cluster given p1, and given p2 and p3 respectively;

[0037] S53. Based on the calculated and predicted cluster formation energy, calculate its derivative with respect to the number of defects at the center of the cluster to obtain the energy level of the corresponding defect near the cluster.

[0038] The present invention further discloses a computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the steps of the refactoring method as described above.

[0039] The beneficial effects of this invention are as follows:

[0040] This invention reproduces the energy and energy levels of defect clusters with high precision by dividing the two-dimensional energy surface of defect clusters into univariate nonlinear functions. Specifically, it fits the energy of clusters with different numbers of He and H at a given p1 using a univariate function that conforms to their changing trends, and then fits the relationship between the parameters of the univariate function and p1 twice.

[0041] Compared with existing methods that directly use general binary functions to fit the energy of defect clusters, this reconstruction method can not only describe the energy of defect clusters in the known computation set well, but also describe the trend of cluster energy and energy levels outside the computation set very well, and has good extrapolation properties. Attached Figure Description

[0042] Figure 1 This is a flowchart of the main steps of the reconstruction method based on the energy surface of a helium-hydrogen complex and a class of univariate function vacancies disclosed in a typical embodiment of the present invention.

[0043] Figure 2 for Figure 1 Flowchart of the algorithm for reconstructing the energy surface of the vacant site and the helium-hydrogen complex;

[0044] Figure 3 The composite formation energy and model extrapolation prediction results obtained by the reconstruction method described in a typical embodiment of the present invention are as follows: Figure 3 (a) shows the vacancy-helium complex in the iron block. V p1 He p2 The result of ) Figure 3 (b) represents the vacancy-hydrogen complex in the iron bulk ( V p1 H p3 The result;

[0045] Figure 4 The vacancy-helium clusters obtained by the reconstruction method described in this invention (V p1 He p2 The V and He energy levels near ) are, among which, Figure 4 In the middle (a), the energy level is V. Figure 4 In the middle (b), the energy level is He. Detailed Implementation

[0046] The embodiments of the present invention are described in detail below. The embodiments described below are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0047] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.

[0048] In this paper, V represents a vacancy, He represents helium gas atoms produced by the transmutation material, H represents hydrogen gas atoms produced by the transmutation material, and p1, p2, and p3 represent the number of V, He, and H atoms, respectively. p1 V represents a vacancy cluster. p1 He p2 V represents a vacancy-helium complex. p1 H p3 This indicates a vacancy-hydrogen complex.

[0049] This paper proposes a method for reconstructing the energy surface of vacancies and helium-hydrogen complexes based on a class of univariate functions. Simply put, for V... p1 He p2 and V p1 H p3 For the formation energy, given p1, a univariate function that satisfies the trend of the formation energy changing with p2 or p3 is selected to describe the formation energy of the complex, and then the relationship between the parameters of the univariate function and p1 is fitted.

[0050] This paper provides a typical embodiment of a method for reconstructing the energy surface of a vacancy and a helium-hydrogen complex. The main steps are as follows: Figure 1 The steps shown are as follows:

[0051] S1. Calculate the energy of small complex clusters.

[0052] In this step, the small complex clusters refer to vacancy-helium complexes V. p1 He p2 and vacancy-hydrogen complex V p1 H p3 Specifically, this step mainly includes the following steps:

[0053] S11, Calculate the small cluster Vp1 Configuration and formation energy of the small cluster V p1 The configuration and formation of this small cluster V can be calculated using methods commonly used in this field based on differential evolution, which will not be elaborated here. p1 Its p1 is between 50 and 200.

[0054] S12, V in step S11 p1 Calculate V based on p1 He p2 and V p1 H p3 The configuration and energy, where p2≤p1, p3≤p1; the specific calculation method is as follows:

[0055] For V p1 He p2 He's alternative position is in V. p1 The alternative location of the region (i.e., V) p1 The lattice position of each vacancy in V); for V p1 H p3 The alternative position for H is V. p1 Each empty space in the area is surrounded by 24 tetrahedral gaps;

[0056] Each time a new He or H is added, it is added based on the previous configuration, i.e., V. p1 He p2+1 =V p1 He p2 +He1, V p1 H p3+1 =V p1 H p3 +H1;

[0057] After each addition, static relaxation is performed to optimize the configuration. It can be understood that the static relaxation here can simply call the static relaxation method commonly used in this field, so it will not be elaborated further.

[0058] After calculating all possible positions, He or H is placed in the position with the lowest energy.

[0059] S2, Analyze V separately p1 He p2 、V p1 H p3 The trend of formation energy with p2 and p3

[0060] Based on the characteristics of the interaction of He inert gases (preferring to occupy the vacuum, i.e., the central core region of vacancy clusters is unknown), we obtain the following interaction trend: for V p1 Hep2 Since low-concentration He occupies the core region of the complex, the cluster formation energy remains almost unchanged when p2 is less than a certain range, which means that the two-dimensional surface of the formation energy is initially relatively flat in the p2 direction; then as p2 increases, due to the rigid repulsion between He-He, the He energy level rises, and the cluster formation energy tends to rise.

[0061] Based on the chemisorption characteristics of H (easily adsorbed on the surface), we obtain the following interaction trend: And for V... p1 H p3 When p3 is small, since H is dispersed and occupies the surface edge position of the complex, and H has a low energy level in the bulk, its energy level becomes negative after being attracted by vacancies on the cluster surface. Therefore, the formation energy of the complex initially decreases almost linearly with p3. Then, as p3 increases, the repulsion between HH causes the formation energy to start to rise.

[0062] S3. Select a suitable univariate function to fit the relationship between cluster energy and p2 and p3 when p1 is given.

[0063] Specifically, for V p1 He p2 Given p1, select a Boltzmann function that satisfies the qualitative analysis trend in step S2 to describe the formation energy of the complex:

[0064] ,

[0065] Where B is of the form of The Boltzmann function, where the independent variable x represents the variable p1. BP(p1) Let represent the Boltzmann function, where the function parameters [A1, A2, x0, dx] are all functions of p1, A1 and A2 are the minimum and maximum values ​​of the function, respectively, x0 represents the center of the function, and dx represents the time constant controlling the rate of increase of the function; Boltzmann function fitting is performed for different numbers of He in each p1 of the small cluster in the computation set.

[0066] For V p1 H p3 Given p1, select an elliptic curve function that satisfies the qualitative analysis trend in step S2 to describe the formation energy of the complex:

[0067] ,

[0068] Where E is of the form of A function, where the independent variable x represents the variable p1. The function is elliptic-like, with parameters [A, B, C] all being functions of p1. Elliptic-like functions are fitted to different numbers of H in each p1 of the small clusters in the computation set.

[0069] S4. Fitting the relationship between the parameters of a univariate function and p1.

[0070] Specifically, this step includes the following steps:

[0071] S41. After fitting all p1s in step S3, we obtained the data on the changes of Boltzmann function parameters and elliptic curve function parameters with p1.

[0072] S42. Select a polynomial to fit the relationship between the above function parameters and p1. In some typical embodiments of the present invention, the selected polynomial is A / B / C=ap1. 2 +bp1+c, where a, b, and c are the parameters to be fitted.

[0073] S5. Calculate the energy of arbitrary clusters and defect levels.

[0074] Specifically, this step includes the following steps:

[0075] S51. For a given arbitrary cluster V p1 He p2 V p1 H p3 First, the Boltzmann function is called. Elliptic curve functions The relationship between parameters and p1, and the fitting of a polynomial expression (e.g., A / B / C=ap1). 2 +bp1+c, where a, b, and c are the parameters to be fitted), calculate the corresponding function parameters of the two functions;

[0076] S52. Using Boltzmann functions and elliptic curve-like functions, calculate the energy of the cluster given p1, and given p2 and p3 respectively.

[0077] S53. Based on the calculated and predicted cluster formation energy, its derivative with respect to the number of defects at the center of the cluster is further calculated to obtain the energy levels of corresponding defects near the cluster. Among these, vacancies and He in V... p1 He p2 The nearby energy levels are respectively defined by the formula: , Calculation, while vacancy, H in V p1 H p3 The nearby energy levels are respectively defined by the formula: , calculate.

[0078] In a typical embodiment of this document, such as Figure 2 As shown, the specific algorithm flow of the reconstruction method described in this paper is as follows:

[0079] S101, Begin, proceed to S102;

[0080] S102, Set the number of vacancies p1, the number of helium atoms p2, and the number of hydrogen atoms p3 in the cluster, then proceed to S103;

[0081] S103, Calculating Complex Clusters (V p1 He p2 and V p1 H p3 Energy enters S104;

[0082] S104. Analyze the energy variation trend of the complex with p2 and p3 respectively, and proceed to S105;

[0083] S105. Select a univariate function to fit the relationship between cluster energy and p2 and p3 when p1 is given, where p1 is within the size range of the cluster when the direct cluster formation energy is reached (e.g., 50-200). Iterate through all p1s to perform this fitting step, and proceed to step S106.

[0084] S106. Determine if p1 is greater than the input range of 50-200. If yes, proceed to S107; otherwise, return to S105.

[0085] S107. Fit the relationship between the parameters of the univariate function and p1, then proceed to S108;

[0086] S108. Input any combination of p1, p2 and p1, p3, and proceed to S109;

[0087] S109: Call the fitting expression of the relationship between the univariate function parameters and p1, calculate the univariate function parameters when p1 is given, and proceed to S110;

[0088] S110, calculate cluster energy and defect energy level, then proceed to S111;

[0089] S111, End.

[0090] The reconstruction method presented in this paper divides the two-dimensional energy surface of defect clusters using a univariate nonlinear function. Specifically, for cluster energies of different quantities of He and H at a given p1, a univariate function conforming to their variation trend is fitted. Subsequently, the parameter of the univariate function is fitted a second time to reflect the relationship between p1 and the parameters, thereby reproducing the energy and energy levels of defect clusters with high accuracy. This reconstruction method not only accurately describes the energy of defect clusters within the known computational set but also provides a good description of the energy and energy level trends of clusters outside the computational set, exhibiting excellent extrapolation properties.

[0091] In another typical embodiment of this document, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, causes the processor to perform the steps of the refactoring method as described above.

[0092] Those skilled in the art will understand that embodiments of the present invention can be provided as methods or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0093] This invention is described with reference to flowchart illustrations and / or block diagrams of methods and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be stored in a computer-readable storage medium capable of directing a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means implemented in the flowchart illustrations and block diagrams. Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0094] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0095] The following specific application examples will provide a more complete explanation of the reconstruction method described in this paper. It should be noted that the application examples below are for illustrative purposes only and do not limit the scope of this application in any way. In addition, unless otherwise specified, methods that do not specify conditions or steps are conventional methods.

[0096] Application Examples

[0097] This application example uses the reconstruction method described in this paper, where the material is a body-centered cubic iron block with a lattice constant of 2.8553 Å. The directly calculated cluster size ranges from 1 to 120, and the input p1 when fitting the predicted cluster formation energy function falls within this range, while p2 ≤ p1 and p3 ≤ p1. The predicted cluster size p1 ranges from 121 to 300, while p2 ≤ p1 and p3 ≤ p1.

[0098] The final iron block contained vacancy-helium complexes ( V p1 He p2 ) Formation energy ( ) and model extrapolation prediction results such as Figure 3 As shown in (a), the vacancy-hydrogen complex ( V p1 H p3 ) Formation energy ( ) and model extrapolation prediction structure such as Figure 3 As shown in (b). Furthermore, Figure 4 The figure shows the vacancy-helium complex calculated using the reconstruction method described in this paper. V p1 He p2 The V and He energy levels are near the vicinity.

[0099] pass Figure 3 The results show that the fitting method using the present invention... V p1 He p2 Formation energy, V p1 H p3 The formation energy agrees well with the cluster formation energy obtained from the computation set, and the trend of cluster formation energy outside the computation range with (p1, p2) or (p1, p3) is consistent with the expected analysis.

[0100] pass Figure 4 The results show that the V and He predicted by this invention are in V p1 He p2 The energy levels in the vicinity also conform to expectations. For example, given p1, the V energy level initially changes relatively flat with p2. After p2 exceeds a certain value, the V energy level decreases, which means that the excess He in the vacancy cluster at this time lowers the V energy level and can promote the absorption of V. The energy level of He near this cluster initially changes very flat with p2. Subsequently, as the excess He accumulates in the cluster, the He energy level rises.

[0101] Therefore, in summary, the reconstruction method in this invention can reconstruct the energy surface of the VHe / VH complex relatively accurately.

[0102] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0103] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this invention patent should be determined by the appended claims.

Claims

1. A method for reconstructing the energy surface of a vacancy-helium-hydrogen complex, characterized in that, Includes the following steps: S1. Calculate the energy of small complex clusters, where the small complex cluster refers to a vacancy-helium complex V. p1 He p2 and vacancy-hydrogen complex V p1 H p3 Where 50≤p1≤200, p2≤p1, p3≤p1; S2. Analyze the vacancy-helium complex V separately. p1 He p2 Vacancy-hydrogen complex V p1 H p3 The formation potential changes with p2 and p3; S3. Select a suitable univariate function to fit the relationship between cluster energy and p2 and p3 for a given p1; for the vacancy-helium complex V p1 He p2 Given p1, the Boltzmann function is chosen to describe the formation energy of the complex: Where B is of the form of The Boltzmann function, where the independent variable x represents the variable p1. BP(p1) Let represent the Boltzmann function, where the function parameters [A1, A2, x0, dx] are all functions of p1, A1 and A2 are the minimum and maximum values ​​of the function, respectively, x0 represents the center of the function, and dx represents the time constant controlling the rate of increase of the function; for the vacancy-hydrogen complex V p1 H p3 Given p1, choose an elliptic curve function to describe the formation energy of the complex: Where E is of the form of A function, where the independent variable x represents the variable p1. This represents an elliptic function, where the function parameters [A, B, C] are all functions of p1; S4. Fit the relationship between the parameters of the univariate function and the change of p1; specifically including the following steps: S41. Fit all p1s to the selected univariate function to obtain the data of the univariate function changing with p1; S42. Select the relationship between the univariate function parameters and p1 described in step S41 of the polynomial fitting process; S5. Calculate the energy of any cluster and the defect energy level.

2. The method for reconstructing the energy surface of the vacancy and helium-hydrogen complex as described in claim 1, characterized in that, Step S1 includes the following steps: S11, Calculate the small cluster V p1 Configuration and formation energy; S12, in small clusters V p1 Based on this, calculate the vacancy and helium complex V separately. p1 He p2 and vacancy-hydrogen complex V p1 H p3 Configuration and energy.

3. The method for reconstructing the energy surface of the vacancy and helium-hydrogen complex as described in claim 2, characterized in that, In step S11, the small cluster V p1 The configuration and formation can invoke a cluster ground state configuration calculation method based on differential evolution.

4. The method for reconstructing the energy surface of the vacancy and helium-hydrogen complex as described in claim 2, characterized in that, In step S12, for the vacancy-helium complex V p1 He p2 He's alternative position is the empty position V. p1 The lattice position of each vacancy; for the vacancy-hydrogen complex V p1 H p3 The alternative position for H is the empty position V. p1 Each empty space in the area is surrounded by 24 tetrahedral gaps; Each time a new He or H is added, follow the V procedure. p1 He p2+1 =V p1 He p2 +He1, V p1 H p3+1 =V p1 H p3 +H1 is added based on the previous configuration; After each addition, static relaxation is performed to optimize the configuration; After calculating all possible positions, place He or H in the position with the lowest energy.

5. The method for reconstructing the energy surface of the vacancy and helium-hydrogen complex as described in claim 1, characterized in that, Step S5 includes the following steps: S51. For a given arbitrary cluster V p1 He p2 V p1 H p3 The expression fitting the relationship between the selected univariate function parameters and p1 is called, and the corresponding function parameters of the univariate function are calculated. S52. Call the selected unary function to calculate the energy of the cluster given p1, and given p2 and p3 respectively; S53. Based on the calculated and predicted cluster formation energy, calculate its derivative with respect to the number of defects at the center of the cluster to obtain the energy level of the corresponding defect near the cluster.

6. A computer-readable storage medium storing a computer program that, when executed by a processor, causes the processor to perform the steps of the reconstruction method as described in any one of claims 1-5.

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