Method for analyzing micro-mechanism of corrosion of zirconium alloy in water environment based on ab initio molecular dynamics
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- XI AN JIAOTONG UNIV
- Filing Date
- 2025-05-09
- Publication Date
- 2026-06-26
AI Technical Summary
Existing technologies are insufficient to accurately capture the dynamic corrosion reaction mechanism of zirconium alloys in aqueous environments at the atomic scale, and traditional computational simulations cannot fully consider temperature and molecular ensemble effects, thus hindering in-depth exploration of the corrosion reaction mechanism.
A multiphase interface model was constructed using an ab initio molecular dynamics approach. Simulation parameters were set to optimize the geometry and perform molecular dynamics simulations. The corrosion elementary reaction pathways and interaction mechanisms were analyzed using the DFT method, and the simulation and data processing were performed using the CP2K software package.
Accurate dynamic simulation of the corrosion process of zirconium alloys under periodic boundary conditions was achieved, improving the calculation accuracy and enabling in-depth analysis of the effects of temperature, alloying elements and hydrochemical environment on corrosion behavior, providing a multi-scale elucidation of the corrosion mechanism of zirconium alloys.
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Abstract
Description
Technical Field
[0001] This invention belongs to the technical field of analyzing the microscopic corrosion process of zirconium alloys in aquatic environments, specifically involving a method for analyzing the microscopic mechanism of zirconium alloy corrosion in aquatic environments based on ab initio molecular dynamics. Background Technology
[0002] In nuclear power systems, the nuclear fuel cladding plays a crucial role as the first line of defense for reactor safety. It is responsible for containing the nuclear fuel pellets and ensuring their isolation from the external coolant under all circumstances, effectively preventing the release of radioactive fission products. Therefore, the integrity of the nuclear fuel cladding directly determines whether the reactor can operate safely and stably.
[0003] Zirconium alloys are widely used as fuel element cladding due to their low neutron absorption cross-section, excellent corrosion resistance, and mechanical properties. However, due to the unique operating environment, Zr alloy cladding is continuously exposed to the high-temperature main coolant during reactor operation, leading to complex chemical reactions on its surface. The formation of corrosion products on the cladding surface and the high hydrogen content within the Zr matrix become key factors limiting fuel lifespan. A thorough understanding of the kinetics of Zr alloy cladding corrosion and the influence of various practical factors is crucial not only for the safe operation of the reactor but also for meeting the economic requirements of higher burnup.
[0004] Currently, while experimental studies can provide macroscopic data, they struggle to capture dynamic reaction mechanisms at the atomic scale and are costly and time-consuming. Traditional computational simulations, such as density functional theory (DFT), cannot fully account for temperature and molecular ensemble effects, and the accuracy and portability limitations of classical molecular dynamics potential functions hinder in-depth exploration of complex corrosion reaction mechanisms. Therefore, a method is urgently needed to dynamically study the corrosion process of zirconium alloys at the atomic scale. Summary of the Invention
[0005] To address the problems existing in the prior art and the limitations of experimental methods and simulation studies, the present invention aims to provide a method for analyzing the microscopic mechanism of zirconium alloy corrosion in a water environment based on ab initio molecular dynamics. This method can accurately simulate the dynamic process of zirconium alloy corrosion under periodic boundary conditions, has higher computational accuracy, and provides a more reasonable description of interatomic forces in the system. It can also analyze the interaction mechanism between the alloy and the corrosive medium at the atomic and electronic scale. Furthermore, it can deeply analyze the influence of temperature, alloying elements, and the water chemical environment on the corrosion behavior of zirconium alloys. The method has a clear logic, simple steps, and is easy to operate.
[0006] To achieve the above objectives, the present invention adopts the following technical solution:
[0007] A method for analyzing the microscopic corrosion mechanism of zirconium alloys in aqueous environments based on ab initio molecular dynamics includes the following steps:
[0008] S1: Construct a multiphase interface model combining a metal substrate model and a corrosion medium layer model to obtain the size information of the simulation box; expand and cross-section the α-zirconium unit cell, and then construct a special quasi-random structure, replacing some zirconium atoms with alloy atoms to obtain a metal substrate model representing a zirconium alloy; the corrosion medium layer model contains water molecules filled in the simulation box, the cross-section of the simulation box is consistent with the cross-sectional size of the metal substrate model, and the number of water molecules is set according to the coolant mass density under normal operating conditions;
[0009] When considering the impact of water chemistry environment, some water molecules in the corrosion medium layer model are replaced with boric acid or lithium hydroxide molecules;
[0010] S2: Set simulation parameters for the multiphase interface model, including external potential parameters, geometric optimization parameters, and ab initio molecular dynamics parameters;
[0011] S3: Optimize the geometry of the multiphase interface model to eliminate local internal stress, and then perform ab initio molecular dynamics simulation to obtain atomic evolution trajectories and corrosion product structures.
[0012] S4: Perform data post-processing and statistical analysis on the ab initio molecular dynamics simulation results, including root mean square bias, radial distribution function, coordination number, atomic density distribution and chemical bond number analysis, obtain the corrosion elementary reaction pathway and calculate the reaction energy barrier, and analyze the interaction mechanism between corrosion groups and the surface using the DFT method; where DFT represents density functional theory.
[0013] Furthermore, the number of atomic layers in the metal substrate model described in step S1 is selected by considering the surface energy convergence of quantum size effects, and the surface energy calculation formula is as follows:
[0014]
[0015] Among them, E n ΔE(n) represents the total energy of the substrate model, n represents the number of atomic layers, and ΔE(n) represents the convergence value of the energy increment of the metal substrate model with adjacent layers.
[0016] Furthermore, in step S1, when considering the influence of the hydrochemical environment, the boric acid or lithium hydroxide molecules are first subjected to geometric structure optimization before replacement to obtain atomic spacing, bond angle and dihedral angle that conform to reality; after replacement, the corrosion medium layer model is subjected to ab initio molecular dynamics simulation to fully consider the solvation effect of boric acid and lithium hydroxide.
[0017] Furthermore, in step S1, the vertical distance between the metal substrate model and the corrosive medium layer model is [missing information]. A vacuum layer is placed above the corrosive medium layer model, which is used to gradually transition the electron density of the atoms near the boundary to zero.
[0018] Furthermore, the external potential field parameter U mentioned in step S2 EX Set it using the following formula:
[0019]
[0020] Where z is the vertical position of the atom in the simulated box, k controls the height of the potential field, n controls the slope of the potential field, z0 controls the center position of the potential field, and b controls the width of the potential field; the external potential field is used to restrict water molecules from crossing the upper boundary of the simulated box.
[0021] Furthermore, the geometric optimization parameters in step S2 include the exchange-correlation functional, dispersion correction, first Brillouin zone sampling grid, cutoff energy, electronic self-consistent iterative convergence threshold, and minimum atomic force.
[0022] Furthermore, the ab initio calculation of molecular dynamics parameters in step S2 includes the ensemble, heat bath, simulation time step, and total simulation duration.
[0023] Furthermore, the geometric optimization and ab initio molecular dynamics simulation described in step S3 are performed using the CP2K software package under the Linux operating system, and the atomic evolution trajectory is visualized using VMD software.
[0024] Furthermore, the data post-processing and statistical analysis of the ab initio molecular dynamics simulation results described in step S4 specifically includes:
[0025] The reaction equilibrium state is determined by the root mean square deviation and the change in total potential energy of the multiphase interface model, and the statistical range of the equilibrium phase is determined.
[0026] The spatial distribution of atoms is characterized by radial distribution function, coordination number, and atomic density distribution, thereby obtaining the bond length and interaction type of chemical bonds.
[0027] Analysis of the number of chemical bonds can further reveal the reaction rate of the corrosion process and the characteristics of the corrosion products.
[0028] The minimum energy path and reaction energy barrier for the dissociation of the corrosive medium and the formation of corrosion products were calculated using the transition state theory of corrosion elementary reactions.
[0029] The Mulliken charge, partial density of states, electronic localization function, and charge density difference were calculated using the DFT method to analyze charge transfer, orbital hybridization, and chemical bond type.
[0030] The advantages of this invention compared to existing technologies are as follows: The method of this invention can accurately simulate the dynamic process of zirconium alloy corrosion under periodic boundary conditions. Compared to molecular dynamics simulations using classical force fields, it has higher computational accuracy and a more reasonable description of interatomic forces in the system. It can also analyze the interaction mechanism between the alloy and the corrosive medium at the atomic and electronic scale. Furthermore, it can deeply analyze the influence of temperature, alloying elements, and the hydrochemical environment on the corrosion behavior of zirconium alloys. The method has a clear logic, simple steps, and is easy to operate. Specifically, this invention establishes a multiphase interface model of the zirconium alloy corrosion system; sets external potential field parameters, geometric optimization parameters, and ab initio molecular dynamics parameters; uses the CP2K software package for geometric optimization and ab initio molecular dynamics simulation; tracks the movement trajectory of molecules and atoms during corrosion dynamics simulation; considers the influence of factors such as temperature, alloying elements, and hydrochemistry on corrosion; combines root mean square deviation and radial distribution function statistical analysis to study the corrosion process and product structure; extracts key elementary reactions and corrosive groups; and combines transition state theory and DFT methods to analyze the minimum energy path of the reaction and interatomic interactions.
[0031] This invention solves the problem of accurately calculating the atomic-scale interaction between zirconium alloys and corrosive media and the dynamic evolution of corrosion reactions in the field of zirconium alloy corrosion. Based on ab initio molecular dynamics simulation, this invention obtains the kinetic properties of corrosion reactions and the electronic structure properties of the system, elucidates the corrosion mechanism from multiple scales, and provides theoretical support for the optimization of corrosion resistance of cladding materials in the future. Attached Figure Description
[0032] To make the objectives, calculation schemes, and advantages of the present invention more apparent, the present invention will now be described in detail with reference to the accompanying drawings, wherein:
[0033] Figure 1 The surface energy of metal substrate models with different zirconium atomic layers provided in the embodiments of the present invention.
[0034] Figure 2 Special quasi-random structure alloy models with different concentrations are provided for embodiments of the present invention: (a) is Zr-6.25% (Nb / Sn); (b) is Zr-12.5% (Nb / Sn); and (c) is Zr-25% (Nb / Sn).
[0035] Figure 3 This is a schematic diagram of a corrosion multiphase interface model provided in an embodiment of the present invention.
[0036] Figure 4 A snapshot of the corrosion of zirconium metal in pure H2O at 598K, provided as an embodiment of the present invention.
[0037] Figure 5In the figures (a) and (b), the root mean square deviation and total potential energy of pure zirconium metal corroded in 598K and H2O, respectively, are provided in the embodiments of the present invention.
[0038] Figure 6 The radial distribution function of zirconium metal in corrosion equilibrium in pure H2O at 598K is provided in the embodiments of the present invention.
[0039] Figure 7 The atomic density distribution of zirconium metal in pure H2O at 598K is provided for embodiments of the present invention.
[0040] Figure 8 The number of chemical bonds of zirconium metal in pure H2O at different temperatures provided in the embodiments of the present invention: where (a) is the number of zirconium oxygen bonds; and (b) is the number of zirconium hydrogen bonds.
[0041] Figure 9 The number of zirconium-oxygen bonds in zirconium-niobium alloys of different concentrations during corrosion in pure H2O at 598K is shown in the embodiments of the present invention.
[0042] Figure 10 The number of zirconium-oxygen bonds in the corrosion simulation of zirconium metal in boron-containing water and pure water at different temperatures provided in the embodiments of the present invention.
[0043] Figure 11 This provides the minimum energy path for the adsorption and dissociation of H2O on the zirconium surface in an embodiment of the present invention.
[0044] Figure 12 Partial density of states analysis of the stable adsorption configuration of H2O on the zirconium surface provided in the embodiments of the present invention. Detailed Implementation
[0045] The technical solutions of the present invention are illustrated below through specific embodiments. Those skilled in the art can clearly understand the technical advantages and practical application value of the present invention through the content disclosed in this specification. The embodiments of the present invention are not limited to the following examples; other different specific implementations can be derived based on the same inventive concept. Furthermore, the technical details recorded in the specification can be adaptively adjusted or modified according to different application scenarios without departing from the core idea of the present invention. It should be noted that the following embodiments are only illustrative of the basic principles of the present invention. Without constituting a technical conflict, the various embodiments and their technical features can be used in combination.
[0046] Please see Figures 1-12 This invention provides a method for analyzing the microscopic corrosion process of zirconium alloys in an aqueous environment based on ab initio molecular dynamics. The method specifically includes the following steps:
[0047] S1: Construct a multiphase interface model combining a metal substrate model and a corrosion medium layer model to obtain the size information of the simulation box; expand and cross-section the α-zirconium unit cell, and then construct a special quasi-random structure, replacing some zirconium atoms with alloy atoms to obtain a metal substrate model representing a zirconium alloy; the corrosion medium layer model contains water molecules filled in the simulation box, and the cross-section of the simulation box is consistent with the cross-sectional size of the metal substrate model. The number of water molecules is set according to the coolant mass density under normal operating conditions; when considering the influence of the water chemical environment, some water molecules in the corrosion medium layer model are replaced with boric acid or lithium hydroxide molecules.
[0048] Specifically, the establishment of the metal substrate model in step S1 includes the surface exposed in the corrosive medium, the selection of the number of substrate atomic layers, and the replacement of zirconium atoms.
[0049] The metal substrate model was orthogonalized, expanded, and sectioned using Materials Studio software from an α-zirconium unit cell. The α phase space group is P63 / mmc, and the lattice constant is [missing value]. α = β = 90°, γ = 120°. The unit cell lattice vector (a, b, c) is redefined as (a, a + 2b, c). The orthogonalized unit cell structure is expanded by 4 times in the a direction and 2 times in the b direction, meaning each layer contains 16 zirconium atoms. The exposed surface is selected as the (0001) plane, which is the closest-packed plane of the HCP lattice, has the most stable chemical properties, and is also the surface with the highest probability of exposure in the actual environment. The cut dimension is...
[0050] Furthermore, the number of atomic layers in the metal substrate model is selected based on the surface energy convergence of the metal substrate model considering quantum size effects, and the calculation formula is as follows:
[0051]
[0052] In the formula E n The total energy of the substrate model is represented by ΔE(n), where n represents the number of atomic layers, and ΔE(n) represents the convergence value of the energy increment of the substrate model for adjacent layers; the surface energy of the metal substrate model with different zirconium atomic layers is as follows: Figure 1 As shown, with 0.01 J / m 2 To meet the convergence limit, the surface energy difference between the five-layer atomic metal substrate model and the six-layer atomic metal substrate model is already below the convergence limit. Therefore, six layers are finally obtained as the atomic layer number of the metal substrate model, which consists of a 4×4×3 supercell with a total of 96 zirconium atoms. The bottom two atomic layers are fixed to simulate the bulk structure, while the remaining layers are allowed to relax.
[0053] Furthermore, the replacement of zirconium atoms was carried out using a special quasi-random structure constructed by the mcsqs program in the ATAT software package. By continuously adjusting the occupancy of different atoms in the model, the correlation function between atoms within the third alloy shell was made close to that of the real alloy. Metal substrate models of zirconium-niobium alloys and zirconium-tin alloys with atomic concentrations of 6.26%, 12.5%, and 25.0% were constructed, with 6, 12, and 24 zirconium atoms replaced, respectively. The metal substrate models of the alloys are shown below. Figure 2 As shown.
[0054] In step S1, the corrosive medium layer model was established by filling an empty box with corrosive medium molecules using Materials Studio software. The cross-sectional dimensions of the box were... The box height needs to ensure that the metal base model is not affected by mirror images under periodic boundary conditions, and should be set to... Filling the box with 50 water molecules corresponds to 0.65 g / cm³ under normal operating conditions. 3 Coolant density.
[0055] Furthermore, in step S1, when considering the influence of the water chemical environment, two water molecules in the corrosion medium layer model determined in step S1 are replaced with boric acid or lithium hydroxide molecules, while keeping the total number of molecules in the corrosion medium layer model consistent.
[0056] Furthermore, in step S1, when considering the influence of the hydrochemical environment, the boric acid or lithium hydroxide molecules are first subjected to geometric structure optimization before replacement to obtain atomic spacing, bond angle and dihedral angle that conform to reality; after replacement, the corrosion medium layer model is subjected to ab initio molecular dynamics simulation under the NVT ensemble to fully consider the solvation effect of boric acid and lithium hydroxide. The NVT ensemble is a canonical ensemble, which represents the conserved particle number, volume and temperature.
[0057] Furthermore, the metal substrate model and the corrosive medium layer model are combined, with the interval between them set to be [missing value]. Set above the corrosive medium layer model The vacuum layer allows the charge density of atoms near the boundary to gradually transition to zero in a vacuum. A schematic diagram of the constructed multiphase interface model is shown below. Figure 3 As shown.
[0058] S2: Set simulation parameters for the multiphase interface model. The simulation parameters include external potential parameters, geometric optimization parameters, and ab initio molecular dynamics parameters.
[0059] Specifically, the external potential parameter refers to the confinement potential applied to the water molecules. This is done to facilitate statistical analysis of the simulation results and to prevent water molecules from crossing the upper boundary of the simulation box and interacting with the lower surface of the metal substrate model. The confinement potential is activated only when molecules approach the potential field boundary, ensuring that no interference occurs under normal circumstances. The constructed external potential formula is:
[0060]
[0061] Where z is the vertical position of the atom in the simulated box. k controls the height of the potential field, n controls the slope of the potential field, z0 controls the center position of the potential field, and b controls the width of the potential field; the external potential field is used to restrict water molecules from crossing the upper boundary of the simulated box. In the example, k = 40, n = 200, z0 = 20, and b = 40.
[0062] Specifically, the geometric optimization parameters include the exchange-correlation functional, dispersion correction, first Brillouin zone sampling grid, cutoff energy, electronic self-consistent iterative convergence threshold, and minimum atomic force.
[0063] Specifically, the exchange-correlation functional is the PBE functional under the generalized gradient approximation, the dispersion correction is the Grimme D3(BJ) dispersion correction, the first Brillouin zone sampling grid is a (2×2×1)MK grid centered at the Γ point, the cutoff energy is set to 500eV, the electronic self-consistent iteration convergence threshold is 1×10-6eV, and the minimum atomic force is 4.5×10-4Hartree / Bohr.
[0064] Specifically, the molecular dynamics parameters calculated from scratch include the ensemble, the thermal bath, the simulation time step, and the total simulation duration.
[0065] Specifically, the ensemble is an NVT canonical ensemble, the heat bath is a CSVR velocity calibration heat bath with no pressure bath, the simulation time step is 0.5 fs, and the total simulation duration is 20 ps.
[0066] S3: Optimize the geometry of the multiphase interface model to eliminate local internal stress, and then perform ab initio molecular dynamics simulation to obtain atomic evolution trajectories and corrosion product structures.
[0067] Specifically, geometric optimization and ab initio molecular dynamics simulations were performed using the CP2K software package under the Linux operating system, with Quickstep as the electronic self-consistent iterative method and three-dimensional periodic boundary conditions. The resulting atomic evolution trajectories were visualized using VMD.
[0068] S4: Perform data post-processing and statistical analysis on the ab initio molecular dynamics simulation results, including root mean square bias, radial distribution function, coordination number, atomic density distribution and chemical bond number analysis, obtain the corrosion elementary reaction pathway and calculate the reaction energy barrier, and analyze the interaction mechanism between corrosion groups and the surface using the DFT method; where DFT represents density functional theory.
[0069] Specifically, the data post-processing and statistical analysis of the ab initio molecular dynamics simulation results include:
[0070] Through visualization analysis of atomic evolution trajectories, the multi-step dissociation reaction of water and the structure of zirconium oxide on the surface are analyzed during zirconium corrosion. A snapshot of zirconium metal corrosion in pure water is shown below. Figure 4 As shown in the figure, the different stages of the H2O molecule's reaction on the metal substrate model surface can be observed. Simultaneously, the corrosion process forms an oxide layer, effectively inhibiting the migration of oxygen and electrons across the oxide layer and slowing down the oxidation rate. The changes in root mean square deviation and total system potential energy (e.g., ...) are used to illustrate this. Figure 5 To determine whether the reaction is in equilibrium and to ascertain the statistical range of the equilibrium phase, the equilibrium time of zirconium metal in a pure water system at 598 K is approximately 10 ps. The spatial distribution of H and O atoms near zirconium atoms is characterized by radial distribution function and atomic density distribution to obtain information about chemical bond lengths, such as... Figure 6 , 7 As shown in the figure, the average bond lengths of Zr-O and Zr-H bonds are respectively... and And the hydrogen bonding interactions between corrosive media; by analyzing the changes in the number of Zr-O, Zr-H bonds with reaction time, the reaction rate and corrosion degree characteristics of the corrosion process are revealed, such as... Figure 8 As shown in the figure, during the corrosion process at 598 K, the number of Zr-O bonds and Zr-H bonds are almost equal, indicating that water molecules tend to undergo only primary dissociation. The number reaches its maximum at approximately 10 ps and then remains almost stable. This trend reflects the passivation properties of the corrosion products, effectively inhibiting further corrosion of deeper Zr atomic layers. However, at 1473 K, the number of Zr-H bonds is much higher than that of Zr-O bonds, indicating that water molecules tend to dissociate completely. At 1473 K, the corrosion reaction is more intense and persistent, and the initial corrosion products cannot form an effective passivation layer, failing to provide adequate protection for deeper Zr atomic layers.
[0071] Furthermore, the number of Zr-O bonds during the corrosion process of zirconium-niobium alloys with different concentrations is as follows: Figure 9As shown in the figure, increasing niobium concentration significantly affects the corrosion behavior of the alloys. The two alloys with higher niobium concentrations (12.5% and 25.0%) exhibited lower rates of Zr-O bond formation during corrosion, with the number of bonds reaching equilibrium at approximately 8 ps, indicating lower corrosion rates. In contrast, the pure zirconium and low-niobium-concentration alloys (6.25%) showed a much higher number of Zr-O bonds at equilibrium than the high-niobium-concentration alloys, despite reaching equilibrium at almost the same time, demonstrating higher corrosion rates.
[0072] Furthermore, when considering the influence of boric acid on the corrosion process in an aqueous chemical environment, the number of Zr-O bonds in corrosion simulations of boron-containing water and pure water at different temperatures is as follows: Figure 10 As shown in the figure, at 598K, the presence of boric acid results in a significantly fewer Zr-O bonds formed compared to the pure water condition when corrosion reaches equilibrium, and the corrosion process reaches equilibrium earlier. This indicates that boric acid molecules can effectively mitigate surface corrosion of the zirconium matrix while maintaining the passivation properties of the corrosion products. However, at a high temperature of 1473K, neither the zirconium corrosion products in the two aqueous chemical environments with or without boric acid molecules exhibited passivation properties; the surface functional groups were highly disordered, and the number of Zr-O bonds maintained a high growth rate throughout the simulation. Specifically, the addition of boric acid molecules resulted in a greater number of Zr-O bonds, indicating a higher degree of corrosion than under pure water conditions.
[0073] Furthermore, the minimum energy path and reaction energy barrier of the water molecule adsorption and dissociation process are calculated using the transition state theory of corrosion elementary reactions. The ease of adsorption and each stage of dissociation reaction is evaluated. The formula for calculating the reaction energy barrier is as follows:
[0074] E a =E TS -E IS
[0075] Among them, E a E represents the reaction energy barrier. TS E represents the transition state energy. IS This represents the initial energy of the reaction. For example... Figure 11 As shown, there is no barrier to the adsorption of water molecules, but there are barriers to both dissociation reactions. The energy barrier of the secondary dissociation is larger than that of the primary dissociation, indicating that the secondary dissociation is less likely to occur than the first two elementary reactions.
[0076] Furthermore, in step S4, the interaction between water molecules and the surface is calculated using the DFT method to obtain electronic structure property data. The partial density of states analysis of the stable adsorption configuration of H2O on the zirconium surface is as follows: Figure 12 As shown, the orbital hybridization phenomenon between different atoms and the changes in orbital energy levels before and after adsorption can be observed.
[0077] The aforementioned method for analyzing the microscopic corrosion process of zirconium alloys in aqueous environments based on ab initio molecular dynamics belongs to the technical field of analyzing the microscopic corrosion process of zirconium alloys in aqueous environments. It is used to study the dynamic corrosion process of zirconium alloys at the atomic scale. Simulation based on ab initio molecular dynamics obtains the kinetic properties of the corrosion reaction and the electronic structure properties of the system, elucidating the corrosion mechanism at multiple scales and providing theoretical support for the future optimization of corrosion resistance of cladding materials.
[0078] In summary, the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Even though the present invention has been described in detail based on the embodiments, those skilled in the art should understand that modifications, substitutions, and other operations can be made to the technical solutions of the present invention without departing from the core spirit and scope of protection of the present invention. Such equivalent changes and improvements made based on the present invention should all be included within the scope of protection defined by the claims of the present invention.
Claims
1. A method for analyzing the microscopic mechanism of corrosion of zirconium alloys in aqueous environments based on ab initio molecular dynamics, characterized in that, Includes the following steps: S1: Construct a multiphase interface model combining a metal substrate model and a corrosion medium layer model to obtain the size information of the simulation box; expand and cross-section the α-zirconium unit cell, and then construct a special quasi-random structure, replacing some zirconium atoms with alloy atoms to obtain a metal substrate model representing a zirconium alloy; the corrosion medium layer model contains water molecules filled in the simulation box, the cross-section of the simulation box is consistent with the cross-sectional size of the metal substrate model, and the number of water molecules is set according to the coolant mass density under normal operating conditions; When considering the impact of water chemistry environment, some water molecules in the corrosion medium layer model are replaced with boric acid or lithium hydroxide molecules; S2: Set simulation parameters for the multiphase interface model, including external potential parameters, geometric optimization parameters, and ab initio molecular dynamics parameters; S3: Optimize the geometry of the multiphase interface model to eliminate local internal stress, and then perform ab initio molecular dynamics simulation to obtain atomic evolution trajectories and corrosion product structures. S4: Perform data post-processing and statistical analysis on the ab initio molecular dynamics simulation results, including root mean square bias, radial distribution function, coordination number, atomic density distribution and chemical bond number analysis, obtain the corrosion elementary reaction pathway and calculate the reaction energy barrier, and analyze the interaction mechanism between corrosion groups and the surface using the DFT method; where DFT represents density functional theory.
2. The method for analyzing the microscopic mechanism of zirconium alloy corrosion in aqueous environments based on ab initio molecular dynamics according to claim 1, characterized in that, The number of atomic layers in the metal substrate model described in step S1 is selected by considering the surface energy convergence of quantum size effects. The surface energy calculation formula is as follows: Among them, E n ΔE(n) represents the total energy of the substrate model, n represents the number of atomic layers, and ΔE(n) represents the convergence value of the energy increment of the metal substrate model with adjacent layers.
3. The method for analyzing the microscopic mechanism of zirconium alloy corrosion in aqueous environments based on ab initio molecular dynamics according to claim 1, characterized in that, In step S1, when considering the influence of the hydrochemical environment, the boric acid or lithium hydroxide molecules are first subjected to geometric structure optimization before replacement to obtain atomic spacing, bond angle and dihedral angle that conform to reality; after replacement, the corrosion medium layer model is subjected to ab initio molecular dynamics simulation to fully consider the solvation effect of boric acid and lithium hydroxide.
4. The method for analyzing the microscopic mechanism of zirconium alloy corrosion in aqueous environments based on ab initio molecular dynamics according to claim 1, characterized in that, In step S1, the vertical distance between the metal substrate model and the corrosive medium layer model is [missing information]. A vacuum layer is disposed above the corrosive medium layer, which is used to gradually transition the electron density of the atoms near the boundary to zero.
5. The method for analyzing the microscopic mechanism of zirconium alloy corrosion in aqueous environments based on ab initio molecular dynamics according to claim 1, characterized in that, The external potential field parameter U mentioned in step S2 EX Set it using the following formula: Where z is the vertical position of the atom in the simulated box, k controls the height of the potential field, n controls the slope of the potential field, z0 controls the center position of the potential field, and b controls the width of the potential field; the external potential field is used to restrict water molecules from crossing the upper boundary of the simulated box.
6. The method for analyzing the microscopic mechanism of zirconium alloy corrosion in aqueous environments based on ab initio molecular dynamics according to claim 1, characterized in that, The geometric optimization parameters mentioned in step S2 include the exchange-correlation functional, dispersion correction, first Brillouin zone sampling grid, cutoff energy, electronic self-consistent iterative convergence threshold, and minimum atomic force.
7. The method for analyzing the microscopic mechanism of zirconium alloy corrosion in aqueous environments based on ab initio molecular dynamics according to claim 1, characterized in that, The ab initio calculation of molecular dynamics parameters in step S2 includes the ensemble, heat bath, simulation time step, and total simulation duration.
8. The method for analyzing the microscopic mechanism of zirconium alloy corrosion in aqueous environments based on ab initio molecular dynamics according to claim 1, characterized in that, The geometric optimization and ab initio molecular dynamics simulations described in step S3 were performed using the CP2K software package under the Linux operating system, and the atomic evolution trajectories were visualized using VMD software.
9. The method for analyzing the microscopic mechanism of zirconium alloy corrosion in aqueous environments based on ab initio molecular dynamics according to claim 1, characterized in that, Step S4, which involves post-processing and statistical analysis of the ab initio molecular dynamics simulation results, specifically includes: The reaction equilibrium state is determined by the root mean square deviation and the change in total potential energy of the multiphase interface model, and the statistical range of the equilibrium phase is determined. The spatial distribution of atoms is characterized by radial distribution function, coordination number, and atomic density distribution, thereby obtaining the bond length and interaction type of chemical bonds. Further analysis of the number of chemical bonds reveals the reaction rate of the corrosion process and the characteristics of the corrosion products. The minimum energy path and reaction energy barrier for the dissociation of the corrosive medium and the formation of corrosion products were calculated using the transition state theory of corrosion elementary reactions. The Mulliken charge, partial density of states, electronic localization function, and charge density difference were calculated using the DFT method to analyze charge transfer, orbital hybridization, and chemical bond type.