Method, apparatus and electronic device for determining plutonium alloy surface adsorption model

Abstract

The present invention provides a method, device and electronic device for determining a surface adsorption model of a plutonium alloy. The method constructs a crystal structure model of plutonium based on the theoretical value of the lattice constant, replaces the plutonium atoms in the crystal structure model with pre-acquired doped atoms to construct an initial plutonium alloy structure model; optimizes the structure of the initial plutonium alloy structure model to obtain a target plutonium alloy structure model in a stable state, and then places the pre-acquired adsorption molecules in the target plutonium alloy structure model in a stable state to construct an initial plutonium alloy surface adsorption model, and optimizes the structure of the initial plutonium alloy surface adsorption model to obtain a target plutonium alloy surface adsorption model that can stably adsorb, solving the technical problem in the prior art that a surface adsorption model cannot be constructed for plutonium alloy materials and meeting the application requirements for plutonium alloy materials in actual application scenarios.

Description

Technical Field

[0001] The present invention relates to the technical field of nuclear fission materials, and particularly to a method, a device and an electronic device for determining a surface adsorption model of a plutonium alloy. Background Art

[0002] Plutonium is a highly radioactive and extremely toxic fissile nuclear material. Due to the radioactivity and high toxicity of plutonium materials, technicians face many challenges in conducting experimental research on plutonium materials. Therefore, current research on plutonium materials mainly focuses on simulation research.

[0003] The melting point of plutonium is 913K. There are six stable phases within the range from absolute zero to the melting point. Among them, δ-plutonium has the best mechanical properties and machining properties, and thus has attracted much attention. The phase change of plutonium metal not only presents a complex relationship at different temperatures, but is also very sensitive to chemical doping and environmental pressure. The incorporation of elements such as gallium or aluminum can increase the temperature stability of plutonium, and at the same time significantly improve the flexibility and ductility of metallic plutonium, which plays a significant role in the processing, storage and application of plutonium materials. Therefore, in practical applications, alloy materials composed of plutonium and other metal or non-metal elements are mostly used.

[0004] Currently, the research on the surface properties and adsorption problems of plutonium mainly focuses on simulation research, and most of the constructed models are adsorption models of pure plutonium surfaces. However, in practical applications, alloy materials composed of plutonium and other metal or non-metal elements are mostly used. Therefore, the adsorption models of pure plutonium surfaces provided in the prior art cannot meet the application requirements for plutonium alloy materials in actual application scenarios. Therefore, how to construct a surface adsorption model for plutonium alloy materials is a technical problem that needs to be solved urgently by those skilled in the art. Summary of the Invention

[0005] The present invention provides a method, a device and an electronic device for determining a surface adsorption model of a plutonium alloy, so as to solve the defect in the prior art that a surface adsorption model cannot be constructed for plutonium alloy materials, and to meet the application requirements for plutonium alloy materials in actual application scenarios.

[0006] The present invention provides a method for determining a surface adsorption model of a plutonium alloy, including: obtaining a theoretical value of the lattice constant of plutonium, and constructing a crystal structure model of plutonium based on the theoretical value of the lattice constant; constructing an initial plutonium alloy structure model based on the pre-obtained doping atoms and the crystal structure model, and optimizing the structure of the initial plutonium alloy structure model based on a preset first model optimization strategy so that the surface of the initial plutonium alloy structure model is in a stable state to obtain a target plutonium alloy structure model; constructing an initial plutonium alloy surface adsorption model based on the pre-obtained adsorption molecules and the target plutonium alloy structure model, and optimizing the structure of the initial plutonium alloy surface adsorption model based on a preset second model optimization strategy so that the initial plutonium alloy surface adsorption model is in a stable adsorption state to obtain a target plutonium alloy surface adsorption model.

[0007] According to the method for determining a surface adsorption model of a plutonium alloy provided by the present invention, the obtaining of the theoretical value of the lattice constant of plutonium and constructing a crystal structure model of plutonium based on the theoretical value of the lattice constant includes: obtaining an experimental value of the lattice constant of plutonium; obtaining the theoretical value of the lattice constant of plutonium based on a preset structure optimization algorithm and a preset solid model state equation, where the preset structure optimization algorithm is used to optimize the structure parameters of the solid model so that the solid model is in a stable state; obtaining the current error value between the experimental value of the lattice constant and the theoretical value of the lattice constant, and determining whether the current error value is within a preset error range; and constructing a crystal structure model of plutonium based on the theoretical value of the lattice constant when the current error value is within the preset error range.

[0008] According to the method for determining a surface adsorption model of a plutonium alloy provided by the present invention, the obtaining of the theoretical value of the lattice constant of plutonium based on a preset structure optimization algorithm and a preset solid model state equation includes: obtaining a preset solid model state equation, where the preset solid model state equation represents the state equation between the volume of the solid model, the system energy corresponding to the volume, the lowest system energy, and the volume value corresponding to the lowest system energy; obtaining the volume empirical data of plutonium and the system energy empirical data corresponding to the volume empirical data; substituting the volume empirical data and the system energy empirical data into the preset solid model state equation, and calculating to obtain the volume value corresponding to the lowest system energy in the preset solid model state equation; and obtaining the theoretical value of the lattice constant of plutonium based on the volume value corresponding to the lowest system energy.

[0009] A method for determining a plutonium alloy surface adsorption model provided by the present invention. Based on the pre-obtained doping atoms and the crystal structure model, an initial plutonium alloy structure model is constructed, and the structure of the initial plutonium alloy structure model is optimized based on a preset first model optimization strategy to make the surface of the initial plutonium alloy structure model in a stable state, obtaining a target plutonium alloy structure model, including: selecting multiple groups of doping positions in the crystal structure model, and replacing the plutonium atoms at each group of the doping positions with the doping atoms to generate multiple initial plutonium alloy structure models; obtaining the surface energy data of each initial plutonium alloy structure model to obtain multiple groups of surface energy data; screening out the initial plutonium alloy structure model with the minimum surface energy from the multiple initial plutonium alloy structure models based on the multiple groups of surface energy data; and taking the initial plutonium alloy structure model with the minimum surface energy as the target plutonium alloy structure model.

[0010] A method for determining a plutonium alloy surface adsorption model provided by the present invention. Based on the pre-obtained adsorption molecules and the target plutonium alloy structure model, an initial plutonium alloy surface adsorption model is constructed, and the structure of the initial plutonium alloy surface adsorption model is optimized based on a preset second model optimization strategy to make the initial plutonium alloy surface adsorption model in a stable adsorption state, obtaining a target plutonium alloy surface adsorption model, including: placing the adsorption molecules on the surface of the target plutonium alloy structure model to obtain an initial plutonium alloy surface adsorption model; adjusting the placement positions of the adsorption molecules in the initial plutonium alloy surface adsorption model based on the preset second model optimization strategy to make the adsorption molecules stably adsorbed on the plutonium alloy surface, obtaining an optimized plutonium alloy surface adsorption model; obtaining the adsorption energy of the adsorption molecules on the plutonium alloy surface in the optimized plutonium alloy surface adsorption model, and judging whether the optimized plutonium alloy surface adsorption model is in a stable adsorption state based on the adsorption energy; and in the case where the optimized plutonium alloy surface adsorption model is in a stable adsorption state, determining the optimized plutonium alloy surface adsorption model as the target plutonium alloy surface adsorption model.

[0011] A method for determining a plutonium alloy surface adsorption model provided by the present invention. After optimizing the structure of the initial plutonium alloy surface adsorption model based on a preset second model optimization strategy to make the initial plutonium alloy surface adsorption model in a stable adsorption state and obtaining the target plutonium alloy surface adsorption model, the method further includes: obtaining adsorption capacity test data of the target plutonium alloy surface adsorption model, and obtaining an adsorption capacity analysis result of the target plutonium alloy surface adsorption model based on the adsorption capacity test data; obtaining net charge distribution data of the target plutonium alloy surface adsorption model, and obtaining a charge transfer analysis result of the target plutonium alloy surface adsorption model based on the net charge distribution data; obtaining differential charge density data of the target plutonium alloy surface adsorption model, and obtaining a charge density change analysis result of the target plutonium alloy surface adsorption model based on the differential charge density data; obtaining partial wave state density data of adsorbed molecules on the plutonium alloy surface after adsorption in the target plutonium alloy surface adsorption model, and obtaining an electronic structure change analysis result of the target plutonium alloy surface adsorption model based on the partial wave state density data; obtaining surface work function change data of the target plutonium alloy surface adsorption model, and obtaining a surface work function analysis result of the target plutonium alloy surface adsorption model based on the surface work function change data.

[0012] The present invention also provides a device for determining a plutonium alloy surface adsorption model, including: a crystal structure construction module, configured to obtain a theoretical value of the lattice constant of plutonium and construct a crystal structure model of plutonium based on the theoretical value of the lattice constant; a doping model construction module, configured to construct an initial plutonium alloy structure model based on a pre-obtained doping atom and the crystal structure model, and optimize the structure of the initial plutonium alloy structure model based on a preset first model optimization strategy to make the surface of the initial plutonium alloy structure model in a stable state and obtain a target plutonium alloy structure model; an adsorption model construction module, configured to construct an initial plutonium alloy surface adsorption model based on a pre-obtained adsorbed molecule and the target plutonium alloy structure model, and optimize the structure of the initial plutonium alloy surface adsorption model based on a preset second model optimization strategy to make the initial plutonium alloy surface adsorption model in a stable adsorption state and obtain a target plutonium alloy surface adsorption model.

[0013] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, it implements the method for determining a plutonium alloy surface adsorption model as described in any one of the above.

[0014] The present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the method for determining a plutonium alloy surface adsorption model as described in any one of the above.

[0015] The present invention also provides a computer program product, including a computer program which, when executed by a processor, implements the method for determining the plutonium alloy surface adsorption model as described in any one of the above.

[0016] The method, device and electronic device for determining the plutonium alloy surface adsorption model provided by the present invention construct a crystal structure model of plutonium based on the theoretical value of the lattice constant, replace the plutonium atoms in the crystal structure model with pre-acquired doping atoms to construct an initial plutonium alloy structure model; optimize the structure of the initial plutonium alloy structure model to obtain a target plutonium alloy structure model in a stable state, and then place the pre-acquired adsorption molecules in the target plutonium alloy structure model in a stable state to construct an initial plutonium alloy surface adsorption model, and optimize the structure of the initial plutonium alloy surface adsorption model to obtain a target plutonium alloy surface adsorption model that can stably adsorb, solving the technical problem in the prior art that a surface adsorption model cannot be constructed for plutonium alloy materials and meeting the application requirements for plutonium alloy materials in actual application scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0018] Figure 1 is one of the flow diagrams of the method for determining the plutonium alloy surface adsorption model provided by the present invention;

[0019] Figure 2 is another flow diagram of the method for determining the plutonium alloy surface adsorption model provided by the present invention;

[0020] Figure 3 is yet another flow diagram of the method for determining the plutonium alloy surface adsorption model provided by the present invention;

[0021] Figure 4 is still another flow diagram of the method for determining the plutonium alloy surface adsorption model provided by the present invention;

[0022] Figure 5 is another flow diagram of the method for determining the plutonium alloy surface adsorption model provided by the present invention;

[0023] Figure 6 is yet another flow diagram of the method for determining the plutonium alloy surface adsorption model provided by the present invention;

[0024] Figure 7aIt is a schematic diagram of the relationship curve between the system energy and the volume change in the second specific embodiment provided by the present invention;

[0025] Figure 7b It is a schematic structural diagram of the crystal structure model of plutonium in the second specific embodiment provided by the present invention;

[0026] Figure 8 It is a schematic structural diagram of the crystal orientation plane structure model in the second specific embodiment provided by the present invention;

[0027] Figures 9a to 9d It is a schematic structural diagram of the initial plutonium-gallium alloy structure model in the second specific embodiment provided by the present invention;

[0028] Figure 10 It is a schematic diagram of the relationship between the surface energy and the number of doped atoms in the second specific embodiment provided by the present invention;

[0029] Figures 11a to 11f It is a schematic structural diagram of the surface adsorption model of the initial plutonium-gallium alloy corresponding to hydrogen molecules in the second specific embodiment provided by the present invention;

[0030] Figures 12a to 12f It is a schematic structural diagram of the surface adsorption model of the initial plutonium-gallium alloy corresponding to oxygen molecules in the second specific embodiment provided by the present invention;

[0031] Figures 13a to 13j It is a schematic structural diagram of the surface adsorption model of the target plutonium-gallium alloy in the second specific embodiment provided by the present invention;

[0032] Figures 14a to 14b It is a schematic diagram of the differential charge density data in the second specific embodiment provided by the present invention;

[0033] Figures 15a to 15d It is a schematic diagram of the partial wave state density data in the second specific embodiment provided by the present invention;

[0034] Figure 16 It is a schematic structural diagram of the device for determining the surface adsorption model of the plutonium alloy provided by the present invention;

[0035] Figure 17 It is a schematic structural diagram of the electronic device provided by the present invention.

[0036] Reference numerals:

[0037] 100: Device for determining the surface adsorption model of the plutonium alloy; 10: Crystal structure construction module; 20: Doping model construction module; 30: Adsorption model construction module; 40: Adsorption model analysis module; 710: Processor; 720: Communication interface; 730: Memory; 740: Communication bus. Detailed implementation manners

[0038] To make the objectives, technical solutions, and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the present invention. Apparently, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present invention without creative efforts shall fall within the protection scope of the present invention.

[0039] The following will describe Figures 1 - 8 a method for determining the surface adsorption model of a plutonium alloy of the present invention. As Figure 1 shown, the present invention provides a method for determining the surface adsorption model of a plutonium alloy, including:

[0040] Step S1: Obtain the theoretical value of the lattice constant of plutonium, and construct a crystal structure model of plutonium based on the theoretical value of the lattice constant.

[0041] Plutonium is a radioactive metal element in the actinide series, with the element symbol Pu and the English name Plutonium. The lattice constant refers to the side length of the unit cell, that is, the side length of each parallelepiped unit.

[0042] Step S2: Construct an initial plutonium alloy structure model based on the pre-obtained doping atoms and the crystal structure model, and optimize the structure of the initial plutonium alloy structure model based on a preset first model optimization strategy to make the surface of the initial plutonium alloy structure model in a stable state, obtaining a target plutonium alloy structure model.

[0043] It should be noted that the doping atoms are used to be incorporated into the crystal structure model of plutonium to form a plutonium alloy material, which can change the temperature performance and metal performance of plutonium to meet the application requirements of plutonium alloy materials with different performances in actual application scenarios. The doping atoms can be metal atoms or non-metal atoms, and the present invention does not make specific limitations.

[0044] The preset first model optimization strategy is used to optimize the structure of the initial plutonium alloy structure model to make the surface of the initial plutonium alloy structure model in a stable state. The present invention does not make specific limitations on the preset first model optimization strategy, as long as it can achieve the function of optimizing the model structure to make the surface of the initial plutonium alloy structure model in a stable state.

[0045] Step S3: Construct an initial plutonium alloy surface adsorption model based on the pre-obtained adsorption molecules and the target plutonium alloy structure model, and optimize the structure of the initial plutonium alloy surface adsorption model based on a preset second model optimization strategy to make the initial plutonium alloy surface adsorption model in a stable adsorption state, obtaining a target plutonium alloy surface adsorption model.

[0046] The adsorbed molecules represent the molecular structure adsorbed on the surface of the plutonium alloy. The adsorbed molecules can be gas molecules or non-gas molecules, and the present invention does not make specific limitations. For example, in the research scenario of simulating the surface corrosion of plutonium alloy materials, oxygen molecules (O 2 ) or water molecules (H 2 O) can be set as the adsorbed molecules to construct the target plutonium alloy surface adsorption model, and the corrosion process on the surface of the target plutonium alloy surface adsorption model is studied. A preset second model optimization strategy is used to optimize the structure of the initial plutonium alloy surface adsorption model so that the initial plutonium alloy surface adsorption model is in a stable adsorption state. The present invention does not make specific limitations on the preset second model optimization strategy, as long as it can achieve the model structure optimization function so that the initial plutonium alloy surface adsorption model is in a stable adsorption state.

[0047] In the above steps S1 to S3, a crystal structure model of plutonium is constructed based on the theoretical value of the lattice constant, and the plutonium atoms in the crystal structure model are replaced with pre-obtained doped atoms to construct an initial plutonium alloy structure model; by optimizing the structure of the initial plutonium alloy structure model, a target plutonium alloy structure model in a stable state is obtained, and then the pre-obtained adsorbed molecules are placed in the target plutonium alloy structure model in a stable state to construct an initial plutonium alloy surface adsorption model, and the structure of the initial plutonium alloy surface adsorption model is optimized to obtain a target plutonium alloy surface adsorption model that can stably adsorb, solving the technical problem of how to construct a surface adsorption model for plutonium alloy materials in the prior art and meeting the application requirements of plutonium alloy materials in actual application scenarios.

[0048] In one embodiment, as Figure 2 shown, the above step S1 specifically includes steps S11 to S14, where: Step S11: Obtain the experimental value of the lattice constant of plutonium.

[0049] Step S12: Based on a preset structure optimization algorithm and a preset solid model state equation, obtain the theoretical value of the lattice constant of plutonium. The preset structure optimization algorithm is used to optimize the structural parameters of the solid model so that the solid model is in a stable state.

[0050] Further, the preset solid model equation of state represents the equation of state between the structural parameters of the solid model and the model stability parameters corresponding to the structural parameters. Based on the preset structure optimization algorithm, the structural parameters of the input solid model and the model stability parameters corresponding to the structural parameters are obtained, and the structural parameters and their corresponding model stability parameters are input into the preset solid model equation of state to optimize the structural parameters of the input solid model and obtain the target structural parameters that make the solid model in a stable state, so as to construct a target solid model according to the target structural parameters. Among them, the input solid model represents the solid model to be optimized input into the preset structure optimization algorithm. In the present invention, the input solid model is the crystal structure model of plutonium to be optimized.

[0051] It should be noted that in the present invention, the lattice constant is also a kind of structural parameter of the crystal structure model of plutonium, but it is not limited that the structural parameters mentioned in the preset structure optimization algorithm must be lattice constants. Other structural parameters can be used for model structure optimization processing, and the theoretical value of the lattice constant of plutonium can be obtained according to the target structural parameters. The present invention does not specifically limit the structural parameters and model stability parameters of the input solid model, as long as the model structure optimization function can be realized to make the input solid model in a stable state.

[0052] Step S13: Obtain the current error value between the experimental value of the lattice constant and the theoretical value of the lattice constant, and judge whether the current error value is within the preset error range.

[0053] Step S14: When the current error value is within the preset error range, construct a crystal structure model of plutonium based on the theoretical value of the lattice constant.

[0054] The above steps S11 to S14 obtain the theoretical value of the lattice constant of plutonium based on the preset structure optimization algorithm and the preset solid model equation of state to optimize the structural parameters of the crystal structure model of plutonium, so as to obtain a crystal structure model of plutonium in a stable state, ensuring the quality of the crystal structure model of plutonium and providing a good foundation for the subsequent construction of the plutonium alloy model and the surface adsorption model. In addition, by judging whether the current error value between the experimental value of the lattice constant and the theoretical value of the lattice constant is within the preset error range, the structural performance of the crystal structure model of plutonium is tested to ensure the quality of the crystal structure model of plutonium and improve the reliability of the target plutonium alloy surface adsorption model.

[0055] In one embodiment, as Figure 3 shown, the above step S12 specifically includes steps S121 to S124, where:

[0056] Step S121: Obtain a preset solid model equation of state, which represents the equation of state between the volume of the solid model, the system energy corresponding to the volume, the lowest system energy, and the volume value corresponding to the lowest system energy.

[0057] Among them, the system energy (or called the bulk phase energy) represents the total energy of the model system of the solid model. Similarly, the lowest system energy represents the lowest total energy of the model system of the solid model. In this embodiment, the input model is the crystal structure model of plutonium to be optimized, the structural parameter of the input model is the volume, and the model stability parameter of the input model is the system energy.

[0058] Step S122: Obtain the volume empirical data of plutonium and the system energy empirical data corresponding to the volume empirical data.

[0059] The volume empirical data represents the volume data of the crystal model structure of plutonium obtained according to historical experimental data. The volume empirical data includes the volumes of multiple crystal model structures of plutonium. The system energy empirical data includes the system energies corresponding to the volumes of multiple crystal model structures of plutonium.

[0060] Step S123: Substitute the volume empirical data and the system energy empirical data into the preset solid model equation of state, and calculate the volume value corresponding to the lowest system energy in the preset solid model equation of state.

[0061] It should be noted that there is a corresponding relationship between the volume of the solid model and its system energy. According to the principle of minimum energy, when the system energy of the solid model is the lowest system energy, the solid model is in the most stable state.

[0062] Step S124: Obtain the theoretical value of the lattice constant of plutonium based on the volume value corresponding to the lowest system energy.

[0063] Specifically, based on a preset structure optimization algorithm, obtain the volume empirical data and the system energy empirical data corresponding to the volume empirical data, input the volume empirical data and its corresponding system energy empirical data into the preset solid model equation of state to optimize the crystal structure model to be optimized, and obtain the target volume value that makes the crystal structure model to be optimized in a stable state. Then, obtain the theoretical value of the lattice constant of plutonium according to the target volume value, and construct the crystal structure model of plutonium according to the theoretical value of the lattice constant. Among them, the target volume value is the volume value corresponding to the lowest system energy, and the crystal structure model corresponding to the lowest system energy is in a stable state.

[0064] In the above steps S121 to S124, the volume value corresponding to the minimum system energy in the preset solid model state equation is obtained by calculation to obtain the crystal structure model of plutonium in a stable state. Moreover, the crystal structure model of plutonium obtained by this method conforms to the model in a stable state defined by the minimum energy principle, which ensures the reliability of the crystal structure model of plutonium, provides a good foundation for the subsequent construction of the plutonium alloy model and the surface adsorption model, and further improves the quality and reliability of the target plutonium alloy surface adsorption model.

[0065] Furthermore, the preset structure optimization algorithm can be the VASP built-in optimization algorithm or other structure optimization algorithms, as long as it can optimize the structural parameters of the model to make the model in a stable state, the present invention does not make any specific restrictions. The preset solid model state equation can be the Birch-Mumaghan state equation (English name: The Birch-Murnaghan equation of state) or other solid model state equations, the present invention does not make any specific restrictions. The following formula is the Birch-Murnaghan state equation:

[0066]

[0067] Where V represents the volume of the solid model, E(V) represents the system energy corresponding to the volume, and E 0 represents the minimum system energy, V 0 Indicates the volume value corresponding to the lowest system energy, B 0 represents the elastic modulus of the material constituting the solid model, B' 0 It is the first-order derivative of the elastic modulus with respect to the pressure change. It should be noted that by inputting the volume empirical data and its corresponding system energy empirical data into the Birch-Murnaghan state equation, the constant term E in the Birch-Murnaghan state equation can be fitted. 0 、V 0 , B 0 and B' 0 .

[0068] In one embodiment, the number of initial plutonium alloy structure models is multiple, such as Figure 4 As shown, the above step S2 includes steps S21 to S24, wherein:

[0069] Step S21: selecting a plurality of groups of doping positions in the crystal structure model, and replacing the plutonium atoms in each group of doping positions with doping atoms, to generate a plurality of initial plutonium alloy structure models.

[0070] Step S22: Obtain the surface energy data of each initial plutonium alloy structure model to obtain multiple sets of surface energy data.

[0071] In this embodiment, doping positions are selected at arbitrary positions on the surface of the initial plutonium alloy structure model to study the changes in the surface properties of the plutonium alloy structure model after doping atoms are incorporated. Surface energy is a measure of the disruption of intermolecular chemical bonds when creating the surface of a substance, and the magnitude of the surface energy can reflect the stability of the substance surface. In solid-state physics theory, surface atoms have more energy than atoms inside the substance. Therefore, according to the principle of minimum energy, atoms will spontaneously tend to the interior of the substance rather than the surface. The smaller the surface energy, the higher the stability of the substance surface.

[0072] Step S23: Based on multiple sets of surface energy data, screen out the initial plutonium alloy structure model with the minimum surface energy from multiple initial plutonium alloy structure models.

[0073] Step S24: Use the initial plutonium alloy structure model with the minimum surface energy as the target plutonium alloy structure model.

[0074] According to the principle of minimum energy and solid-state physics theory, the initial plutonium alloy structure model with the minimum surface energy is the most stable plutonium alloy structure model. Therefore, the initial plutonium alloy structure model with the minimum surface energy is selected as the target plutonium alloy structure model.

[0075] In the above steps S21 to S24, by screening out the initial plutonium alloy structure model with the minimum surface energy from multiple initial plutonium alloy structure models, a target plutonium alloy structure model in a stable state is obtained. Moreover, the target plutonium alloy structure model of plutonium obtained by this method conforms to the model in a stable state defined by the principle of minimum energy and solid-state physics theory, ensuring the reliability of the target plutonium alloy structure model, providing a good foundation for constructing the surface adsorption model subsequently, and further improving the quality and reliability of the target plutonium alloy surface adsorption model.

[0076] In one embodiment, step S21 further includes: the doping positions corresponding to each group and the number of doping positions are different. Doping positions can be selected at arbitrary positions on the surface of the initial plutonium alloy structure model, or at arbitrary positions inside the initial plutonium alloy structure model. This embodiment does not make specific limitations.

[0077] In this embodiment, by selecting multiple groups of doping positions and setting different corresponding doping positions and the number of doping positions for each group, multiple initial plutonium alloy structure models with different doping structures are generated to form a control group, which facilitates subsequent research on the law between the doping structure and the surface energy size based on the multiple initial plutonium alloy structure models with different doping structures, so that the target plutonium alloy structure model with the minimum surface energy can be quickly and accurately found, thereby improving the data processing efficiency and data processing effect.

[0078] In one embodiment, as Figure 5 shown, the above step S3 specifically includes steps S31 to S34, where:

[0079] Step S31: Place the adsorbed molecule on the surface of the target plutonium alloy structure model to obtain an initial plutonium alloy surface adsorption model.

[0080] Step S32: Adjust the placement position of the adsorbed molecule in the initial plutonium alloy surface adsorption model based on a preset second model optimization strategy to enable the adsorbed molecule to be stably adsorbed on the plutonium alloy surface, and obtain an optimized plutonium alloy surface adsorption model.

[0081] Furthermore, the preset second model optimization strategy can be the conjugate gradient method, or the quasi-Newton method, or other model optimization methods, which are not limited in this embodiment. Among them, the quasi-Newton method (IBRION = 1) has a relatively fast calculation speed and is suitable for the case where the structure of the initial model is relatively close to the stable model (the global minimum on the potential energy surface). The conjugate gradient method (IBRION = 20) is slower, but the possibility of finding the global minimum is also greater. Those skilled in the art can independently select the specific preset second model optimization strategy according to actual application requirements.

[0082] Step S33: Obtain the adsorption energy of the adsorbed molecule on the plutonium alloy surface in the optimized plutonium alloy surface adsorption model, and judge whether the optimized plutonium alloy surface adsorption model is in a stable adsorption state based on the adsorption energy.

[0083] Step S34: When the optimized plutonium alloy surface adsorption model is in a stable adsorption state, determine the optimized plutonium alloy surface adsorption model as the target plutonium alloy surface adsorption model.

[0084] The above steps S31 to S34 adjust the placement position of the adsorbed molecule in the initial plutonium alloy surface adsorption model to enable the adsorbed molecule to be stably adsorbed on the plutonium alloy surface, so as to obtain the target plutonium alloy surface adsorption model in a stable adsorption state, improving the quality of the target plutonium alloy surface adsorption model. In addition, by judging whether the optimized plutonium alloy surface adsorption model is in a stable adsorption state based on the adsorption energy, the adsorption stability of the plutonium alloy surface adsorption model is verified, further improving the reliability of the target plutonium alloy surface adsorption model.

[0085] In one embodiment, the placement positions of the adsorbed molecules include bridge sites, heart sites, and top sites on the surface of the plutonium alloy; the adsorption directions of the adsorbed molecules include a first adsorption direction perpendicular to the surface of the plutonium alloy and a second adsorption direction parallel to the surface of the plutonium alloy.

[0086] In this embodiment, by providing a variety of different placement positions of the adsorbed molecules and multiple different adsorption directions of the adsorbed molecules, a plurality of initial plutonium alloy surface adsorption models with different adsorption structures can be generated to form a control group, which is convenient for subsequent research on the law between the adsorption structure and the adsorption stability based on the plurality of initial plutonium alloy surface adsorption models with different adsorption structures, so that the target plutonium alloy structure model with the highest adsorption stability can be quickly and accurately found, and thus the data processing efficiency and the data processing effect can be improved.

[0087] In one embodiment, as Figure 6 shown, after the above step S3, the method for determining the plutonium alloy surface adsorption model provided by the present invention further includes step S4, and step S4 specifically includes steps S41 to S45, where:

[0088] Step S41: Obtain the adsorption capacity test data of the target plutonium alloy surface adsorption model, and obtain the adsorption capacity analysis result of the target plutonium alloy surface adsorption model based on the adsorption capacity test data.

[0089] Among them, the adsorption capacity test data includes the adsorption energy of the adsorbed molecules on the surface of the plutonium alloy, the closest distance between the adsorbed molecules and the surface of the plutonium alloy, the distance between the adsorbed molecules and the nearest neighbor atoms on the surface of the plutonium alloy, and the distance between two adsorbed molecules.

[0090] Step S42: Obtain the net charge distribution data of the target plutonium alloy surface adsorption model, and obtain the charge transfer analysis result of the target plutonium alloy surface adsorption model based on the net charge distribution data.

[0091] Among them, the net charge distribution data includes the transferred charge amount of the adsorbed molecules and the transferred charge amounts of the atoms in each layer of the plutonium alloy.

[0092] Step S43: Obtain the differential charge density data of the target plutonium alloy surface adsorption model, and obtain the charge density change analysis result of the target plutonium alloy surface adsorption model based on the differential charge density data.

[0093] Among them, the differential charge density data includes the differential charge density value of the target plutonium alloy surface. The differential charge density value represents the difference between the charge density value of the target plutonium alloy surface adsorption model and the sum of the charge density values of the adsorbed molecules and the plutonium alloy surface after adsorption, and its definition formula is:

[0094] Δρ = ρ A+B-ρ A -ρ B

[0095] Among them, Δρ is the differential charge density value, and ρ A+B is the charge density value of the adsorption model, and ρ A is the charge density value of the adsorbed molecule after adsorption, and ρ B is the charge density of the plutonium alloy surface after adsorption.

[0096] Step S44: Obtain the partial wave state density data of the adsorbed molecule on the surface of the target plutonium alloy surface adsorption model after adsorption, and obtain the analysis result of the electronic structure change of the target plutonium alloy surface adsorption model based on the partial wave state density data.

[0097] Step S45: Obtain the surface work function change data of the target plutonium alloy surface adsorption model, and obtain the surface work function analysis result of the target plutonium alloy surface adsorption model based on the surface work function change data.

[0098] Among them, the work function (Workfunction), also known as the work function and the work function of escape, reflects the minimum energy required for electrons to move from the inside of the solid to the surface. It is the energy difference between the vacuum electrostatic potential at infinity outside the metal and the Fermi level, indicating the ability of electrons to escape to the metal surface. The calculation formula is as follows:

[0099] Φ = E vacuum - E Fermi

[0100] Among them, "Φ" represents the work function, "E vacuum " represents the vacuum level, and "E Fermi " represents the Fermi level, with the unit of eV.

[0101] In the above steps S41 to S45, by analyzing the adsorption capacity, charge transfer, charge density change, electronic structure change, and surface work function of the target plutonium alloy surface adsorption model, the interaction mechanism between the adsorbed molecule and the target plutonium alloy surface adsorption model is explored, providing a theoretical basis for the research on the surface corrosion of plutonium alloys.

[0102] Two specific embodiments are provided below to further illustrate the method for determining the plutonium alloy surface adsorption model provided by the present invention.

[0103] In the first specific embodiment, the method for determining the plutonium alloy surface adsorption model provided by the present invention includes the following steps:

[0104] Step 1: Obtain the experimental value of the lattice constant of plutonium; based on a preset structure optimization algorithm and a preset solid model equation of state, obtain the theoretical value of the lattice constant of plutonium. The preset structure optimization algorithm is used to optimize the structural parameters of the model to make the model in a stable state; obtain the current error value between the experimental value of the lattice constant and the theoretical value of the lattice constant, and determine whether the current error value is within the preset error range; in the case where the current error value is within the preset error range, construct a crystal structure model of plutonium based on the theoretical value of the lattice constant.

[0105] Step 2: Select multiple groups of doping positions in the crystal structure model, and replace the plutonium atoms at each group of doping positions with doping atoms to generate multiple initial plutonium alloy structure models; obtain the surface energy data of each initial plutonium alloy structure model to obtain multiple groups of surface energy data; based on the multiple groups of surface energy data, screen out the initial plutonium alloy structure model with the minimum surface energy from the multiple initial plutonium alloy structure models; use the initial plutonium alloy structure model with the minimum surface energy as the target plutonium alloy structure model.

[0106] Step 3: Place the adsorbed molecules on the surface of the target plutonium alloy structure model to obtain an initial plutonium alloy surface adsorption model; based on a preset second model optimization strategy, adjust the placement positions of the adsorbed molecules in the initial plutonium alloy surface adsorption model to make the adsorbed molecules stably adsorbed on the plutonium alloy surface to obtain an optimized plutonium alloy surface adsorption model; obtain the adsorption energy of the adsorbed molecules on the plutonium alloy surface in the optimized plutonium alloy surface adsorption model, and based on the adsorption energy, determine whether the optimized plutonium alloy surface adsorption model is in a stable adsorption state; in the case where the optimized plutonium alloy surface adsorption model is in a stable adsorption state, determine the optimized plutonium alloy surface adsorption model as the target plutonium alloy surface adsorption model.

[0107] Furthermore, the doping atom is a metal atom. Preferably, the doping atom is a gallium atom, a cerium atom or an aluminum atom to increase the temperature stability of plutonium, and at the same time significantly improve the flexibility and ductility of metallic plutonium, thereby improving the material properties of the plutonium alloy material.

[0108] In Specific Embodiment 2, taking metallic plutonium δ-Pu as the substrate, gallium atoms as the doping atoms, and hydrogen molecules H2 and oxygen molecules O2 as the adsorbed molecules, the method for determining the plutonium alloy surface adsorption model provided by the present invention is described in more detail. The specific steps include the following:

[0109] Step (1): Obtain the experimental value of the lattice constant of plutonium δ-Pu, which is α = β = γ = 90°, the volume occupied by a single unit cell δ-Pu is one of the six stable phases of plutonium. The crystal structure of metallic δ-Pu is face-centered cubic (fcc), and the space group code is Fm-3m. The Birch-Mumaghan equation of state is obtained, and the volume empirical data of plutonium is obtained based on the VASP built-in optimization algorithm, and the system energy empirical data corresponding to the volume empirical data is obtained. The corresponding relationship between the volume empirical data and the system energy empirical data is shown in Table 1. The lattice constant of plutonium is the side length of its crystal structure, and the volume of plutonium is the cube of its lattice constant.

[0110] Table 1 Relationship between the lattice constant, volume and system energy of plutonium

[0111]

[0112] Figure 7a Schematic diagram of the relationship curve between system energy and volume change in the second specific embodiment provided by the present invention. The volume empirical data and the system energy empirical data are substituted into the Birch-Murnaghan state equation for fitting processing, and the Birch-Murnaghan third-order equation fitting curve of the relationship between system energy and volume change is drawn, as shown in FIG. Figure 7a As shown, find Figure 7a The lowest point system energy is the lowest system energy (i.e. -54.73103841 eV), and the volume value corresponding to the lowest system energy is obtained (i.e. ), and based on the volume value corresponding to the lowest system energy, the theoretical value of the lattice constant of plutonium is obtained (i.e. ).in, Figure 7a The horizontal axis of the middle curve is the scaling factor, and the vertical axis is the system energy.

[0113] It can be seen from this that the theoretical value of the lattice constant of plutonium δ-Pu is α=β=γ=90°, volume The system energy E = -54.731 eV. The current error value between the experimental value of the lattice constant and the theoretical value of the lattice constant is obtained, which is 2.9%. According to the calculation results, the current error value between the experimental value of the lattice constant and the theoretical value of the lattice constant is within the preset error range. Figure 7b As shown in the figure, the crystal structure model of plutonium δ-Pu is drawn according to the theoretical value of the lattice constant of plutonium δ-Pu. Figure 7b The crystal structure model of plutonium δ-Pu is drawn based on the lattice constant corresponding to the lowest system energy, and the error between the experimental value of the lattice constant and the theoretical value of the lattice constant is within the preset error range. Therefore, the crystal structure model of plutonium δ-Pu has high stability and reliability.

[0114] Step (2): Since plutonium δ-Pu has a face-centered cubic structure with high symmetry, each crystal plane in each crystal plane family is completely equivalent. Plutonium δ-Pu has three crystal plane families, namely {100}, {110}, and {111}. According to the crystal structure model of plutonium δ-Pu, select the {100} crystal plane to construct the crystal orientation plane structure model of δ-Pu, select 5 layers of atomic structure, and set the thickness of the vacuum layer to The crystal orientation plane structure model of the crystal plane {100} is as Figure 8 shown. Taking the example of doping gallium atoms into the crystal orientation plane structure model of the crystal plane {100} below, the construction process of the plutonium gallium alloy structure model is described. In the same way, gallium atoms can be doped into the crystal orientation plane structure models corresponding to other crystal planes to construct a complete plutonium gallium alloy structure model.

[0115] Since the outermost surface atoms have a great influence on the surface properties of the model, in order to explore the changes in the surface properties of the plutonium gallium alloy structure model after doping gallium atoms into the crystal structure model of plutonium δ-Pu, four groups of doping positions are selected on the surface of the crystal structure model, and the plutonium atoms at each group of doping positions are replaced with gallium atoms to generate four initial plutonium gallium alloy structure models with different numbers of gallium atoms. Figures 9a to 9d Figure is the structural schematic diagram of the initial plutonium gallium alloy structure model in the second specific embodiment provided by the present invention. Among them, the first group of doping positions is as Figure 9a shown, and the number of gallium atoms is one. The second group of doping positions is as Figure 9b shown, and the number of gallium atoms is four. The third group of doping positions is as Figure 9c shown, and the number of gallium atoms is five. The fourth group of doping positions is as Figure 9d shown, and the number of gallium atoms is six.

[0116] Obtain the surface energy data of each initial plutonium gallium alloy structure model to obtain multiple groups of surface energy data, as shown in Table 2. The surface energy data includes surface energy, the number of gallium atoms, and the doping position. Among them, "E slab " represents the total energy of the initial plutonium gallium alloy structure model, "A" represents the surface area of the initial plutonium gallium alloy structure model, "N Ga " represents the number of gallium atoms, "E sur " represents the surface energy, "a" represents Figure 9a the first group of doping positions shown, "b" represents Figure 9b the second group of doping positions shown, "c" represents Figure 9c the third group of doping positions shown, "d" represents Figure 9d the fourth group of doping positions shown.

[0117] Table 2 Table of the variation relationship between surface energy and the number of gallium atoms

[0118]

[0119] Based on multiple sets of surface energy data, a schematic diagram of the relationship between the surface energy of the initial plutonium-gallium alloy structure model and the number of doped atoms is drawn, as Figure 10 shown. According to Figure 10 the schematic diagram of the relationship between the surface energy and the number of doped atoms shown, among the four initial plutonium-gallium alloy structure models, the one with the minimum surface energy is Figure 11a the initial plutonium-gallium alloy structure model doped with one gallium atom shown in which has a surface energy of And when the number of doped gallium atoms increases, the surface energy increases, and the maximum is Therefore, the initial plutonium-gallium alloy structure model with the minimum surface energy (such as Figure 9a shown) is used as the target plutonium-gallium alloy structure model, that is, the gallium atom replaces the plutonium atom at the most central position on the surface of the crystal structure model of plutonium δ-Pu.

[0120] Step (3): The adsorbed molecules include oxygen molecules and hydrogen molecules. The placement positions of the adsorbed molecules include the bridge position (bridge, abbreviated as b), the hollow position (hollow, abbreviated as h), and the top position (top, abbreviated as t) on the surface of the plutonium-gallium alloy. The adsorption directions of the adsorbed molecules include the first adsorption direction (ver) perpendicular to the surface of the plutonium-gallium alloy and the second adsorption direction (hor) parallel to the surface of the plutonium-gallium alloy. Set the bond length of O-O in the oxygen molecule O2 to 12.4596 nm and the bond length of H-H in the hydrogen molecule H2 to 7.3717 nm. Based on the combination of the above three placement positions and two adsorption directions, the hydrogen molecules and oxygen molecules are respectively placed on the surface of the target plutonium-gallium alloy structure model with a coverage of 0.25, obtaining six initial plutonium-gallium alloy surface adsorption models corresponding to hydrogen molecules (such as Figures 11a to 11f shown) and six initial plutonium-gallium alloy surface adsorption models corresponding to oxygen molecules (such as Figures 12b to 12f shown).

[0121] Taking Figure 11a as an example to illustrate the initial plutonium-gallium alloy surface adsorption model corresponding to hydrogen molecules, "Initial H-1" represents the first initial plutonium-gallium alloy surface adsorption model corresponding to hydrogen molecules, that is, "H-t-hor", where "H" represents the adsorption of hydrogen molecules, "t" represents the placement position of hydrogen molecules as the top position, and "hor" represents the adsorption direction of hydrogen molecules as the second adsorption direction parallel to the surface of the plutonium-gallium alloy. In addition, in the two figures corresponding to "Initial H-1", the left figure is the three-dimensional view of the initial plutonium-gallium alloy surface adsorption model, and the right figure is the top view of the initial plutonium-gallium alloy surface adsorption model. Similarly, Figure 11b "Initial H-2" in Figure 11c"Initial H-3" in it represents the third initial plutonium-gallium alloy surface adsorption model corresponding to hydrogen molecules, that is, "H-t-ver". Figure 11d "Initial H-4" in it represents the fourth initial plutonium-gallium alloy surface adsorption model corresponding to hydrogen molecules, that is, "H-b-hor". Figure 11e "Initial H-5" in it represents the fifth initial plutonium-gallium alloy surface adsorption model corresponding to hydrogen molecules, that is, "H-h-hor". Figure 11f "Initial H-6" in it represents the sixth initial plutonium-gallium alloy surface adsorption model corresponding to hydrogen molecules, that is, "H-b-ver".

[0122] Take Figure 12a as an example to illustrate the initial plutonium-gallium alloy surface adsorption model corresponding to oxygen molecules. "Initial O-1" represents the first initial plutonium-gallium alloy surface adsorption model corresponding to oxygen molecules, that is, "O-t-hor". Among them, "O" represents the adsorption of oxygen molecules, "t" represents that the placement position of oxygen molecules is the top position, and "hor" represents that the adsorption direction of oxygen molecules is the second adsorption direction parallel to the plutonium-gallium alloy surface. In addition, in the two figures corresponding to "Initial O-1", the left figure is the three-dimensional view of the initial plutonium-gallium alloy surface adsorption model, and the right figure is the top view of the initial plutonium-gallium alloy surface adsorption model. Similarly, Figure 12b "Initial O-2" in it represents the second initial plutonium-gallium alloy surface adsorption model corresponding to oxygen molecules, that is, "O-h-ver". Figure 12c "Initial O-3" in it represents the third initial plutonium-gallium alloy surface adsorption model corresponding to oxygen molecules, that is, "O-t-ver". Figure 12d "Initial O-4" in it represents the fourth initial plutonium-gallium alloy surface adsorption model corresponding to oxygen molecules, that is, "O-b-hor". Figure 12e "Initial O-5" in it represents the fifth initial plutonium-gallium alloy surface adsorption model corresponding to oxygen molecules, that is, "O-h-hor". Figure 12f "Initial O-6" in it represents the sixth initial plutonium-gallium alloy surface adsorption model corresponding to oxygen molecules, that is, "O-b-ver".

[0123] Adjust the placement positions of hydrogen molecules and oxygen molecules in the initial plutonium-gallium alloy surface adsorption model based on the conjugate gradient method so that the hydrogen molecules and oxygen molecules are stably adsorbed on the plutonium-gallium alloy surface, obtaining the optimized plutonium-gallium alloy surface adsorption model corresponding to the hydrogen molecules and the optimized plutonium-gallium alloy surface adsorption model corresponding to the oxygen molecules. Obtain the adsorption energies of the hydrogen molecules and oxygen molecules on the plutonium-gallium alloy surface in the optimized plutonium-gallium alloy surface adsorption model. When the adsorption energy is greater than 0, the adsorption reaction is an endothermic reaction, and at this time, the optimized plutonium-gallium alloy surface adsorption model is not in a stable adsorption state. When the adsorption energy is less than 0, the adsorption reaction is an exothermic reaction, and at this time, it can be determined that the optimized plutonium-gallium alloy surface adsorption model is in a stable adsorption state, and this optimized plutonium-gallium alloy surface adsorption model is used as the target plutonium-gallium alloy surface adsorption model (as Figures 13a to 13j shown).

[0124] Among them, Figure 13a "Target O-1" in represents the first target plutonium-gallium alloy surface adsorption model corresponding to oxygen molecules, that is, "O-t-hor". Figure 13b "Target O-2" in represents the first target plutonium-gallium alloy surface adsorption model corresponding to oxygen molecules, that is, "O-h-ver". Figure 13c "Target O-3" in represents the first target plutonium-gallium alloy surface adsorption model corresponding to oxygen molecules, that is, "O-t-ver". Figure 13d "Target O-4" in represents the first target plutonium-gallium alloy surface adsorption model corresponding to oxygen molecules, that is, "O-b-hor". Figure 13e "Target O-5" in represents the first target plutonium-gallium alloy surface adsorption model corresponding to oxygen molecules, that is, "O-h-hor". Figure 13f "Target O-6" in represents the first target plutonium-gallium alloy surface adsorption model corresponding to oxygen molecules, that is, "O-b-ver". Figure 13g "Target H-1" in represents the first target plutonium-gallium alloy surface adsorption model corresponding to hydrogen molecules, that is, "H-t-hor". Figure 13h "Target H-2" in represents the second target plutonium-gallium alloy surface adsorption model corresponding to hydrogen molecules, that is, "H-h-ver". Figure 13i "Target H-3" in represents the third target plutonium-gallium alloy surface adsorption model corresponding to hydrogen molecules, that is, "H-h-hor". Figure 13j "Target H-4" in represents the fourth target plutonium-gallium alloy surface adsorption model corresponding to hydrogen molecules, that is, "H-b-hor".

[0125] Step (4): Obtain the adsorption capacity test data of the adsorption model on the surface of the target plutonium-gallium alloy, and based on the adsorption capacity test data, obtain the adsorption capacity analysis result of the adsorption model on the surface of the target plutonium-gallium alloy. Table 3 is the table corresponding to the adsorption capacity test data. As shown in Table 3, the adsorption capacity test data includes the adsorption energy of the adsorbed molecule on the surface of the plutonium-gallium alloy, the closest distance between the adsorbed molecule and the surface of the plutonium-gallium alloy, the distance between the adsorbed molecule and the nearest neighbor atom on the surface of the plutonium-gallium alloy, and the distance between two adsorbed molecules. When the adsorption energy is less than -0.415 eV, the adsorption type is determined to be chemisorption. When the adsorption energy is greater than -0.415 eV, the adsorption type is determined to be physisorption.

[0126] Table 3 Table corresponding to the adsorption capacity test data

[0127]

[0128] Combined with Figures 13a to 13f And analysis based on Table 3 shows that the adsorption capacity analysis result corresponding to oxygen molecules is that the adsorption intensity of oxygen molecules on the surface of the plutonium-gallium alloy is much greater than that of hydrogen molecules. Oxygen molecules can be stably adsorbed at the hollow site, bridge site, and top site. The adsorption energy is much less than -0.415 eV, and the adsorption energy is between -5 and -10 eV, releasing a large amount of heat. Its adsorption type is chemisorption. From the perspective of bond length, the oxygen molecules dissociate during the adsorption process, the O-O bond breaks to form two oxygen atoms adsorbed on the surface of the plutonium-gallium alloy, and new chemical bonds are formed with the plutonium atoms and gallium atoms on the surface of the plutonium-gallium alloy respectively. From the perspective of adsorption energy, the relationship between the adsorption position and the adsorption energy is relatively small. During the adsorption of oxygen, a large degree of structural change occurs on the surface of the plutonium-gallium alloy, and there is a large degree of interaction between oxygen and the surface of the plutonium-gallium alloy.

[0129] Combined with Figures 13g to 13j And analysis based on Table 3 shows that the adsorption capacity analysis result corresponding to hydrogen molecules is that hydrogen molecules can be stably adsorbed only when the placement position of the initial adsorption model of the plutonium-gallium alloy surface is at the top site and the adsorption direction is the second adsorption direction parallel to the surface of the plutonium-gallium alloy, and its adsorption energy is greater than -0.415 eV, and the adsorption type is physisorption. During the optimization process, the initially parallel adsorbed hydrogen molecules gradually turn into vertical adsorption, and there is a strong repulsive force between the hydrogen molecules and the surface of the plutonium-gallium alloy. From the perspective of adsorption energy, hydrogen molecules are not easily adsorbed on the surface of the plutonium-gallium alloy, and the order of adsorption difficulty is the hollow site, bridge site, and top site. In terms of adsorption distance, the distance between the hydrogen atoms in the hydrogen molecule and the surface of the plutonium-gallium alloy is much greater than the distance between the oxygen atoms in the oxygen molecule and the surface of the plutonium-gallium alloy, and the bond length between the hydrogen molecules does not change significantly.

[0130] Step (5): The adsorption reaction of hydrogen and oxygen on the surface of plutonium gallium alloy is necessarily accompanied by the transfer of charges between the active gas molecules (e.g., oxygen molecules and hydrogen molecules) and the surface atoms of the plutonium gallium alloy. The Bader charge analysis can quantitatively represent the amount of charge transfer to analyze the charge transfer situation on the surface of the plutonium gallium alloy. Based on the Bader charge analysis method, the net charge distribution data of the target plutonium gallium alloy surface adsorption model is obtained, and based on the net charge distribution data, the charge transfer analysis result of the target plutonium gallium alloy surface adsorption model is obtained. Table 4 is the table corresponding to the net charge distribution data. As shown in Table 4, the net charge distribution data includes the transferred charge amounts of hydrogen molecules, oxygen molecules, and the transferred charge amounts of each layer of atoms in the plutonium gallium alloy. Among them, "Q1" and "Q2" represent the transferred charge amounts of hydrogen atoms in hydrogen molecules or oxygen atoms in oxygen molecules; Qtotal represents the total transferred charge amount of the adsorbed molecules, Qtotal = Q1 + Q2; "Q1st", "Q2nd", "Q3rd", "Q4th", and "Q5th" are the transferred charge amounts of the atoms in the first to fifth layers on the surface of the plutonium gallium alloy, respectively.

[0131] Table 4 The table corresponding to the net charge distribution data

[0132]

[0133] According to the analysis of Table 4, the charge transfer analysis result is as follows: Both hydrogen molecules and oxygen molecules gain charges during the adsorption process, but the amounts of charges are quite different. The interaction force between hydrogen molecules and the surface atoms of the plutonium gallium alloy is small, and the charge transfer amount is small. The interaction force between oxygen molecules and the surface atoms of the plutonium gallium alloy is large, and the charge transfer amount is large, that is, the adsorption type of oxygen molecules is chemical adsorption, and the adsorption type of hydrogen molecules is physical adsorption. Since the larger the charge transfer amount, the more heat is released during the adsorption process and the greater the adsorption strength. In the adsorption models of oxygen molecules on the surface of each target plutonium gallium alloy, the charge transfer amounts are not very different. In particular, the adsorption models of the target plutonium gallium alloy surface with the adsorption positions and directions of bridge-site parallel adsorption and heart-site vertical adsorption have larger adsorption energies and charge transfer amounts. In all the adsorption models of the target plutonium gallium alloy surface, the atoms in the first, second, fourth, and fifth layers of the plutonium gallium alloy surface generally lose charges, and the atoms in the third layer gain charges. In terms of numerical values, the charge transfer amount of the first-layer atoms is the largest. Thus, it can be seen that oxygen molecules and hydrogen molecules mainly interact with the atoms in the first layer on the surface of the plutonium gallium alloy.

[0134] Step (6): Figures 14a to 14b is the schematic diagram of the differential charge density data in the second specific embodiment provided by the present invention. The differential charge density data of the target plutonium gallium alloy surface adsorption model is obtained, and based on the differential charge density data, the charge density change analysis result of the target plutonium gallium alloy surface adsorption model is obtained. The charge density change analysis result is specifically as follows:Figure 14a It is a schematic diagram of the differential charge density data corresponding to hydrogen molecules. As Figure 14a shown, in the most stable plutonium-gallium alloy surface adsorption model "H-t-hor" of hydrogen molecules, in the plutonium-gallium alloy surface adsorption model, the charge density on the side of the hydrogen molecule close to the plutonium-gallium alloy surface decreases, while the charge density on the other side increases. The difference in the amount of charge increase and decrease is not significant. Compared with the atoms in other layers, the change in the charge density of the first-layer atoms on the plutonium-gallium alloy surface is more obvious. Hydrogen molecules mainly interact with the first-layer atoms on the plutonium-gallium alloy surface. Figure 14b It is a schematic diagram of the differential charge density data corresponding to oxygen molecules. As Figure 14b shown, in the most stable plutonium-gallium alloy surface adsorption model "O-h-ver" of oxygen molecules, the same electron density isosurface is used as that of the plutonium-gallium alloy surface adsorption model corresponding to hydrogen molecules. In the plutonium-gallium alloy surface adsorption model, the charge density around the oxygen molecule increases, and the charge density of its neighboring plutonium atoms decreases. There is a large interaction force between the dissociated oxygen atoms and their neighboring plutonium atoms. Oxygen molecules mainly interact with the first-layer atoms on the plutonium-gallium alloy surface.

[0135] By comparing and analyzing Figure 14a with Figure 14b , it can be known that in the plutonium-gallium alloy surface adsorption model, compared with hydrogen atoms, the degree of charge transfer between oxygen atoms and the surface atoms of the plutonium-gallium alloy is greater, and the influence of the adsorption of oxygen atoms on the surface charge distribution of the plutonium-gallium alloy is stronger. The interaction force between oxygen molecules and the plutonium-gallium alloy surface is greater. The reason may be that the electronegativity of oxygen atoms is stronger than that of hydrogen atoms, and oxygen atoms have a stronger attraction for electrons, so they are more likely to interact with metal atoms. Through the calculation and analysis of differential charge density, the charge movement and the properties such as the bonding polarization direction during the bonding and bonding electron coupling processes can be clearly obtained, which helps to understand the adsorption process.

[0136] Step (7): In order to further study the microscopic interaction between oxygen atoms in oxygen molecules and the surface atoms of the plutonium-gallium alloy, select the target plutonium-gallium alloy surface adsorption model with the most stable adsorption of oxygen molecules for research, obtain the partial wave state density data of the oxygen molecules adsorbed on the plutonium-gallium alloy surface in the target plutonium-gallium alloy surface adsorption model, and obtain the analysis result of the electronic structure change of the target plutonium-gallium alloy surface adsorption model based on the partial wave state density data. Figures 15a to 15b It is a schematic diagram of the partial wave state density data corresponding to oxygen atoms. Among them, Figure 15a is a comparison diagram of the partial wave state density of oxygen atoms and their nearest neighbor plutonium atoms, Figure 15b is a comparison diagram of the partial wave state density of oxygen atoms and their nearest neighbor gallium atoms. Figures 15a to 15b "Pure" in represents the state density value of the pure surface model. The abscissa represents the energy level of single electrons, and the ordinate represents the number of states.

[0137] According to Figure 15a and Figure 15b it can be known that the analysis result of the electronic structure change corresponding to the oxygen molecule is as follows: the electron states of the 2p orbital and 2s orbital of the oxygen atom are respectively distributed near -5 eV and -22 eV. First of all, the interaction between the oxygen atom and the plutonium atom is near -5 eV, and the electron states of the 6s, 7s, and 6d orbitals of the plutonium atom are all split, and new obvious peaks appear, and the peak values are relatively large, which indicates that there is a hybridization effect between the 2p orbital of the oxygen atom and the 6s, 7s, and 6d orbitals of the plutonium atom, forming a stable bonding effect. The interaction between the oxygen atom and the plutonium atom is near -24 eV to -16 eV. The peak value of the 6p orbital of the plutonium atom decreases, the broadening increases, and it is basically the same as the broadening of the 2s orbital of the oxygen atom. The electron states of other orbitals of the plutonium atom do not change to a large extent. Secondly, the interaction between the oxygen atom and the gallium atom is near -5 eV, and a peak with a relatively small intensity appears in the 4s orbital of the gallium atom. The interaction between the oxygen atom and the gallium atom is near -24 eV to -16 eV, and the broadening of the 3d orbital of the gallium atom also increases to a certain extent, but it is not significant. It can be seen that during the interaction between the oxygen molecule and the surface of the plutonium-gallium alloy, electron transfer occurs in the atomic orbitals of both, and the interaction intensity between the plutonium atom and the oxygen atom is relatively large. The mutual bonding effect is mainly due to the overlapping hybridization of the Pu-6s, Pu-7s, Pu-6d, Ga-3d, and O-2p orbitals.

[0138] In order to further study the microscopic interaction between the hydrogen atom and the surface atoms of the plutonium-gallium alloy, the target plutonium-gallium alloy surface adsorption model with the most stable hydrogen molecule adsorption is selected for research, and the partial wave state density data of the hydrogen molecule adsorbed on the surface of the plutonium-gallium alloy in the target plutonium-gallium alloy surface adsorption model are obtained, and the analysis result of the electronic structure change of the target plutonium-gallium alloy surface adsorption model is obtained based on the partial wave state density data. Figures 15c to 15d is a schematic diagram of the partial wave state density data corresponding to the hydrogen atom, where Figure 15c is a comparison diagram of the partial wave state density of the hydrogen atom and its nearest neighbor plutonium atom, Figure 15d is a comparison diagram of the partial wave state density of the hydrogen atom and its nearest neighbor gallium atom. Figures 15c to 15d The "pure" in

[0139] According to Figure 15c and Figure 15dIt can be seen that the analysis result of the electronic structure change corresponding to the hydrogen molecule is as follows: the electronic state of the hydrogen molecule is mainly concentrated around -7 eV and the Fermi level, and compared with the oxygen molecule, its electronic state intensity is smaller. First of all, the interaction between the hydrogen atom and the plutonium atom is around -7 eV. The electronic states of the 6s, 7s, and 6d orbitals of the plutonium atom show an energy broadening in this energy range, and they are distributed in the same energy range as the 1s orbital of the hydrogen atom, overlapping with the electronic state of the hydrogen molecule. The same phenomenon also occurs in the density of states orbitals of the gallium atom. The 4p and 3d orbitals near the Fermi level show a certain degree of broadening, while the 4s orbital of the gallium atom shows almost no obvious change before and after adsorption. From this, it can be known that only physical adsorption occurs between the hydrogen molecule and the plutonium-gallium alloy, no chemical bond is formed, and the density of electronic states will not change to a large extent. Compared with the adsorption of oxygen molecules, the interaction degree is smaller.

[0140] Step (8): Obtain the surface work function change data of the surface adsorption model of the target plutonium-gallium alloy, and based on the surface work function change data, obtain the surface work function analysis result of the surface adsorption model of the target plutonium-gallium alloy. There is currently no experimental data available for comparison of the surface work function of plutonium δ-Pu. The surface work function of its neighboring element uranium is in the range of 3.63 eV - 3.90 eV. The surface work function of pure plutonium reported in the literature is in the range of 4 eV - 5 eV. The surface work function of the plutonium-gallium alloy calculated in this invention is 2.989 eV. Compared with pure plutonium, the surface work function of the plutonium-gallium alloy has decreased. After the adsorption of hydrogen molecules and oxygen molecules, the surface work function of the plutonium-gallium alloy has changed to a certain extent because of the electronegativity difference between the surface atoms of the plutonium-gallium alloy and the adsorbed molecules, which causes a redistribution of charges during the adsorption process. It is known that the electronegativity of H is 2.1 and the electronegativity of O is 3.5. However, the surface work functions of the surface adsorption models of hydrogen molecules and oxygen molecules are not very different, probably because the distance between the oxygen molecule and the surface of the plutonium-gallium alloy is significantly smaller than that between the hydrogen molecule and the surface of the plutonium-gallium alloy, thus offsetting the surface dipole moment formed after the adsorption of oxygen molecules.

[0141] Table 5 The table corresponding to the surface work function change data

[0142] Adsorption model Vacuum level / eV Fermi level / eV Work function / eV △Φ / eV H - b - hor 6.74788 3.7704 2.97748 -0.04856 H - b - ver 6.80774 3.6797 3.12804 0.102 H - h - hor 6.69731 3.7233 2.97401 -0.05203 H - h - ver 6.68363 3.7529 2.93073 -0.09531 H - t - hor 6.86626 3.8399 3.02636 0.00032 H - t - ver 6.67606 3.7408 2.93526 -0.09078 O - b - hor 6.70248 3.8454 2.85708 -0.13247 O - b - ver 7.03123 3.5598 3.47143 0.48188 O - h - hor 6.91343 3.6899 3.22353 0.23398 O - h - ver 6.75235 3.7953 2.95705 -0.0325 O - t - hor 6.77736 3.8633 2.91406 -0.07549 O - t - ver 6.81517 3.8026 3.01257 0.02302 Clean surface 6.78165 3.7921 2.98955 /

[0143] Next, the device for determining the surface adsorption model of the plutonium alloy provided by the present invention will be described. The device for determining the surface adsorption model of the plutonium alloy described below can be correspondingly referred to the method for determining the surface adsorption model of the plutonium alloy described above.

[0144] Next, in combination with Figure 16 Describe the device for determining the surface adsorption model of the plutonium alloy of the present invention, as Figure 16As shown in the figure, the device 100 for determining the plutonium alloy surface adsorption model provided by the present invention includes: a crystal structure construction module 10, configured to obtain the theoretical value of the lattice constant of plutonium and construct a crystal structure model of plutonium based on the theoretical value of the lattice constant. A doping model construction module 20, configured to construct an initial plutonium alloy structure model based on the pre-obtained doping atoms and the crystal structure model, and optimize the structure of the initial plutonium alloy structure model based on a preset first model optimization strategy, so that the surface of the initial plutonium alloy structure model is in a stable state, and obtain a target plutonium alloy structure model. An adsorption model construction module 30, configured to construct an initial plutonium alloy surface adsorption model based on the pre-obtained adsorption molecules and the target plutonium alloy structure model, and optimize the structure of the initial plutonium alloy surface adsorption model based on a preset second model optimization strategy, so that the initial plutonium alloy surface adsorption model is in a stable adsorption state, and obtain a target plutonium alloy surface adsorption model.

[0145] In one embodiment, the crystal structure construction module 10 includes an experimental value acquisition unit, a theoretical value acquisition unit, an error value judgment unit, and a crystal model construction unit, where: The experimental value acquisition unit is configured to obtain the experimental value of the lattice constant of plutonium. The theoretical value acquisition unit is configured to obtain the theoretical value of the lattice constant of plutonium based on a preset structure optimization algorithm and a preset solid model state equation. The preset structure optimization algorithm is used to optimize the structure parameters of the solid model so that the solid model is in a stable state. The error value judgment unit is configured to obtain the current error value between the experimental value of the lattice constant and the theoretical value of the lattice constant, and judge whether the current error value is within a preset error range. The crystal model construction unit is configured to construct a crystal structure model of plutonium based on the theoretical value of the lattice constant when the current error value is within the preset error range.

[0146] In one embodiment, the above-mentioned theoretical value acquisition unit includes a state equation acquisition subunit, an empirical data acquisition subunit, a volume parameter calculation subunit, and a theoretical value acquisition subunit, where: The state equation acquisition subunit is configured to obtain a preset solid model state equation, and the preset solid model state equation represents the state equation between the volume of the solid model, the system energy corresponding to the volume, the lowest system energy, and the volume value corresponding to the lowest system energy. The empirical data acquisition subunit is configured to obtain the volume empirical data of plutonium and obtain the system energy empirical data corresponding to the volume empirical data. The volume parameter calculation subunit is configured to substitute the volume empirical data and the system energy empirical data into the preset solid model state equation, and calculate the volume value corresponding to the lowest system energy in the preset solid model state equation. The theoretical value acquisition subunit is configured to obtain the theoretical value of the lattice constant of plutonium based on the volume value corresponding to the lowest system energy.

[0147] In one embodiment, the doping model construction module 20 further includes an initial alloy model construction unit, a surface energy data acquisition unit, an alloy model screening unit, and a model determination unit, where: The initial alloy model construction unit is configured to select multiple groups of doping positions in the crystal structure model, and replace the plutonium atoms at each group of doping positions with doping atoms to generate multiple initial plutonium alloy structure models. The surface energy data acquisition unit is configured to acquire the surface energy data of each initial plutonium alloy structure model to obtain multiple groups of surface energy data. The alloy model screening unit is configured to screen out the initial plutonium alloy structure model with the minimum surface energy from the multiple initial plutonium alloy structure models based on the multiple groups of surface energy data. The alloy model determination unit is configured to use the initial plutonium alloy structure model with the minimum surface energy as the target plutonium alloy structure model.

[0148] In one embodiment, the adsorption model construction module 30 further includes an initial adsorption model construction unit, an adsorption model optimization unit, an adsorption energy acquisition unit, and an adsorption model determination unit, where: The initial adsorption model construction unit is configured to place the adsorption molecules on the surface of the target plutonium alloy structure model to obtain an initial plutonium alloy surface adsorption model. The adsorption model optimization unit is configured to adjust the placement positions of the adsorption molecules in the initial plutonium alloy surface adsorption model based on a preset second model optimization strategy so that the adsorption molecules are stably adsorbed on the plutonium alloy surface to obtain an optimized plutonium alloy surface adsorption model. The adsorption energy acquisition unit is configured to acquire the adsorption energy of the adsorption molecules on the plutonium alloy surface in the optimized plutonium alloy surface adsorption model, and determine whether the optimized plutonium alloy surface adsorption model is in a stable adsorption state based on the adsorption energy. The adsorption model determination unit is configured to determine the optimized plutonium alloy surface adsorption model as the target plutonium alloy surface adsorption model when the optimized plutonium alloy surface adsorption model is in a stable adsorption state.

[0149] In one embodiment, as Figure 16As shown, the device 100 for determining the surface adsorption model of plutonium alloy further includes an adsorption model analysis module 40. The adsorption model analysis module 40 includes an adsorption capacity analysis unit, a charge transfer analysis unit, a charge density analysis unit, an electronic structure analysis unit, and a work function analysis unit, where: The adsorption capacity analysis unit is used to obtain the adsorption capacity test data of the surface adsorption model of the target plutonium alloy, and obtain the adsorption capacity analysis result of the surface adsorption model of the target plutonium alloy based on the adsorption capacity test data. The charge transfer analysis unit is used to obtain the net charge distribution data of the surface adsorption model of the target plutonium alloy, and obtain the charge transfer analysis result of the surface adsorption model of the target plutonium alloy based on the net charge distribution data. The charge density analysis unit is used to obtain the differential charge density data of the surface adsorption model of the target plutonium alloy, and obtain the charge density change analysis result of the surface adsorption model of the target plutonium alloy based on the differential charge density data. The electronic structure analysis unit is used to obtain the partial wave state density data of the adsorbed molecules on the surface of the surface adsorption model of the target plutonium alloy after adsorption on the plutonium alloy surface, and obtain the electronic structure change analysis result of the surface adsorption model of the target plutonium alloy based on the partial wave state density data. The work function analysis unit is used to obtain the surface work function change data of the surface adsorption model of the target plutonium alloy, and obtain the surface work function analysis result of the surface adsorption model of the target plutonium alloy based on the surface work function change data.

[0150] Figure 17 An example of a schematic physical structure diagram of an electronic device is shown, such as Figure 17 As shown, the electronic device may include: a processor 710, a communication interface 720, a memory 730, and a communication bus 740. Among them, the processor 710, the communication interface 720, and the memory 730 complete communication with each other through the communication bus 740. The processor 710 can call the logical instructions in the memory 730 to execute the method for determining the surface adsorption model of plutonium alloy. The method includes: obtaining the theoretical value of the lattice constant of plutonium, and constructing a crystal structure model of plutonium based on the theoretical value of the lattice constant; constructing an initial plutonium alloy structure model based on the pre-obtained doping atoms and the crystal structure model, and optimizing the structure of the initial plutonium alloy structure model based on a preset first model optimization strategy to make the surface of the initial plutonium alloy structure model in a stable state, and obtaining a target plutonium alloy structure model; constructing an initial plutonium alloy surface adsorption model based on the pre-obtained adsorbed molecules and the target plutonium alloy structure model, and optimizing the structure of the initial plutonium alloy surface adsorption model based on a preset second model optimization strategy to make the initial plutonium alloy surface adsorption model in a stable adsorption state, and obtaining a target plutonium alloy surface adsorption model.

[0151] In addition, when the logical instructions in the above-mentioned memory 730 are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs.

[0152] On the other hand, the present invention also provides a computer program product. The computer program product includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the method for determining the plutonium alloy surface adsorption model provided by the above-mentioned various methods. The method includes: obtaining the theoretical value of the lattice constant of plutonium and constructing a crystal structure model of plutonium based on the theoretical value of the lattice constant; constructing an initial plutonium alloy structure model based on the pre-obtained doping atoms and the crystal structure model, and optimizing the structure of the initial plutonium alloy structure model based on a preset first model optimization strategy so that the surface of the initial plutonium alloy structure model is in a stable state to obtain a target plutonium alloy structure model; constructing an initial plutonium alloy surface adsorption model based on the pre-obtained adsorption molecules and the target plutonium alloy structure model, and optimizing the structure of the initial plutonium alloy surface adsorption model based on a preset second model optimization strategy so that the initial plutonium alloy surface adsorption model is in a stable adsorption state to obtain a target plutonium alloy surface adsorption model.

[0153] In another aspect, the present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it is used to implement the method for determining the plutonium alloy surface adsorption model provided by the above-mentioned various methods. The method includes: obtaining the theoretical value of the lattice constant of plutonium, and constructing a crystal structure model of plutonium based on the theoretical value of the lattice constant; constructing an initial plutonium alloy structure model based on the pre-obtained doping atoms and the crystal structure model, and optimizing the structure of the initial plutonium alloy structure model based on a preset first model optimization strategy, so that the surface of the initial plutonium alloy structure model is in a stable state, and obtaining a target plutonium alloy structure model; constructing an initial plutonium alloy surface adsorption model based on the pre-obtained adsorption molecules and the target plutonium alloy structure model, and optimizing the structure of the initial plutonium alloy surface adsorption model based on a preset second model optimization strategy, so that the initial plutonium alloy surface adsorption model is in a stable adsorption state, and obtaining a target plutonium alloy surface adsorption model.

[0154] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative work.

[0155] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments. Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for determining a plutonium alloy surface adsorption model, characterized in that, it includes: Obtaining the theoretical value of the lattice constant of plutonium, and constructing a crystal structure model of plutonium based on the theoretical value of the lattice constant; Constructing an initial plutonium alloy structure model based on the pre-obtained doping atoms and the crystal structure model, and optimizing the structure of the initial plutonium alloy structure model based on a preset first model optimization strategy, so that the surface of the initial plutonium alloy structure model is in a stable state, and obtaining a target plutonium alloy structure model; Constructing an initial plutonium alloy surface adsorption model based on the pre-obtained adsorption molecules and the target plutonium alloy structure model, and optimizing the structure of the initial plutonium alloy surface adsorption model based on a preset second model optimization strategy, so that the initial plutonium alloy surface adsorption model is in a stable adsorption state, and obtaining a target plutonium alloy surface adsorption model; The constructing an initial plutonium alloy structure model based on the pre-obtained doping atoms and the crystal structure model, and optimizing the structure of the initial plutonium alloy structure model based on a preset first model optimization strategy, so that the surface of the initial plutonium alloy structure model is in a stable state, and obtaining a target plutonium alloy structure model includes: Selecting multiple groups of doping positions in the crystal structure model, and replacing the plutonium atoms at each group of the doping positions with the doping atoms to generate multiple initial plutonium alloy structure models; Obtaining the surface energy data of each initial plutonium alloy structure model to obtain multiple groups of surface energy data; Screening out the initial plutonium alloy structure model with the minimum surface energy from multiple initial plutonium alloy structure models based on multiple groups of the surface energy data; Taking the initial plutonium alloy structure model with the minimum surface energy as the target plutonium alloy structure model.

2. The method for determining a plutonium alloy surface adsorption model according to claim 1, characterized in that, the obtaining the theoretical value of the lattice constant of plutonium, and constructing a crystal structure model of plutonium based on the theoretical value of the lattice constant includes: Obtaining the experimental value of the lattice constant of plutonium; Obtaining the theoretical value of the lattice constant of plutonium based on a preset structure optimization algorithm and a preset solid model state equation, and the preset structure optimization algorithm is used to optimize the structure parameters of the solid model so that the solid model is in a stable state; Obtaining the current error value between the experimental value of the lattice constant and the theoretical value of the lattice constant, and judging whether the current error value is within a preset error range; In the case where the current error value is within the preset error range, constructing a crystal structure model of plutonium based on the theoretical value of the lattice constant.

3. The method for determining a plutonium alloy surface adsorption model according to claim 2, characterized in that, the obtaining the theoretical value of the lattice constant of plutonium based on a preset structure optimization algorithm and a preset solid model state equation includes: Obtaining a preset solid model state equation, and the preset solid model state equation represents the state equation between the volume of the solid model, the system energy corresponding to the volume, the lowest system energy, and the volume value corresponding to the lowest system energy; Obtaining the volume empirical data of plutonium, and obtaining the system energy empirical data corresponding to the volume empirical data; Substitute the volume empirical data and the system energy empirical data into the preset solid model equation of state, and calculate the volume value corresponding to the lowest system energy in the preset solid model equation of state; Obtain the theoretical value of the lattice constant of plutonium based on the volume value corresponding to the lowest system energy.

4. The method for determining the plutonium alloy surface adsorption model according to claim 1, characterized in that, the method of constructing an initial plutonium alloy surface adsorption model based on the pre-obtained adsorbed molecules and the target plutonium alloy structural model, and optimizing the structure of the initial plutonium alloy surface adsorption model based on a preset second model optimization strategy to make the initial plutonium alloy surface adsorption model in a stable adsorption state, and obtaining a target plutonium alloy surface adsorption model, includes: Place the adsorbed molecules on the surface of the target plutonium alloy structural model to obtain an initial plutonium alloy surface adsorption model; Adjust the placement position of the adsorbed molecules in the initial plutonium alloy surface adsorption model based on the preset second model optimization strategy to make the adsorbed molecules stably adsorbed on the plutonium alloy surface, and obtain an optimized plutonium alloy surface adsorption model; Obtain the adsorption energy of the adsorbed molecules on the plutonium alloy surface in the optimized plutonium alloy surface adsorption model, and judge whether the optimized plutonium alloy surface adsorption model is in a stable adsorption state based on the adsorption energy; When the optimized plutonium alloy surface adsorption model is in a stable adsorption state, determine the optimized plutonium alloy surface adsorption model as the target plutonium alloy surface adsorption model.

5. The method for determining the plutonium alloy surface adsorption model according to claim 1, characterized in that, after optimizing the structure of the initial plutonium alloy surface adsorption model based on the preset second model optimization strategy to make the initial plutonium alloy surface adsorption model in a stable adsorption state and obtaining a target plutonium alloy surface adsorption model, the method further includes: Obtain the adsorption capacity test data of the target plutonium alloy surface adsorption model, and obtain the adsorption capacity analysis result of the target plutonium alloy surface adsorption model based on the adsorption capacity test data; Obtain the net charge distribution data of the target plutonium alloy surface adsorption model, and obtain the charge transfer analysis result of the target plutonium alloy surface adsorption model based on the net charge distribution data; Obtain the differential charge density data of the target plutonium alloy surface adsorption model, and obtain the charge density change analysis result of the target plutonium alloy surface adsorption model based on the differential charge density data; Obtain the partial wave state density data of the adsorbed molecules on the plutonium alloy surface after adsorption in the target plutonium alloy surface adsorption model, and obtain the electronic structure change analysis result of the target plutonium alloy surface adsorption model based on the partial wave state density data; Obtain the surface work function change data of the target plutonium alloy surface adsorption model, and obtain the surface work function analysis result of the target plutonium alloy surface adsorption model based on the surface work function change data.

6. A device for determining a plutonium alloy surface adsorption model, characterized in that, comprises: A crystal structure construction module, configured to obtain the theoretical value of the lattice constant of plutonium, and construct a crystal structure model of plutonium based on the lattice constant theoretical value; A doping model construction module, configured to construct an initial plutonium alloy structure model based on the pre-acquired doping atoms and the crystal structure model, and optimize the structure of the initial plutonium alloy structure model based on a preset first model optimization strategy, so that the surface of the initial plutonium alloy structure model is in a stable state, and obtain a target plutonium alloy structure model; An adsorption model construction module, configured to construct an initial plutonium alloy surface adsorption model based on the pre-acquired adsorption molecules and the target plutonium alloy structure model, and optimize the structure of the initial plutonium alloy surface adsorption model based on a preset second model optimization strategy, so that the initial plutonium alloy surface adsorption model is in a stable adsorption state, and obtain a target plutonium alloy surface adsorption model; The doping model construction module includes: An initial alloy model construction unit, configured to select multiple groups of doping positions in the crystal structure model, and replace the plutonium atoms at each group of doping positions with doping atoms to generate multiple initial plutonium alloy structure models; A surface energy data acquisition unit, configured to acquire the surface energy data of each initial plutonium alloy structure model to obtain multiple groups of surface energy data; An alloy model screening unit, configured to screen out the initial plutonium alloy structure model with the minimum surface energy from multiple initial plutonium alloy structure models based on multiple groups of surface energy data; An alloy model determination unit, configured to use the initial plutonium alloy structure model with the minimum surface energy as the target plutonium alloy structure model.

7. An electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein, when the processor executes the program, it implements the method for determining the plutonium alloy surface adsorption model according to any one of claims 1 to 5.

8. A non-transitory computer-readable storage medium, on which a computer program is stored, wherein, when the computer program is executed by a processor, it implements the method for determining the plutonium alloy surface adsorption model according to any one of claims 1 to 5.

9. A computer program product, including a computer program, wherein, when the computer program is executed by a processor, it implements the method for determining the plutonium alloy surface adsorption model according to any one of claims 1 to 5.

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