Method for calculating and predicting ferrite martensitic stainless steel oxide layer defect diffusion behavior

Abstract

The invention discloses a method for calculating and predicting a defect diffusion behavior of a ferrite martensitic stainless steel oxide layer. The method belongs to the technical field of new materials, and comprises the following operation steps: respectively constructing crystal structure models of a ferrite martensitic stainless steel oxide layer with different defect sites by using MS software, and converting a structure data file into a. Vasp file format readable by VASP software by using VESTA software; adopting VASP software to calculate defect formation energy of different defect sites; screening to form stable defects with low energy, and constructing an initial state model and a final state model of defect diffusion; using a CI-NEB method to calculate diffusion energy barriers of the defect in different paths, and using an approximation formula after approximation optimization to calculate a diffusion rate; and further analyzing the behavior and influence of the defect through a state density map and an electronic local area map. According to the method, the diffusion energy barrier and diffusion rate of the defect between different paths are effectively predicted through a theoretical calculation method, and required data support can be provided for phase field simulation and molecular dynamics simulation.

Description

Technical Field

[0001] The present invention belongs to the field of new material technology and relates to a method for calculating and predicting the diffusion behavior of defects in the oxide layer of ferritic martensitic stainless steel; specifically, it relates to a method for calculating and predicting the diffusion behavior of defects in ferritic martensitic stainless steel based on first principles. Background Art

[0002] At present, nuclear energy, as a baseload energy with high energy density and low carbon emissions, plays an irreplaceable role in achieving the goal of carbon neutrality. The cladding material serves as the most direct isolation barrier between the fuel and the coolant. It faces a series of severe tests such as high temperature, high pressure, corrosion and strong radiation. Among the many candidate materials, ferritic / martensitic stainless steel (such as T91, HT9, etc.) stands out for its unique comprehensive performance. At the same time, it has engineering advantages such as controllable manufacturing costs and excellent high-temperature strength. It is recognized by the international nuclear energy community as the preferred choice for lead-based fast reactor cladding materials. However, during long-term service, the surface oxide layer of the material is subjected to the multi-field coupling of radiation-temperature-corrosion, which will form microscopic defects such as vacancies, interstitial atoms, and dislocation rings. The diffusion behavior of these defects not only accelerates the thickening of the oxide layer, but is also likely to cause crack initiation and expansion, and ultimately lead to failure of the cladding structure.

[0003] The diffusion coefficient of oxide layer defects is a key kinetic parameter for the material's resistance to environmental corrosion. How to quantitatively evaluate it has become a key issue in the development of nuclear energy research. Existing research currently has several significant limitations and bottlenecks: (1) The need to reproduce extreme conditions such as high temperature, high pressure, and irradiation during the experiment consumes a lot of resources; (2) The irradiation corrosion experiment cycle of cladding materials is long, and some experiments often take months or even longer; (3) The dynamic evolution of defects in extreme environments is difficult to capture in situ. With the current development of observation and analysis measurement equipment, some parameters in the nuclear reaction process are difficult or impossible to measure experimentally; (4) Nuclear irradiation-related experiments are dangerous and require high personnel and equipment. However, theoretical calculation research also has problems such as low calculation accuracy, high difficulty, and difficulty in reproducing high temperatures. A new method is urgently needed to solve the above problems. Summary of the Invention

[0004] In view of the above problems, the present invention aims to propose a method for calculating and predicting the diffusion behavior of defects in the oxide layer of ferritic martensitic stainless steel; that is, a method for calculating and predicting the diffusion behavior of defects in ferritic martensitic stainless steel based on first principles.

[0005] The technical solution of the present invention is: a method for calculating and predicting the diffusion behavior of oxide layer defects in ferritic and martensitic stainless steels according to the present invention; comprising the following steps:

[0006] (1) Based on the database and MS software, the crystal structure model of the main components of the ferrite-martensitic stainless steel oxide layer, Fe3O4 and FeCr2O4, was constructed, and the structural data file was converted into the .vasp file format readable by VASP using VESTA software;

[0007] (2) Using the density functional theory (DFT)-based software VASP, the defect-free Fe3O4 and FeCr2O4 materials were initially constructed and the DFT+U method was used to select different U value parameters for structural relaxation. After self-consistent convergence, the results were analyzed and extracted. The mechanical properties of Fe3O4 and FeCr2O4 were calculated using the energy-strain method, and the structure and mechanical properties were compared to select the U value parameter closest to the experimental results.

[0008] (3) Based on the defect-free structure model established in step (1), vacancy defect models and interstitial defect models of Fe and O are constructed according to the types of defect sites, structural relaxation is performed using the parameters screened in step (2), and the most stable defect formation site is determined by the defect crystal formation energy;

[0009] (4) Based on the stable defect sites determined in step (3), the diffusion paths of vacancy defects and interstitial defects are constructed respectively, the defect-free ideal model established in step (1) is subjected to 2×2×2 cell expansion processing, and the initial state model and final state model of Fe3O4 and FeCr2O4 are established according to the diffusion paths;

[0010] (5) Combining density functional theory and transition state calculation method, use VASP software with plug-in compilation to calculate the diffusion energy barrier of the defect diffusion path in step (4), substitute the diffusion energy barrier into the approximately optimized diffusion coefficient formula, and obtain the diffusion energy barrier of different diffusion paths;

[0011] (6) For the defect model constructed in step (4), static self-consistent calculations and non-static self-consistent calculations are performed. The results are analyzed to extract the ELF and DOS diagrams of Fe3O4 and FeCr2O4 after the defect influence. By comparing with the results of step (2), the influence of defects on the electronic structure and energy band can be obtained.

[0012] Furthermore, in step (1), the Fe3O4 and FeCr2O4 are selected to have a structural configuration of space group Fd-3m;

[0013] The VESTA software imports a structure file as a .cif structure file and exports a structure file as a .vasp structure file.

[0014] Furthermore, in step (1), the specific steps are:

[0015] (1.1) Obtain the lattice parameters, atomic coordinate positions, bond lengths and angles of the initial structures of defect-free Fe3O4 and FeCr2O4 based on literature and databases;

[0016] (1.2) Use VESTA software to preliminarily construct defect-free Fe3O4 and FeCr2O4, obtain the structure of defect-free Fe3O4 and FeCr2O4 and convert their structure files into .vasp file format.

[0017] Furthermore, in step (2), the specific settings of the calculation parameters include the wave function cutoff energy of 500 eV and the convergence standard of the force The convergence criterion of energy is 10 -6 The structure optimization was carried out under the parameter of eV, the U value of Fe and Cr elements was selected in the range of 2-4eV, and the K point was sampled using the Γ-centered sampling method with a sampling density of 7×7×7.

[0018] Furthermore, in step (2), the specific steps are:

[0019] (2.1) Using VASP software based on density functional theory to optimize the relaxation of defect-free Fe3O4 and FeCr2O4 structures;

[0020] (2.2) Based on the optimized model obtained by the above calculation, a series of Fe3O4 and FeCr2O4 models with a volume expansion ratio of 0.9-1.1 and a step size of 0.05 were constructed;

[0021] (2.3) Based on a series of models of different volumes constructed in step (2.2), structural optimization is performed to obtain the system energy, a volume-energy fitting curve is established according to the volume, and the bulk modulus is obtained according to the slope;

[0022] (2.4) Compare the bulk modulus and structural parameters calculated in step (2.3) with the experimental values in the literature, select the group with the smallest error, and use this parameter as the standard for subsequent steps;

[0023] (2.5) Change the U value of Fe and Cr elements within the range of 2-4 eV with a step size of 0.5 eV, and repeat the above steps until the group with the lowest error with the experimental results or literature values is selected, and record its parameters.

[0024] Furthermore, there are four defect sites in Fe3O4, of which the wyckoff positions of the two substitutional sites are 8a and 16d, and the Wyckoff positions of the two interstitial sites are 16c and 32e; there are two defect sites in FeCr2O4, whose wyckoff positions are 16c and 32e.

[0025] Furthermore, in step (3), the formula for calculating the defect system formation energy is as follows. The calculation formula for the formation energy of FeCr2O4 is the same as that of Fe3O4:

[0026]

[0027]

[0028] Where, E Fe24O32 is the total energy of ideal Fe3O4;

[0029] is the defect formation energy of the vacancy defect;

[0030] is the defect formation energy of the interstitial defect;

[0031] E M23O32 is the substitutional doped Fe3O4 with dopant atoms M and the total energy;

[0032] EM Fe24O32 is the total energy of interstitially doped Fe3O4 with dopant atoms M;

[0033] μ Fe is the cohesive energy of body-centered cubic Fe (energy per atom);

[0034] μ M is the average per-atom energy of the dopant atoms.

[0035] Furthermore, the calculation formula for the defect formation energy of FeCr2O4 is the same as that of Fe3O4.

[0036] Furthermore, in the calculation process of step (3), Fe and Cr are corrected using the DFT+U method, with Fe corrected using a U value of 3 eV and Cr corrected using a U value of 3.5 eV.

[0037] Furthermore, the calculation formula of the diffusion coefficient in step (5) is as follows:

[0038]

[0039] Where L represents the length of the diffusion path;

[0040] c is a constant, c = 6 in a three-dimensional system;

[0041] z is the coordination number;

[0042] τ is the time interval between two migrations of the same atom in the same path;

[0043] R0 is the trial frequency;

[0044] Eα is the reaction activation energy;

[0045] m is the mass of the diffusing atom;

[0046] k B is the Boltzmann constant;

[0047] T is temperature.

[0048] Furthermore, the diffusion coefficient calculation in step (5) is based on the VASP software package compiled with the Transition State Tools for VASP (VTST) plug-in. In the calculation process, the plane wave cutoff energy is selected as 400 eV, and the convergence criterion of the force is The convergence criterion of energy is 10 -6 eV,U Fe =3eV, U Cr =3.5eV.

[0049] The beneficial effects of the present invention are: 1. The present invention provides a method for predicting the diffusion behavior of oxide layer defects in ferritic martensitic stainless steel based on first-principles calculations, which explains the influence of internal defects in the oxide layer on the structure, mechanical properties and electronic properties of the oxide layer; 2. The present invention is based on first-principles calculations of density functional theory, and by inputting basic information such as defect information and element pseudopotentials, parameters such as oxide layer defect formation energy and defect diffusion coefficient can be obtained, which can provide basic data for phase field simulation and molecular dynamics simulation; 3. The data predicted by the present invention has a very small error compared with the data obtained by existing experimental measurements, and can be extended to different diffusion paths; 4. The present invention adopts the form of calculation, which reduces the high cost caused by experimental equipment and experimental materials, and the time period is shorter and the process is easier to control. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 is a flow chart of the method of the present invention;

[0051] Figure 2 Schematic diagrams of Fe3O4 and FeCr2O4 models selected in the embodiments of the present invention, wherein Figure (a) is the Fe3O4 model and Figure (b) is the FeCr2O4 model;

[0052] Figure 3 This is a comparison of the diffusion coefficients of Fe3O4 under the influence of point defects in an embodiment of the present invention and that of ideal Fe3O4;

[0053] Figure 4 This is a comparison of the diffusion coefficients of FeCr2O4 under the influence of point defects in an embodiment of the present invention and that of ideal FeCr2O4;

[0054] Figure 5is an electronic state density diagram of Fe3O4 under the influence of defects in an embodiment of the present invention;

[0055] Figure 6 : is the electronic state density diagram of FeCr2O4 under the influence of defects in an embodiment of the present invention. DETAILED DESCRIPTION

[0056] The specific technical solutions of the present invention are further described in detail below with reference to specific examples.

[0057] As shown in the figure, the present invention describes a method for calculating and predicting the diffusion behavior of defects in the oxide layer of ferritic martensitic stainless steel. The method uses the first principles to calculate the formation energy of different defect sites, determine stable defects, and calculate the diffusion energy barrier for the diffusion of defects between different sites by formulating defect paths and using the transition state search method. The diffusion coefficient of the corresponding path can be determined in combination with the optimized diffusion coefficient formula. The crystal DOS curve and ELF diagram under the influence of defects can illustrate the influence of defects on the electronic structure and energy band of the crystal, and then predict the influence of defects on the diffusion behavior of defects in the oxide layer of ferritic martensitic stainless steel.

[0058] Example

[0059] Step 1: Construct a crystal structure model of the ferrite-martensitic stainless steel oxide layer. The specific process includes:

[0060] Step 1-1: Construct a Fe3O4 structural model with the chemical formula Fe3O4, space group number 225, and space group F3-3m. The specific structural model is as follows Figure 2 As shown in Figure (a), the yellow atoms represent Fe atoms, and the red atoms represent O atoms. The atomic distribution is highly symmetrical: atoms occupy the vertices and face centers of the cubic unit cell. Each unit cell contains 4 atoms, the vertex atoms are shared by 8 adjacent unit cells, and the face center atoms are shared by 2 unit cells. Constructing the structural model of FeCr2O4 FeCr2O4 and Fe3O4 both belong to the cubic crystal system and have a spatial symmetry group of F3-3m. The specific structural model is as follows Figure 2 As shown in (b), yellow atoms represent Fe atoms, blue atoms represent Cr atoms, and red atoms represent O atoms.

[0061] Step 1-2: Build the structure using Materials Studios, export the built structure in .cif format, and convert it into .vasp structure file type using VESTA software.

[0062] The defect model adopts the most stable state model.

[0063] The associated .vasp file uses the inverted lattice vector.

[0064] Step 2: Using the density functional theory (DFT)-based software VASP, the DFT+U method was used to select different U value parameters for structural relaxation of the initially constructed FeCr2O4 and Fe3O4 materials. After self-consistent convergence, the results were analyzed and extracted. The energy-strain method was then used to calculate the mechanical properties of Fe3O4 and FeCr2O4. The structure and mechanical properties were compared to select the U value parameter that was closest to the experimental results. The specific process includes:

[0065] Step 2-1: Based on the density functional theory, VASP software was used to optimize the structure of defect-free Fe3O4 and FeCr2O4. The structural optimization parameters were set as follows: the wave function cutoff energy was 500 eV, and the convergence standard of the force was The convergence criterion of energy is 10 -6 The structure optimization was carried out under the parameter of eV, the U value of Fe and Cr elements was selected in the range of 2-4eV, and the K point was sampled using the Γ-centered sampling method with a sampling density of 7×7×7;

[0066] Step 2-2: Calculate the mechanical properties using the energy-strain method. By adjusting the size of the structural parameters, a series of structural models with different volumes are constructed. In this embodiment, the volume expansion ratio is from 0.9 to 1.1, with a step size of 0.05, for a total of 5 points. Relaxation optimization is performed on the structural model of each volume to obtain its ground state energy;

[0067] Step 2-3: Use the volume expansion ratio as the left side of the horizontal axis and the obtained ground state energy as the vertical axis coordinate. Fit the EV curve of energy and volume through the binomial equation, and obtain the corresponding bulk modulus of the system through the slope of the fitting curve;

[0068] Step 2-4: Compare the structural parameters and mechanical properties calculated values corresponding to each U value with the literature range, select the group with the smallest error, and use the parameters of this group as the basic calculation parameters for subsequent calculations;

[0069] Step 3: Based on the constructed ideal crystal structure model, construct the vacancy defect model and interstitial defect model of Fe and O, calculate the defect formation energy of the system, and determine the most stable defect site through the defect formation energy;

[0070] Among them, there are four defect sites constructed by Fe3O4, of which the wyckoff positions of the two substitution sites are 8a and 16d, and the Wyckoff positions of the two interstitial sites are 16c and 32e; FeCr2O4 has two defect sites, whose wyckoff positions are 16c and 32e.

[0071] The defect formation energy of the vacancy defect and interstitial defect of Fe3O4 can be calculated according to the following formula:

[0072]

[0073]

[0074] Where, E Fe24O32 is the total energy of ideal Fe3O4;

[0075] is the defect formation energy of the vacancy defect;

[0076] is the defect formation energy of the interstitial defect;

[0077] E M23O32 is the substitutional doped Fe3O4 with dopant atoms M and the total energy;

[0078] EM Fe24O32 is the total energy of interstitially doped Fe3O4 with dopant atoms M;

[0079] μ Fe is the cohesive energy of body-centered cubic Fe (energy per atom);

[0080] μ M is the average per-atom energy of the dopant atoms;

[0081] The calculation formula of the defect formation energy of FeCr2O4 is the same as that of Fe3O4;

[0082] Step 4: Based on the stable defect sites, the diffusion paths of vacancy defects and interstitial defects are constructed respectively, and the initial and final state models of Fe3O4 and FeCr2O4 are established according to the diffusion paths. The specific steps include:

[0083] Step 4-1: Selecting a diffusion path for study. Based on the calculation results of defect formation energy, the stable vacancy defect wyckoff position of Fe3O4 is 8a, the stable vacancy defect wyckoff position is 16d, the stable vacancy defect wyckoff position of FeCr2O4 is 16c, and the stable vacancy defect wyckoff position is 32e. In the embodiment, the diffusion path selected is the diffusion path between vacancies;

[0084] Step 4-2: Perform a 2×2×2 cell expansion on the ideal defect-free model of Fe3O4 and FeCr2O4 in VESTA software. Select a pair of the most adjacent stable vacancy defects and use the configurations with one of the point defects as the initial and final states of defect diffusion. Delete the atoms at the corresponding defect sites using Materials Studios or VESTA to construct the initial and final state models of defect diffusion.

[0085] Step 4-3: Export the constructed initial and final states respectively and convert them into .vasp files through VESTA;

[0086] Step 5: Combine density functional theory and transition state calculation method, use VASP software with plug-in compilation to calculate the diffusion energy barrier of the defect diffusion path, substitute the diffusion energy barrier into the optimized diffusion coefficient formula, and obtain the diffusion energy barrier of different diffusion paths. The specific steps include:

[0087] Step 5-1: Perform structural relaxation on the initial and final state models of defect diffusion, and verify the optimized lattice gap using the VTST dist.pl script to ensure that the return value is less than 5A.

[0088] Step 5-2: Based on the initial and final state structure output files, use the nebmake.pl script of VTST to insert a series of intermediate states of the diffusion path, with the number of insertion points being 3 or 5;

[0089] Step 5-3: Use the CI-NEB method to call the VASP software compiled with the VTST plug-in for calculation. The specific parameters are set as follows: the plane wave cutoff energy is 400 eV, the convergence standard of the force is The convergence criterion of energy is 10 -6 eV,U Fe =3eV, U Cr =3.5eV, the K-space grid density is divided using the MP method, and the density is set to 4×4×4;

[0090] Step 5-4: Use the VTST script nebresults.pl to package and output the calculation results;

[0091] Step 5-5: Determine the diffusion energy barrier of the diffusion path based on the data, and substitute the diffusion energy barrier into the approximately optimized diffusion coefficient formula to solve for the diffusion coefficient;

[0092] The calculation formula of the diffusion coefficient is as follows:

[0093]

[0094] Where L represents the length of the diffusion path;

[0095] c is a constant, c = 6 in a three-dimensional system;

[0096] z is the coordination number;

[0097] τ is the time interval between two migrations of the same atom in the same path;

[0098] R0 is the trial frequency;

[0099] E α is the reaction activation energy;

[0100] m is the mass of the diffusing atom;

[0101] k B is the Boltzmann constant;

[0102] T is temperature.

[0103] Figure 3 A comparison of the diffusion coefficients of Fe3O4 under the influence of point defects in the embodiment and that of ideal Fe3O4;

[0104] Figure 4 This is a comparison of the diffusion coefficients of FeCr2O4 under the influence of point defects in the embodiment and that of ideal FeCr2O4;

[0105] Depend on Figures 3-4 It can be seen that under the influence of vacancy defects, the crystal lattice structure undergoes a certain amount of deformation, resulting in a change in the migration energy, a reduction in the migration energy barrier, and an increase in the diffusion coefficient; the results predicted by theoretical calculations are very consistent with the approximate range given in the literature or experiments; the introduction of defects will have a greater impact on the diffusion of crystal defects, and the diffusion coefficient will increase by an order of magnitude.

[0106] Step 5: Calculate and extract the ELF and DOS diagrams of Fe3O4 and FeCr2O4 after defect influence, and compare and analyze the influence of defects on electronic structure and energy band.

[0107] The self-consistent calculation and band structure calculation of Fe3O4 and FeCr2O4 defect structures were performed using the VASP software based on density functional theory. The specific parameters were set as follows: the wave function cutoff energy was 500 eV, the convergence standard of the force was The convergence criterion of energy is 10 -6 The structure optimization was performed under the parameter of Γ-MK-Γ. The U value of Fe and Cr elements was selected in the range of 2-4 eV. The K point was sampled using the Γ-centered sampling method with a sampling density of 7×7×7. The parameter LELF=.TRUE. was set. The path of high symmetric points in K space in the band structure calculation was Γ-MK-Γ.

[0108] Figure 5 The electronic state density diagram of Fe3O4 under the influence of defects in the embodiment;

[0109] Figure 6 This is the electronic state density diagram of FeCr2O4 under the influence of defects in the embodiment.

[0110] Depend on Figures 5-6It can be seen that due to the strong effect of Fe and Cr vacancies on the charge distribution of Fe3O4 and FeCr2O4 matrices, the DOS curve of Fe3O4 / FeCr2O4 under the action of Fe and Cr vacancies is not zero at the Fermi level, showing the properties of a conductor, while the DOS curve of Fe3O4 / FeCr2O4 under the action of O vacancies is still zero at the Fermi level and there is a large band gap, showing the properties of an insulator; the effects of defects on Fe3O4 / FeCr2O4 are consistent, which shows that the influence of metal atom vacancy defects on the matrix performance is more obvious.

[0111] In summary, this method of predicting the diffusion behavior of defects in ferritic martensitic stainless steel based on first-principles calculations will effectively evaluate the impact of defects on the oxide layer of cladding materials and provide basic data to provide theoretical guidance for irradiation defect corrosion.

Claims

1. A method for calculating and predicting the diffusion behavior of oxide layer defects in ferritic and martensitic stainless steel, characterized in that: The steps are as follows: Step (1): Based on the database and MS software, the crystal structure model of the main components of the ferrite-martensitic stainless steel oxide layer, Fe3O4 and FeCr2O4, was constructed, and the structure data file was converted into a .vasp file format readable by VASP using VESTA software; Step (2): Using the density functional theory-based software VASP, the initially constructed defect-free Fe3O4 and FeCr2O4 materials were subjected to structural relaxation using the DFT+U method with different U value parameters. After self-consistent convergence, the results were analyzed and extracted. The mechanical properties of Fe3O4 and FeCr2O4 were calculated using the energy-strain method, and the structure and mechanical properties were compared to select the U value parameter closest to the experimental results. Step (3): Based on the defect-free structure model established in step (1), vacancy defect models and interstitial defect models of Fe and O are constructed according to the types of defect sites, structural relaxation is performed using the parameters screened in step (2), and the most stable defect formation site is determined by the defect crystal formation energy; Step (4): Based on the stable defect sites determined in step (3), the diffusion paths of vacancy defects and interstitial defects are constructed respectively, the defect-free ideal model established in step (1) is expanded, and the initial state model and final state model of Fe3O4 and FeCr2O4 are established according to the diffusion paths; Step (5): Combining density functional theory and transition state calculation method, use VASP software with plug-in compilation to calculate the diffusion energy barrier of the defect diffusion path, substitute the diffusion energy barrier into the approximately optimized diffusion coefficient formula, and obtain the diffusion energy barrier of different diffusion paths; Step (6): For the constructed defect model, static self-consistent calculations and non-static self-consistent calculations are performed, the results are analyzed, and the ELF and DOS diagrams of Fe3O4 and FeCr2O4 after the defect influence are extracted. By comparing with the results of step (2), the influence of the defect on the electronic structure and energy band can be obtained.

2. The method for calculating and predicting the diffusion behavior of oxide layer defects in ferritic and martensitic stainless steel according to claim 1, characterized in that: In step (1), the Fe3O4 and FeCr2O4 are selected to have a structural configuration of space group Fd-3m; The VESTA software imports a structure file as a .cif structure file and exports a structure file as a .vasp structure file.

3. The method for calculating and predicting the diffusion behavior of oxide layer defects in ferritic and martensitic stainless steel according to claim 1, characterized in that: The specific operation process of step (1) is as follows: (1.1) Obtain the lattice parameters, atomic coordinate positions, and bond lengths and angles of the initial structures of defect-free Fe3O4 and FeCr2O4 based on literature and databases; (1.2) Use VESTA software to preliminarily construct defect-free Fe3O4 and FeCr2O4, obtain the structure of defect-free Fe3O4 and FeCr2O4 and convert their structure files into .vasp file format.

4. The method for calculating and predicting the diffusion behavior of oxide layer defects in ferritic and martensitic stainless steel according to claim 1, characterized in that: In step (2), the specific settings of the calculation parameters include the wave function cutoff energy of 500eV and the convergence standard of the force The convergence criterion of energy is 10 -6 The structure optimization was carried out under the parameter of eV, the U value of Fe and Cr elements was selected in the range of 2-4eV, and the K point was sampled using the Γ-centered sampling method with a sampling density of 7×7×7.

5. The method for calculating and predicting the diffusion behavior of oxide layer defects in ferritic and martensitic stainless steel according to claim 1, characterized in that: The specific operation process of step (2) is as follows: Step (2.1): Use VASP software based on density functional theory to perform structural optimization relaxation of defect-free Fe3O4 and FeCr2O4; Step (2.2): Based on the optimized model calculated above, a series of Fe3O4 and FeCr2O4 models with a volume expansion ratio of 0.9-1.1 and a step size of 0.05 were constructed; Step (2.3): Based on a series of models of different volumes constructed in step (2.2), the structure is optimized to obtain the system energy, a volume-energy fitting curve is established according to the volume, and the bulk modulus is obtained according to the slope; Step (2.4): Compare the bulk modulus and structural parameters calculated in step (2.3) with the experimental values in the literature, select the group with the smallest error, and use this parameter as the standard for subsequent steps; Step (2.5): Change the U value of Fe and Cr elements within the range of 2-4 eV with a step size of 0.5 eV, and repeat the above steps until the group with the lowest error with the experimental results or literature values is selected, and record its parameters.

6. The method for calculating and predicting the diffusion behavior of oxide layer defects in ferritic and martensitic stainless steel according to claim 5, characterized in that: There are four defect sites in Fe3O4, among which the wyckoff positions of the two substitutional sites are 8a and 16d, and the Wyckoff positions of the two interstitial sites are 16c and 32e; there are two defect sites in FeCr2O4, whose wyckoff positions are 16c and 32e.

7. The method for calculating and predicting the diffusion behavior of oxide layer defects in ferritic and martensitic stainless steel according to claim 1, characterized in that: In step (3), the formula for calculating the defect system formation energy is as follows: Where, E Fe24O32 It represents the total energy of ideal Fe3O4; is the defect formation energy of the vacancy defect; is the defect formation energy of the interstitial defect; E M23O32 It represents the substitutional doping of Fe3O4 with dopant atoms M and the total energy; EM Fe24O32 It represents the total energy of interstitially doped Fe3O4 with dopant atoms M; μ Fe It represents the cohesive energy of body-centered cubic Fe; μ M It represents the average energy per atom of the dopant atoms.

8. The method for calculating and predicting the diffusion behavior of oxide layer defects in ferritic and martensitic stainless steel according to claim 1, characterized in that: In step (3), Fe and Cr are corrected using the DFT+U method during the calculation process, with Fe corrected using a U value of 3 eV and Cr corrected using a U value of 3.5 eV.

9. The method for calculating and predicting the diffusion behavior of oxide layer defects in ferritic and martensitic stainless steel according to claim 1, characterized in that: In step (5), the calculation formula of the diffusion coefficient in the calculation process is as follows: Where L represents the length of the diffusion path; c is a constant, c = 6 in a three-dimensional system; z is the coordination number; τ is the time interval between two migrations of the same atom in the same path; R0 is the trial frequency; E α is the reaction activation energy; m is the mass of the diffusing atom; k B is the Boltzmann constant; T is temperature.

10. The method for calculating and predicting the diffusion behavior of oxide layer defects in ferritic and martensitic stainless steel according to claim 9, characterized in that: In step (5), the lattice defect diffusion coefficient calculation is based on the VASP software package compiled with the transition state search tool plug-in VTST plug-in; In the calculation process, the plane wave cutoff energy is selected as 400eV, and the convergence standard of the force is The convergence criterion of energy is 10 -6 eV,U Fe =3eV, U Cr =3.5eV.

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