Anti-irradiation metal material nanocrystallization design method based on cellular model

Abstract

The invention relates to the technical field of nuclear materials, and discloses an anti-radiation metal material nanocrystallization design method based on a cellular model, and the method comprises the steps: building a defect reaction list and a rate coefficient, building a cluster dynamics model framework, determining model parameters, and carrying out simulation calculation. The dynamic influence of the grain boundary on defect evolution is comprehensively depicted by introducing the grain boundary type capture trap strength model considering the defect dynamic behavior, the limitation that an existing model is only based on the relation between simple absorption strength and grain size is solved, and the method is suitable for the unbalanced defect behavior in the long-time dynamic evolution process. And cross-scale defect behavior simulation is realized. Through the method, the influence of different grain sizes and grain boundary characteristics on the anti-radiation performance of the material can be deeply researched, an optimal design scheme is provided, the anti-radiation performance of the material is improved, the service life is prolonged, and powerful support is provided for the safety and economy of a nuclear reactor.

Description

Technical Field

[0001] The invention relates to the technical field of nuclear materials, and in particular to a method for designing nano-scale radiation-resistant metal materials based on a cellular model. Background Art

[0002] In the nuclear industry, the design of highly radiation-resistant materials for fission and fusion devices has always been a key bottleneck restricting the sustainable development of nuclear energy. Under the extreme environment of long-term, high-energy neutron irradiation in nuclear reactors, a series of complex physical changes will occur inside the nuclear materials. The interaction between neutrons and the atomic nuclei of the material will produce severe displacement damage and lead to the generation of a large number of transmutation elements. These changes trigger the aggregation of point defects (such as self-interstitial atoms and vacancies), which in turn form large dislocation loops and voids. The continued accumulation of these defects will significantly change the microstructure of the material, resulting in a series of adverse effects such as decreased mechanical properties, reduced thermal conductivity, and increased ductile-brittle transition temperature, ultimately greatly shortening the service life of the nuclear reactor and limiting its operational safety and stability.

[0003] Currently, in the practical application of nuclear devices, body-centered cubic (BCC) metals and their alloys have become the preferred materials for structures and plasma-facing components due to their excellent mechanical and thermal properties, as well as relatively high radiation / corrosion tolerance. Over the past few decades, researchers have conducted extensive and in-depth research on the response of BCC metals under neutron irradiation. However, with the continuous advancement of nuclear energy technology, the performance of pure BCC metals as nuclear materials has gradually approached their theoretical limits. In order to meet the more stringent design requirements of future fusion reactors, it is urgent to further improve the material performance, especially the radiation tolerance, especially in strong irradiation environments. Therefore, in-depth exploration of the radiation tolerance mechanism of BCC metals and accurate prediction of their long-term service performance in nuclear devices have become the core tasks in the current field of nuclear materials research.

[0004] In recent years, material nanocrystalization technology, as a potential effective approach, has been considered to significantly improve the comprehensive performance of materials under irradiation environments. Numerous experimental and theoretical studies have confirmed that reducing grain size can effectively reduce the number of defects in certain nanocrystalline (grain size less than 100 nanometers) face-centered cubic (FCC) metals such as gold, silver, and copper, as well as nanocrystalline FCC metals such as iron (Fe), molybdenum (Mo), and tungsten (W). This phenomenon is mainly attributed to the high density of grain boundaries, which can serve as effective sites for absorbing intrinsic defects and emitting interstitials to eliminate vacancies near grain boundaries. However, experimental studies have also revealed a paradoxical phenomenon: nanocrystals of some materials (such as zirconia, SiC, and W) do not show any advantages in radiation tolerance compared to coarse-grained (grain size greater than 10 microns) materials, and may even be relatively inferior. Although a large amount of experimental evidence has demonstrated the macroscopic characteristics of nanomaterials, the fundamental scientific question of how defect traps interact and effectively eliminate these defects still requires in-depth research and answers.

[0005] To fully and deeply understand the damage behavior of polycrystalline materials under irradiation, various computational and simulation tools play an indispensable role. These tools enable systematic investigation of the irradiation damage behavior of polycrystalline materials at time scales ranging from nanoseconds in the non-steady state to infinite in the steady state, and from nanometers to single crystals. For example, atomic-scale methods such as density functional theory, molecular statics, and molecular dynamics can simulate the dynamic mechanisms and interaction rules between small defects (typically fewer than a few dozen) and trapping traps such as grain boundaries in the non-steady state at time scales less than nanoseconds. Steady-state rate theory is employed to simulate the steady-state conditions of materials with varying grain sizes at infinite (sufficiently long) times. For complex processes between these two extremes, mesoscopic methods such as kinetic Monte Carlo and cluster dynamics (CD) are often used to simulate the evolution and accumulation of defects in irradiated BCC metals. However, because the irradiation damage process involves numerous complex factors, such as the intrinsic properties of the defects and the structural characteristics of the metal, suitable multiscale models are currently lacking to accurately simulate the irradiation tolerance of polycrystalline core-structured metals.

[0006] In terms of experimental research, due to the scarcity of fusion neutron sources, nuclear material reactor experiments generally use heavy ion / proton irradiation to simulate neutron irradiation. However, this simulation method has many difficulties. Experimental detection technology cannot accurately reveal the microscopic dynamic evolution mechanism of defects, nor can it accurately predict the performance changes of materials during long-term service. In this context, computational simulation, as an important supplement to experimental research, is of vital importance for a deep and systematic understanding of the basic laws of radiation damage effects. The radiation effect of materials is a complex dynamic process involving long time, multiple scales and multiple microscopic mechanism couplings, and a multi-scale simulation framework needs to be constructed to fully describe it. The key to multi-scale models is to achieve reasonable coupling between calculation methods at different scales. However, the field of neutron irradiation simulation of fusion reactor metal materials is currently in its infancy both at home and abroad, and related research still faces many challenges.

[0007] In the relevant technical field, several invention patents have been developed to simulate nuclear material radiation damage. For example, patent publication number CN112926205B, "Method and Model System for Simulating Irradiation Damage in Zirconium-Based Alloys Based on Cluster Dynamics," constructs a cluster dynamics model based on cluster dynamics, the physical mechanism of interactions between defects, and the problem of dislocation loop growth. By inputting material parameters, simulations and calculations are performed to obtain data on the dependence of the concentration of point defect clusters on irradiation dose. Further processing is performed to obtain the dose dependence of the defect cluster density, the distribution of the number of defects within a cluster, and the distribution of defect cluster sizes at a fixed dose. Patent publication number CN113076640A, "Software Simulation System and Method for Irradiation Damage in Zirconium-Based Alloys Based on Cluster Dynamics," integrates a cluster dynamics simulation module, a computational control module, and a GUI module. This system not only studies the process by which point defects generated by irradiation form point defect clusters, but also simulates the influence of defect capture traps on cluster growth dynamics. The cluster dynamics model is integrated into a dedicated platform, integrating model building with calculations, data storage, data processing, and results visualization. The invention patent, publication number CN112885414B, titled "System and Method for Irradiation Damage Simulation Based on Rate Theory and Cluster Dynamics," combines a cluster dynamics module with a rate theory module, respectively used to simulate the formation and growth stages of point defect clusters at low irradiation doses, and the growth stage of dislocation loops at high irradiation doses. By analyzing the correlation between defect cluster distribution and average cluster size and multiple factors, this system provides a more comprehensive perspective for irradiation damage research. The invention patent, publication number CN110459269B, titled "A Multiscale Coupling Simulation Method for Irradiation Damage of Nuclear Reactor Materials," organically combines molecular dynamics (MD), kinetic Monte Carlo (KMC), and cluster dynamics (CD). Through multiscale coupling simulation, this method achieves complete simulation from the atomic scale of defect generation to the large spatiotemporal scale of microstructural characterization, providing strong support for material property prediction. The invention patent with publication number CN111695245A, "A parallel simulation method for spatially resolved random cluster dynamics of material irradiation damage", is based on spatially resolved random cluster dynamics. It improves simulation efficiency through parallel computing and can more accurately describe the distribution and evolution of irradiation-induced defects in the material at different locations. It provides a powerful means for in-depth understanding of the material irradiation damage mechanism, predicting material performance changes, and optimizing material design.

[0008] However, during the research process, the aforementioned patents primarily focused on multi-scale simulations of the radiation damage behavior of intrinsic materials. They have not yet systematically considered the radiation resistance of polycrystalline materials with different grain sizes, nor have they proposed a grain size design solution for metal material systems under neutron irradiation. Therefore, key issues that need to be urgently addressed in the field of nuclear material radiation damage simulation include how to quantitatively simulate the long-term dynamic evolution of defects in metal materials with grain boundary characteristics under neutron irradiation, how to rationally introduce a grain boundary-type capture well strength model into the cluster dynamics model, and how to make material nanoscaling a practical design solution, thereby providing reliable advice for the selection of fusion reactor structural materials. Summary of the Invention

[0009] Existing multiscale models consider grain boundaries based on a simple relationship between absorption intensity and grain size. These models can only address the effect of grain size on defect behavior in equilibrium, but fail to consider the dynamic behavior of defects over long periods of time. The present invention addresses how to quantitatively simulate the dynamic evolution of defects in metals with varying grain sizes, how to rationally incorporate a grain boundary-type trap strength model that accounts for the dynamic behavior of defects into cluster dynamics models, and how to rationally describe the cross-temporal and spatial behavior of defects at spatial scales from nanometers to meters and time scales from femtoseconds to years. This approach provides a method for designing nanoscale radiation-resistant metal materials based on the cellular model.

[0010] This application proposes a rate model based on an improved grain boundary strength model based on diffusion theory; a rate equation for quantitatively simulating the long-term evolution of point defects and their clusters under electron irradiation; and a quantitative simulation of the multi-scale behavior of the long-term dynamic evolution of defects in polycrystalline core materials damaged by electron irradiation, and obtains the dynamic distribution of defects, providing theoretical guidance for the design of polycrystalline core materials. The above technical objectives of the present invention are achieved through the following technical solutions.

[0011] In a first aspect, the present invention provides a method for designing nanostructured radiation-resistant metal materials based on a cellular model, comprising the following steps:

[0012] S1. Construction of defect reaction kinetic parameters:

[0013] Based on the initial defect parameters, a list of defect reactions of polycrystalline metal materials under uniform electron irradiation is established, and the rate coefficient of each defect reaction is determined;

[0014] S2. Establishment of cluster dynamics framework for coupled cellular model:

[0015] Based on the defect reaction list, a cluster dynamics model is constructed to describe defect generation, diffusion, reaction and grain boundary absorption. The model characterizes the evolution of defect concentration with time and space through a set of partial differential equations; a cellular model of isolated spherical grains is introduced;

[0016] S3. Quantitative modeling of grain boundary absorption intensity:

[0017] Based on the continuity equation and spherical coordinate boundary conditions, the steady-state concentration distribution of point defects within the grain is solved. The expression for the capture well strength of the grain boundary for movable defects is derived by assuming an ideal capture well, and the polycrystalline solid is equivalent to a continuum with full absorption intensity.

[0018] S4. Dynamic simulation and nanoscale design of irradiation defects:

[0019] The grain boundary trap strength expression is introduced into the main equation of cluster dynamics to simulate the spatiotemporal evolution of defect concentration under different grain sizes; by analyzing the correlation between defect concentration distribution and grain size, the optimized grain size of radiation-resistant metal materials is determined.

[0020] Furthermore, in the method, the defect reaction list includes at least one of the following reaction events:

[0021] the creation, annihilation, and recombination of interstitial atoms and vacancies;

[0022] The formation and decomposition of self-interstitial atomic clusters or vacancy clusters and their reactions with point defects;

[0023] Migration, merging, and size evolution of defect clusters;

[0024] Absorption of self-interstitial atoms and vacancies by grain boundaries and dislocations.

[0025] Furthermore, in the method, the rate coefficient of the defect reaction is obtained by any of the following methods:

[0026] a) Calculate the defect migration energy barrier based on first principles;

[0027] b) Molecular dynamics simulation of defect interaction potential;

[0028] c) Experimental measurement of defect reaction cross sections under irradiation conditions;

[0029] d) Empirical formula fitting to known material data.

[0030] Furthermore, in the cellular model, the grains are isolated spheres with a radius R in the range of 1 nm to 10 μm; the grain boundaries are ideal trapping wells with negligible thickness, satisfying the fully absorbing boundary condition of c(r=R)=0, where c represents the point defect concentration in the dissipative continuum, r is the distance from the defect to the grain center, and R is the radius of the spherical grain.

[0031] Furthermore, in the method, the grain boundary type capture well strength expression is:

[0032]

[0033] Where θ is the defect, is the sum of the strengths of all traps in the “single crystal” microstructure within the grain, and R is the grain radius.

[0034] Furthermore, in the method, in step S4: the grain boundary type capture well strength expression is introduced into the cluster dynamics master equation, that is, it is described by introducing it into the intrinsic absorption term in the one-dimensional diffusion-reaction master equation.

[0035] Furthermore, by introducing the grain boundary trap strength expression into the intrinsic absorption term in the one-dimensional diffusion-reaction master equation, the specific expression is described as follows:

[0036]

[0037] Among them C θ is the concentration of defects θ under irradiation for a specific time t; G θ is the defect generation rate; ω(θ',θ) is the unit concentration rate coefficient of the transformation of θ'-type defects / clusters to θ-type; L θ is the absorption of the defect by the capture well, which is the absorption term in the equation, where and are the capture strengths of GB and DL type defect traps at grain boundaries, respectively; D θ is the diffusion rate of the defect.

[0038] Furthermore, in the method, the model can simultaneously characterize:

[0039] Spatial scale: from atomic-scale defects less than 1 nm to cross-scale behaviors of grains with a size of μm;

[0040] Time scale: a dynamic process from the instantaneous defect generation of femtoseconds (fs) during irradiation to the long-term evolution of years.

[0041] On the other hand, a radiation-resistant metal material designed and obtained by the method of the present invention is also provided.

[0042] Finally, the present invention also provides the application of the radiation-resistant metal material in a fusion reactor.

[0043] Compared to existing technologies, the proposed method for nano-designing radiation-resistant metal materials based on the cellular model addresses several key issues in existing models, enabling quantitative simulation of the dynamic behavior of defects in metals with different grain sizes. This provides strong theoretical and technical support for material design and performance optimization. Specific benefits are as follows:

[0044] (1) Comprehensive description of the dynamic influence of grain boundaries on defect behavior

[0045] Existing models rely solely on the relationship between absorption intensity and grain size, ignoring the complex mechanisms of grain boundaries and failing to fully describe their dynamic impact on defect behavior. This paper rationally incorporates a grain boundary strength model (cellular model) into the cluster dynamics model, taking into account the dynamic behavior of defects. This model comprehensively characterizes the dynamic influence of grain boundaries on defect evolution. This model more accurately describes the defect absorption and emission processes at grain boundaries, improving simulation accuracy and reliability.

[0046] (2) Applicable to non-equilibrium defect behavior during long-term dynamic evolution

[0047] Existing techniques primarily focus on studying the effect of equilibrium grain size on defect behavior, but are difficult to apply to non-equilibrium defect behavior during long-term dynamic evolution. This paper establishes a defect behavior description method applicable to long-term dynamic evolution processes, fully capturing the evolution of defects in non-equilibrium states. This method can simulate the dynamic evolution of defects under long-term irradiation and reveal the damage mechanisms of materials in irradiated environments.

[0048] (3) Realize cross-scale defect behavior simulation

[0049] Existing models are unable to effectively characterize the cross-scale defect evolution behavior from nanometers to meters and from femtoseconds to years. This invention achieves precise simulation of defect behavior at spatial scales from nanometers to meters and time scales from femtoseconds to years, breaking through the cross-scale limitations of existing models. Through a multiscale coupled simulation approach, combining molecular dynamics (MD), kinetic Monte Carlo (KMC), and cluster dynamics (CD), a complete simulation is achieved, from the atomic scale of defect generation to the large spatial and temporal scales of microstructural characterization.

[0050] (4) Improve the material's radiation resistance and extend its service life

[0051] The simulation method of this invention allows for in-depth research into the effects of varying grain sizes and grain boundary characteristics on a material's radiation resistance, enabling the development of design solutions to optimize this performance. By adjusting grain size, grain boundary characteristics, and alloy composition, the material's radiation resistance can be optimized, extending its service life in irradiated environments and improving the safety and economic efficiency of nuclear reactors. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 The flowchart of the quantitative simulation method of defect evolution of polycrystalline metal materials under uniform electron irradiation in the present invention is shown.

[0053] Figure 2 The framework diagram of the cluster dynamics model for implementing the long-term dynamic evolution of defects in this invention

[0054] Figure 3 The cellular model is an isolated grain with radius R. Inside the spherical grain, the defect concentration intensity is c. The boundary conditions on the grain boundary for the fractional defect concentration c are given. The only defect flux reaching the grain boundary originates from the interior of the spherical grain. DETAILED DESCRIPTION

[0055] The technical solutions of the present invention are described below with reference to the following embodiments; however, the present invention is not limited to the following embodiments.

[0056] In order to enable those skilled in the art to better understand and implement the technical solution of the present invention, the present invention is further described below with reference to specific embodiments and drawings, but the embodiments are not intended to limit the present invention.

[0057] The experimental methods and detection methods described in the following examples are conventional methods unless otherwise specified; the reagents and materials are commercially available unless otherwise specified.

[0058] The technical terms involved in this application are defined as follows:

[0059] Cellular model: A physical model that simplifies a polycrystalline material into a collection of isolated spherical grains, each separated by an idealized grain boundary. In this context, it specifically refers to a spherically symmetric model with the grain radius R as the characteristic dimension and the grain boundary as a fully absorbing boundary.

[0060] Absorption intensity (trapping strength): a physical quantity that characterizes the ability of grain boundaries to absorb defects, with the unit being m -2 .

[0061] dpa / s (atomic displacement damage / second): The unit of radiation damage rate, which represents the number of displacement collisions suffered by each atom per second, is used to quantify the defect generation rate K.

[0062] Full absorption boundary condition: a condition for specifying the function value on a boundary in a mathematical physics equation. In the present invention, the defect concentration c(R) at the grain boundary is set to 0, indicating that the grain boundary is a perfect defect capture well.

[0063] Frenkel pair: A defect pair consisting of a self-interstitial atom and its corresponding vacancy generated by irradiation, which is the most basic irradiation defect form in metal materials.

[0064] Cluster Dynamics: A simulation method that describes the size distribution of defect clusters by solving coupled rate equations. The governing equations include defect diffusion, reaction, absorption, and other processes.

[0065] Cross-scale simulation: refers to a computational method that simultaneously covers the spatial range from the atomic scale (defect core structure) to the mesoscopic scale (grain structure), as well as the temporal range from femtosecond defect generation to annual evolution.

[0066] Perfect Sink: This refers to a situation where a grain boundary has the perfect ability to absorb defects. This means that defects are immediately annihilated or captured upon reaching the grain boundary and do not return to the grain interior. This is mathematically represented by the boundary condition c(R) = 0.

[0067] Diffusion coefficient (D): Indicates the diffusion rate of defects. This parameter affects the efficiency of defect absorption by grain boundaries.

[0068] Example 1

[0069] The nanostructured design method of radiation-resistant metal materials based on the cellular model is shown in the flowchart. Figure 1 As shown, it is specifically implemented by the following steps.

[0070] S101. Construct defect reaction list and rate coefficient:

[0071] The initial defect reactions were summarized to construct a table of defect reaction events and corresponding rate coefficients in uniform electron-irradiated polycrystalline metal materials, as shown in Table 1. The reaction events in Table 1 cover the generation, annihilation, and recombination processes between self-interstitial atoms, vacancies, and their clusters. The rate coefficients were obtained through theoretical calculations.

[0072] Table 1 List of defect reactions in uniform electron irradiated polycrystalline metal materials

[0073]

[0074] S102, build the model:

[0075] Cluster dynamics model framework: Building Figure 2The cluster dynamics model framework diagram shown in the figure describes in detail the process of defect generation, diffusion, reaction, and absorption by grain boundaries. A series of partial differential equations are used to describe the changes in the concentration of different types of defects (self-interstitial atoms, vacancies, and their clusters) over time and space.

[0076] Cellular model: The cellular model with isolated grain radius R is as follows Figure 3 As shown, the sum of the various trapping strengths within the spherical grains is The boundary condition for the fractional defect concentration c at a grain boundary is that the only defect flux reaching the grain boundary originates from within the spherical grain. This model focuses on the contribution of the average density of GBs, which is characterized by grain size, and ignores the influence of microstructural details within the material. The model for a polycrystal considers a single isolated spherical grain with radius R, surrounded by no surrounding medium, and assumes similar conditions in all grains.

[0077] S103, determine model parameters:

[0078] To obtain the effective strength of grain boundaries using this model, we proceed as follows: The steady-state atomic concentration of point defects (either self-interstitial atoms or vacancies) within a grain, c = c(R), is given by the continuity equation,

[0079]

[0080] The spherical polar coordinate system with the center of the spherical grain as the origin is used here, where D represents the diffusion coefficient of the point defect, K is the generation rate of the point defect, in dpa / s. is the sum of the intensities of all traps within the “single crystal” microstructure within the grain. To simplify the derivation, thermal emission processes from point defects will not be explicitly included, but the appropriate form for the final vacancy emission rate will be directly given.

[0081] If the grain boundary is an ideal trap, then

[0082] c=0(r=R), (2)

[0083] Then, the concentration inside the grain is determined by the solution of equation (1), which must satisfy equation (2) and be bounded at distance r = 0, that is:

[0084]

[0085] The loss rate (per atom) of point defects within a grain to the grain boundary is:

[0086]

[0087] By replacing the polycrystalline solid with a complete lossy continuum of full absorption strength,

[0088]

[0089] in is the grain boundary trap strength. The continuity equation of the continuum is (ignoring thermal radiation and bulk recombination losses),

[0090] K-Dk 2 c ∞ =0, (6)

[0091] Where c represents the point defect concentration in the dissipative continuum, and the point defect loss rate equivalent to equation (4) in the continuum is:

[0092]

[0093] This follows from the continuity equation (6):

[0094]

[0095] Equating equations (4) and (8) yields the required expression for the grain boundary type trap strength (under the ideal trap assumption (2)),

[0096] It is used to express the absorption intensity of the grain boundary to the movable defect θ (self-interstitial atoms, vacancies), and its expression is,

[0097] The absorption strength of mobile defects by grain boundaries is determined by the number of trapping traps within the grains, including interstitial atoms, vacancies, dislocations, etc., in addition to GBs, as well as the grain size.

[0098] S104, simulation calculation:

[0099] The above model is used to simulate the cluster dynamics of irradiated defect evolution in polycrystalline materials. By considering that the grain boundary strength model is introduced into the evolution of different types of defect concentrations over time and space, it can be described by the intrinsic absorption terms in a set of one-dimensional diffusion-reaction master equations.

[0100]

[0101] Among them, C θ is the concentration of defects θ (interstitial atoms (I) and vacancies (V)) under irradiation for a specific time t; G θ is the defect generation rate; ω(θ',θ) is the unit concentration rate coefficient of the transformation of θ'-type defects / clusters to θ-type; L θ is the absorption of the defect by the capture well, which is the absorption term in the equation, where and are the capture strengths of grain boundary (GB) and dislocation (DL) type defect traps, respectively; D θ is the diffusion rate of the defect.

[0102] This allows us to understand the dynamic changes in the concentration of various defects over time, as well as the influence of factors such as defect generation, reaction, and absorption by traps such as grain boundaries. Ultimately, we can obtain the dynamic defect concentration distribution of materials with different grain sizes after uniform electron irradiation.

[0103] Example 2

[0104] This embodiment provides a radiation-resistant metal material designed and obtained using the method described in Example 1.

[0105] Example 3

[0106] This embodiment provides an application of the radiation-resistant metal material in Embodiment 2 in a fusion reactor.

[0107] Existing models are based solely on the simple relationship between absorption intensity and grain size, ignoring the complex mechanism of action of grain boundaries and failing to fully describe the dynamic effects of grain boundaries on defect behavior. Furthermore, existing technologies mostly focus on studying the effects of equilibrium grain size on defect behavior, making them difficult to apply to non-equilibrium defect behavior during long-term dynamic evolution. They are unable to effectively characterize cross-scale defect evolution behavior at spatial scales from nanometers to meters and time scales from femtoseconds to years. By addressing these issues, the present invention achieves quantitative simulation of defect dynamic behavior in metals with different grain sizes, providing strong theoretical and technical support for material design and performance optimization. In the cluster dynamics model, a grain boundary strength model (cellular model) that takes into account defect dynamic behavior is rationally introduced to comprehensively characterize the dynamic effects of grain boundaries on defect evolution. A defect behavior description method applicable to long-term dynamic evolution processes is established, which can fully capture the laws of defect evolution under non-equilibrium conditions. Accurate simulation of defect behavior at spatial scales from nanometers to meters and time scales from femtoseconds to years is achieved, breaking through the cross-scale limitations of existing models. By directly comparing the simulation results with the experimental data, the accuracy of the model is verified and the model parameters are further optimized to enable it to have the ability to predict the macroscopic properties and defect behavior of the material.

[0108] As described above, the basic principles, main features and advantages of the present invention are well described. The above embodiments and descriptions are merely descriptions of preferred embodiments of the present invention, and the present invention is not limited to the above embodiments. Various changes and improvements made to the technical solutions of the present invention by those skilled in the art without departing from the spirit and scope of the present invention should fall within the scope of protection determined by the present invention.

Claims

1. A method for designing nanostructured radiation-resistant metal materials based on a cellular model, characterized in that: The following steps are involved: S1. Construction of defect reaction kinetic parameters: Based on the initial defect parameters, a list of defect reactions of polycrystalline metal materials under uniform electron irradiation is established, and the rate coefficient of each defect reaction is determined; S2. Establishment of cluster dynamics framework for coupled cellular model: Based on the defect reaction list, a cluster dynamics model is constructed to describe defect generation, diffusion, reaction and grain boundary absorption, wherein the model characterizes the evolution of defect concentration over time and space through a set of partial differential equations; Then introduce the cellular model of isolated spherical grains; S3. Quantitative modeling of grain boundary absorption intensity: Based on the continuity equation and spherical coordinate boundary conditions, the steady-state concentration distribution of point defects within the grain is solved. The expression for the capture well strength of the grain boundary for movable defects is derived by assuming an ideal capture well, and the polycrystalline solid is equivalent to a continuum with full absorption intensity. S4. Dynamic simulation and nanoscale design of irradiation defects: The grain boundary trap strength expression is introduced into the main equation of cluster dynamics to simulate the spatiotemporal evolution of defect concentration under different grain sizes; by analyzing the correlation between defect concentration distribution and grain size, the optimized grain size of radiation-resistant metal materials is determined.

2. The method according to claim 1, characterized in that The defect response list includes at least one of the following response events: the creation, annihilation, and recombination of interstitial atoms and vacancies; The formation and decomposition of self-interstitial atomic clusters or vacancy clusters and their reactions with point defects; Migration, merging, and size evolution of defect clusters; Absorption of self-interstitial atoms and vacancies by grain boundaries and dislocations.

3. The method according to claim 1 or 2, characterized in that The rate coefficient of the defect reaction is obtained by any of the following methods: a) Calculate the defect migration energy barrier based on first principles; b) Molecular dynamics simulation of defect interaction potential; c) Experimental measurement of defect reaction cross sections under irradiation conditions; d) Empirical formula fitting to known material data.

4. The method according to claim 1, wherein In the cellular model, the grains are isolated spheres with a radius R in the range of 1 nm to 10 μm; the grain boundaries are ideal trapping wells with negligible thickness, satisfying the fully absorbing boundary condition of c(r=R)=0, where c represents the point defect concentration in the dissipative continuum, r is the distance from the defect to the grain center, and R is the radius of the spherical grain.

5. The method according to claim 1, wherein The grain boundary trap strength The expression is: Where θ is the defect, is the sum of the strengths of all traps in the "single crystal" microstructure within the grain, and R is the grain radius.

6. The method according to claim 1, characterized in that In the step S4, the grain boundary type trap strength expression is introduced into the cluster dynamics master equation by introducing it into the intrinsic absorption term in the one-dimensional diffusion-reaction master equation.

7. The method according to claim 6, characterized in that The specific expression is described by introducing the grain boundary trap strength expression into the intrinsic absorption term in the one-dimensional diffusion-reaction main equation: Among them, C θ is the concentration of defects θ under irradiation for a specific time t; G θ is the defect generation rate; ω(θ',θ) is the unit concentration rate coefficient of the transformation of θ'-type defects / clusters to θ-type; L θ is the absorption of the defect by the capture well, which is the absorption term in the equation, where and are the capture strengths of GB and DL type defect traps at grain boundaries, respectively; D θ is the diffusion rate of the defect.

8. The method according to claim 1, wherein The model is able to simultaneously characterize: Spatial scale: from atomic-scale defects less than 1 nm to cross-scale behaviors of grains with a size of μm; Time scale: A dynamic process from femtoseconds of transient defect generation during irradiation to years of long-term evolution.

9. The radiation-resistant metal material obtained by the method according to any one of claims 1 to 8.

10. Use of the radiation-resistant metal material according to claim 9 in a fusion reactor.

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