Metal surface Patch effect detection method based on first principle

Abstract

The invention discloses a metal surface Patch effect detection method based on a first principle. The method comprises the following steps: acquiring an actual primitive cell crystal structure of a target metal surface and acquiring a corresponding primitive cell crystal structure data file; establishing a slab model based on the metal primitive cell file, and calculating to obtain a work function difference caused by crystal face anisotropy after structure optimization; establishing a grain boundary model of the target crystal face to obtain the influence of the existence of the grain boundary on the work function; an adsorption model and a defect model are established on the basis of the slab structure model with the stable configuration, work function change is obtained after structure optimization, and finally detection of the Patch effect on the metal surface is achieved. According to the method, the high operation cost caused by experimental equipment and experimental materials is reduced, the process operation is simple and convenient, and the root cause of the Patch effect on the metal surface can be revealed.

Description

Technical Field

[0001] The present invention belongs to the field of computer technology, and in particular relates to a metal surface patch effect detection method based on first principles. Background Art

[0002] The surface of an ideal conductor is equipotential, but the potential distribution on the surface of an actual conductor is not uniform and varies over time. This effect is called the Patch effect. This phenomenon is caused by factors such as regions with different crystal orientations, radiation damage, and contaminants. The existence of the Patch effect has a significant impact on high-precision experiments and measurements, especially in areas that require extremely high precision and stability, such as gravitational wave detection.

[0003] In gravitational wave detection, the main load of the inertial sensor carried by the satellite is one or two Au-plated metal blocks as test masses. The reference datum of the inertial sensor requires that the trajectory moves along the geodesic without drag, and that the noise to the test mass is lower than the detection index. However, the patch effect of the test mass has always been one of the factors affecting the detection accuracy, posing a challenge to achieving high measurement accuracy in missions such as LISA and Tianqin. Therefore, there is an urgent need to have a deeper understanding of the patch effect. Factors that cause the patch effect, such as surface adsorption, crystal plane orientation, surface defects, etc. In order to determine the impact of these factors on the detection accuracy, it is necessary to establish a relevant model to calculate the changes in surface potential under the influence of these factors. Summary of the invention

[0004] In order to solve the above technical problems, the present invention constructs a variety of relevant models according to different influencing factors to explore the Patch effect on the metal surface.

[0005] The technical solution adopted by the present invention to solve the technical problem is: a method for constructing a slab model, a grain boundary model, an adsorption model and a defect model based on first principle calculation in the present invention,

[0006] The present invention first provides a metal surface patch effect detection method based on the first principle, comprising the following steps:

[0007] 1) Obtain the actual unit cell crystal structure of the target metal surface;

[0008] 2) Obtaining a unit cell crystal structure data file corresponding to the actual unit cell crystal structure from a material database;

[0009] 3) cutting a target crystal plane based on the primitive cell crystal structure data file, and constructing a grain boundary model of the target crystal plane based on the cut target crystal plane and a slab model with a vacuum layer;

[0010] 4) performing first principle relaxation calculations on the slab model and the grain boundary model respectively to obtain structural information of the slab model with a stable configuration and structural information of the grain boundary model with a stable configuration, and then performing visualization to obtain the slab model with a stable configuration and the grain boundary model with a stable configuration;

[0011] 5) Based on the structural information of the slab model of the stable configuration, the adsorption model of impurity atoms or molecules and the defect model with point defects and defect clusters are established;

[0012] 6) performing first principle relaxation calculation on the adsorption model and the defect model to obtain structural information of the adsorption model with a stable configuration and the defect model with a stable configuration; and then performing visualization to obtain the adsorption model with a stable configuration and the defect model with a stable configuration;

[0013] 7) Based on the structural information of the slab model of the stable configuration, the grain boundary model of the stable configuration, the adsorption model of the stable configuration and the defect model of the stable configuration, the first-principles electronic property calculation is performed to obtain the corresponding work function, thereby realizing the detection of the Patch effect on the target metal surface.

[0014] The present invention also provides a system for implementing the above-mentioned metal surface patch effect detection method based on first principles, comprising:

[0015] A unit cell crystal structure acquisition module, used to acquire the actual unit cell crystal structure of the metal surface of the target metal;

[0016] A data file acquisition module is used to acquire a unit cell crystal structure data file corresponding to the actual unit cell crystal structure from a material database;

[0017] A slab model building module, used to build a slab model of a target crystal surface based on a primitive cell crystal structure data file of the target metal;

[0018] A slab model relaxation module is used to perform first principle relaxation calculation on the slab model to obtain structural information of the slab model with a stable configuration;

[0019] A grain boundary model building module is used to build a grain boundary model of a target crystal plane based on a primitive cell crystal structure data file of the target metal;

[0020] A grain boundary model relaxation module performs a first principle relaxation calculation on the grain boundary model to obtain structural information of the grain boundary model of a stable configuration;

[0021] An adsorption model building module is used to visualize the structural information of the stable slab model; based on the slab model structure file of the stable configuration, an adsorption model of adsorbed impurity atoms or molecules on the target crystal surface is established;

[0022] An adsorption model relaxation module, used to perform first-principles relaxation calculations on the adsorption models to obtain structural information of the adsorption models with stable configurations;

[0023] A defect model building module is used to visualize the structural information of the slab model of the stable configuration; based on the slab model structure file of the stable configuration, establish a defect model of the target crystal surface;

[0024] A defect model relaxation module performs first principle relaxation calculation on the defect model to obtain structural information of the defect model with a stable configuration;

[0025] The electronic property module is used to perform first-principles electronic property calculations based on the slab model structure information of the stable configuration, the grain boundary model structure information of the stable configuration, the adsorption model structure information of the stable configuration and the defect model structure information of the stable configuration, so as to obtain the work function of the slab model of the stable configuration, the grain boundary model of the stable configuration, the adsorption model of the stable configuration and the defect model of the stable configuration; thereby detecting the Patch effect on the target metal surface.

[0026] Compared with the prior art, the present invention has the following beneficial effects:

[0027] The present invention studies the influence of metal crystal anisotropy, grain boundaries, surface impurity adsorption, defects and other factors on the work function through model calculation, establishes a grain boundary model of the target crystal plane to obtain the influence of the existence of the grain boundary on the work function; finally, an adsorption model and a defect model are established based on the slab structure model of the stable configuration, and the work function change is obtained after the structure is optimized. The present invention makes full use of the powerful theoretical calculation and simulation capabilities of the high-performance computing platform, reduces the high operating costs brought by experimental equipment and experimental materials, and the process is simple to operate, and can detect the metal surface potential, that is, the root cause of the Patch effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 This is a schematic diagram of obtaining the unit cell crystal structure of Au from the Materials Project open source material database according to the first embodiment of the present invention;

[0029] Figure 2 : is a side view of the Au(100) surface slab model of a stable configuration in Example 1 of the present invention and a corresponding work function diagram; wherein, Figure 2 (a) is a side view of the slab model of the Au(100) crystal plane with a stable configuration; Figure 2(b) is the work function diagram of the Au(100) crystal plane slab model;

[0030] Figure 3 1 is a comparison diagram of the work functions of the three crystal planes Au(100), Au(110), and Au(111) of the stable configuration in Example 1 of the present invention;

[0031] Figure 4 is the work function of the Au(100) surface grain boundary model of the stable configuration of the second embodiment of the present invention; wherein, Figure 4 (a) is the grain boundary model structure of Au(100) surface. Figure 4 (b) corresponds to the work function of the grain boundary model structure of the Au(100) surface;

[0032] Figure 5 This is a side view of a slab adsorption model of an Au(100) surface with a stable configuration for adsorbing impurity atoms or molecules according to the third embodiment of the present invention; wherein, Figure 5 (a) is a top view of the adsorption model of H adsorbed on the Au(100) surface, and 5(b) is a top view of the adsorption model of -OH adsorbed on the Au(100) surface;

[0033] Figure 6 This is a comparison diagram of the work functions of the adsorption model of impurity atoms or molecules adsorbed on the Au (100) surface in a stable configuration according to Example 3 of the present invention;

[0034] Figure 7 7(a) is a differential charge density diagram of the adsorption model of impurity atoms or molecules adsorbed on the Au(100) surface in a stable configuration according to the third embodiment of the present invention; wherein, 7(a) is a differential charge density diagram of H adsorbed on the Au(100) surface, and 7(b) is a differential charge density diagram of -OH adsorbed on the Au(100) surface;

[0035] Figure 8 It is a stereoscopic diagram of a defect model of a Au(100) crystal plane with point defects and defect clusters in a stable configuration in the fourth embodiment of the present invention; wherein, Figure 8 (a) is a stereogram of a slab model with a point defect on the Au(100) crystal surface, and (b) is a stereogram of a slab model with a defect cluster on the Au(100) crystal surface.

[0036] Fig. 9 This is a comparison diagram of the defect model work functions of the Au(100) crystal plane with a stable configuration and a point defect and a defect cluster in Example 4 of the present invention;

[0037] Fig.10 It is an intuitive diagram of the electron density distribution after the formation of point defects and defect clusters on the Au (100) surface; among them, 10 (a) is the electron distribution diagram of the point defects formed on the Au (100) surface, and 10 (b) is the electron distribution diagram of the defect clusters formed on the Au (100) surface. DETAILED DESCRIPTION

[0038] The present invention is further described and illustrated below in conjunction with specific embodiments. The embodiments are merely exemplary of the present disclosure and do not define the scope of limitation. The technical features of each embodiment of the present invention may be combined accordingly without conflicting with each other.

[0039] The present invention first provides a metal surface patch effect detection method based on the first principle, which comprises the following steps:

[0040] 1) obtaining the actual unit cell crystal structure of the target metal surface; the method for obtaining the actual unit cell crystal structure of the target metal surface can adopt X-ray diffraction analysis (XRD) or vacuum surface analysis;

[0041] 2) Obtaining the unit cell crystal structure data file of the target metal from the material database;

[0042] 3) cutting a target crystal plane based on the primitive cell crystal structure data file of the target metal, and adding a vacuum layer to the cut target crystal plane to isolate the influence between periodic atoms, thereby establishing a slab model and a grain boundary model;

[0043] 4) performing first principle relaxation calculations on the slab model and the grain boundary model respectively to obtain structural information of the slab model with a stable configuration and structural information of the grain boundary model with a stable configuration;

[0044] 5) Based on the structural information of the stable slab model, an adsorption model of impurity atoms or molecules and a defect model with point defects and defect clusters are established;

[0045] 6) performing first principle relaxation calculations on the adsorption model and the defect model to obtain structural information of the adsorption model and the defect model of a stable configuration;

[0046] 7) Based on the slab model, grain boundary model, adsorption model and defect model structural information of the stable configuration, first-principles electronic property calculations are performed to obtain the corresponding work function, thereby completing the detection of the Patch effect on the target metal surface.

[0047] Among them, the work function is the minimum energy required for a solid to move an electron from the inside of the solid to the outside of the solid surface, which can reflect the ability of the solid to release electrons. When the distribution of electrons on the surface of the solid changes due to external influences, the work function will change, and then the surface potential will change. Therefore, the surface patch effect can be obtained by obtaining the work function. The actual unit cell crystal structure of the target metal surface can be obtained by X-ray diffraction, neutron diffraction, electron microscopy, thermodynamics, nuclear magnetic resonance or Raman scattering.

[0048] Embodiment 1

[0049] In the embodiment of the present invention, the work function of the Au(100) slab model structure on the surface of the Au-plated metal block of the main load of the inertial sensor is calculated based on the first principle, including:

[0050] Obtain the actual unit cell crystal structure of Au(100) on the surface of Au metal block;

[0051] A data file of a unit cell crystal structure corresponding to the actual unit cell crystal structure is obtained from the material database; specifically, a .cif file of the unit cell crystal structure of Au is obtained using the Materials Project open source material database, which can provide parameters such as the lattice shape, lattice constant, and atomic coordinates of the material.

[0052] The slab model of Au(100) was established using Material studio software. Specifically, the following steps were used: using Material studio software to cut the Au(100) crystal surface; A slab model is established by isolating the influence between periodic atoms with a vacuum layer; based on the established slab model, a first pseudopotential file matching the density functional calculation tool is obtained; with the help of the three-dimensional visualization system for electronic and structural analysis (VESTA), the .cif file format of the obtained unit cell crystal structure data of different crystal systems is converted into the .vasp file format of the density functional calculation software. The first pseudopotential file is analyzed based on the preset density functional calculation tool, and the PBE functional of the generalized gradient approximation (GGA) is used to describe the exchange interaction between electrons, and the maximum plane wave cutoff energy information of Au is obtained;

[0053] The slab model is set to have a truncation energy based on the maximum plane wave truncation energy information to obtain a slab model with a stable configuration. Specifically, the maximum plane wave truncation energy of Au is set to 450 eV.

[0054] The slab model structure is subjected to first principle relaxation calculation to obtain the slab model structure information of a stable configuration; the slab model structure information of a stable configuration includes lattice parameters and atomic coordinates.

[0055] When performing first-principles relaxation calculations, you need to input parameter setting files (INCAR), crystal inverted vector lattice files (KPOINTS), slab model structure files (POSCAR) and pseudopotential files (POTCAR). After the relaxation calculation is completed, the CONTCAR file will be output, which contains the slab model structure information of the stable configuration.

[0056] When performing first-principles relaxation calculations on the slab model structure, the top three layers of atoms are allowed to relax until the residual force is less than The maximum plane wave cutoff energy is set to 450eV. It should be noted that the basis for setting the cutoff energy is ENCUT ≥ ENMAX. Too large a cutoff energy may slow down the convergence speed but does not effectively improve the calculation accuracy, thereby increasing the calculation time and cost. Too small a cutoff energy may cause the calculation accuracy of the system to decrease, affecting the calculation results of the structural optimization of the Au (100) crystal plane slab. The Au (100) slab model structure of the stable configuration is visualized to obtain the Au (100) slab model structure of the stable configuration;

[0057] Based on the stable slab model structure, first principle electronic property calculations are performed to obtain the work function of the slab model structure with a stable configuration.

[0058] It should be noted that in order to facilitate the subsequent study of the influence of impurity atoms or molecules adsorbed on the Au crystal surface on the work function, the top view of the established slab model is 5×5. This is to avoid the interaction between impurity atoms or molecules and their periodic mirror images, which may lead to non-convergence or calculation errors.

[0059] like Figure 1 As shown, the unit cell crystal structure of Au is obtained from the open source material database Materials Project. The space group of Au is Fm3m, and the lattice constant is: α=β=γ=90°.

[0060] like Figure 2 , which is a side view of the Au(100) surface slab model of a stable configuration and a corresponding work function diagram in Example 1 of the present invention; wherein, Figure 2 (a) is a side view of the slab model of the Au(100) crystal plane with a stable configuration. Figure 2 (b) is the work function diagram of the Au(100) crystal plane slab model.

[0061] Figure 3 This is a comparison chart of the work functions of the three crystal planes Au(100), Au(110), and Au(111). Figure 3 It is known that the work function of Au exhibits significant crystal plane anisotropy, Au(111)>Au(100)>Au(110).

[0062] The surface potential change caused by crystal plane anisotropy can be obtained through the calculation in Example 1.

[0063] Embodiment 2

[0064] This example demonstrates the method for constructing a grain boundary model based on first-principles calculations of the present invention, including:

[0065] The .cif file of the unit cell crystal structure of bulk Au was obtained using the open source materials database (Materials Project), which can provide Au lattice shape, lattice constants and atomic coordinates.

[0066] The grain boundary model structure of Au(100) crystal plane was established using atmosk software.

[0067] With the help of VESTA (Three-Dimensional Visualization System for Electronic and Structural Analysis), the .cif file of the grain boundary model structure of the Au(100) crystal plane was converted into the file format of density functional calculation software (vasp).

[0068] According to the maximum plane wave cutoff energy information of the Au element in the pseudopotential file (POTCAR), the cutoff energy is set; the first-principles structural relaxation calculation is performed on the Au grain boundary model structure to obtain the energy and structurally stable Au grain boundary model structure information, including lattice parameters and atomic coordinates; the structural relaxation calculation file includes the parameter setting file (INCAR), the crystal structure file (POSCAR), the pseudopotential file (POTCAR) and the crystal inverse lattice file (KPOINTS); in the crystal structure relaxation calculation, the output file CONTCAR is the Au (100) grain boundary model structure file obtained after relaxation.

[0069] First-principles electronic property calculations were performed based on the stable Au(100) crystal plane grain boundary model structure, and the work function of the grain boundary model structure with a stable configuration was obtained.

[0070] Figure 4 This is the grain boundary model structure of the Au (100) crystal plane with a stable configuration in Example 2 of the present invention, wherein the red frame is the grain boundary. Figure 4 (a) is the grain boundary model structure of Au(100) surface. Figure 4 (b) is the work function of the grain boundary model structure of the Au (100) surface, which indicates that there is a mutation in the electrostatic potential at the grain boundary of the Au film, which affects the electrostatic potential on the surface.

[0071] Through the calculation in Example 2, the change of surface potential in the presence of grain boundaries can be obtained. The presence of grain boundaries will lead to changes in surface potential.

[0072] Embodiment 3

[0073] This example is based on Example 1, and further establishes a slab structure adsorption model, including:

[0074] The slab model structure of the Au(100) crystal surface after structural relaxation in Example 1 is visualized by Material Studio software to obtain the slab model structure information; the adsorbed impurity atoms or molecules are built on the slab model of the Au(100) crystal surface. The impurity molecules here are H and -OH.

[0075] The adsorption model structure information of slab adsorbed impurity atoms or molecules is converted into .cif file format using Material Studio software.

[0076] Use VESTA software to convert the .cif file of the adsorption model structure of slab adsorbed impurity atoms or molecules into the .vasp file format.

[0077] According to the maximum plane wave cutoff energy information of element Au, the cutoff energy is set; first-principles structural relaxation calculations are performed on different structures to obtain the energy and structurally stable adsorption model structure information, including lattice parameters and atomic coordinates; the structural relaxation calculation files include parameter setting files (INCAR), crystal structure files (POSCAR), pseudopotential files (POTCAR) and crystal inverse lattice files (KPOINTS); in the crystal structure relaxation calculation, the output file CONTCAR is the calculated stable adsorption model structure file after relaxation.

[0078] Based on the stable adsorption model structure, first principle electronic property calculations are performed to obtain the work function of the stable adsorption model structure.

[0079] Based on the stable adsorption model structure, first-principles charge density calculation is performed to specify the electron transfer on the adsorption model surface, and the differential charge density is calculated.

[0080] The stability of the Au surface and the adsorption stability are obtained by calculating the adsorption energy of impurity atoms or molecules adsorbed on the surface. Figure 5 Top view of the slab adsorption model of impurity atoms or molecules adsorbed on the Au(100) surface with a stable configuration. Figure 5 (a) and Figure 5(b) The top view of the slab adsorption model of H and -OH adsorbed on the Au(100) surface, respectively. Both H and -OH can be stably adsorbed on the Au(100) surface.

[0081] Figure 6 The work function comparison diagram of the slab adsorption model of H and -OH adsorbed on the Au (100) surface. Figure 6 It is concluded that the adsorption of impurity atoms or molecules will change the work function of the surface.

[0082] Figure 7 The differential charge density diagram of the slab adsorption model of H,-OH adsorbed on the Au(100) surface with a stable configuration. Figure 7 (a) and Figure 7 (b) The differential charge density diagram of Au(100) surface adsorbing H and -OH. The cyan area in the differential charge density diagram indicates the loss of electrons, and the yellow area indicates the gain of electrons. The figure shows that after the Au(100) surface adsorbs H and -OH, due to the electronegativity of H and O, electrons flow from Au to impurity atoms or molecules, which leads to a change in the surface work function.

[0083] The change in surface potential in the presence of surface adsorbed impurity atoms or molecules can be obtained through the calculation in Example 3.

[0084] Embodiment 4

[0085] This example is based on the first embodiment and establishes a defect structure model, including:

[0086] The slab model structure of Au(100) after structural relaxation in Example 1 is visualized by using Material Studio software to obtain the slab model structure information; an Au atom is removed from the surface of the Au(100) slab model to simulate the point defect model of the Au surface, and multiple continuous adjacent atoms are removed to simulate defect clusters;

[0087] The structural information of the two defect models of Au(100) was converted into .cif file format using Material Studio software.

[0088] The .cif files of the two defect model structures of Au(100) were converted into vasp file formats respectively using VESTA software.

[0089] According to the plane wave cutoff energy information in the Au element in the pseudopotential file (POTCAR), the cutoff energy is set; the first principle structural relaxation calculation is performed on the Au defect model structure to obtain the structurally stable Au(100) defect model structure information, including lattice parameters and atomic coordinates; the structural relaxation calculation file includes the parameter setting file (INCAR), the crystal structure file (POSCAR), the pseudopotential file (POTCAR) and the crystal inverse lattice file (KPOINTS); in the crystal structure relaxation calculation, the output file CONTCAR is the Au(100) defect model structure file after relaxation obtained by calculation.

[0090] Based on the stable defect model structure, first principle electronic property calculations are performed to obtain the work function of the stable defect model structure.

[0091] Based on the stable defect model structure, a first-principles electron density distribution calculation is performed to obtain the electron density distribution on the surface of the stable defect model structure.

[0092] Figure 8 This is a three-dimensional diagram of the defect structure model of the Au(100) crystal plane. Figure 8 (a) and Figure 8 (b) Stereoscopic images of the slab model representing the Au(100) crystal surface with point defects and defect clusters, respectively.

[0093] Fig. 9 The work function comparison diagram of Au(100) crystal surface with point defects and defect clusters is shown in Figure 2. Fig. 9 The comparison in Figure 2 shows that when the Au surface has defects, the work function of the surface will be reduced.

[0094] Fig.10 It is the electron density distribution at the Fermi level after the formation of point defects and defect clusters. Fig.10 (a) and Fig.10 (b) The electron distribution diagrams of point defects and defect clusters formed on the Au(100) surface, respectively. The figure shows that the presence of vacancies changes the local electronic state, resulting in electron redistribution in these areas. High potentials are caused near the vacancies and low potentials are caused around the vacancies, resulting in surface potential fluctuations and increased electronic noise. On the Au(100) surface, the contribution of a single vacancy to the potential distribution inhomogeneity is relatively small. However, the formation of defect clusters causes electrons to accumulate on atoms near the defect clusters, resulting in a decrease in the potential near the vacancies.

[0095] The change of surface potential in the presence of surface defects can be obtained through the calculation of Example 4.

[0096] Based on the same inventive concept, a system for implementing the above-mentioned metal surface patch effect detection method based on first principles is also provided in this embodiment, including:

[0097] A unit cell crystal structure acquisition module is used to obtain the actual unit cell crystal structure of the target metal surface;

[0098] A data file acquisition module is used to acquire a unit cell crystal structure data file corresponding to the actual unit cell crystal structure from a material database;

[0099] A slab model building module, used to build a slab model of a target crystal surface based on a primitive cell crystal structure data file of the target metal;

[0100] A slab model relaxation module is used to perform first principle relaxation calculation on the slab model to obtain structural information of the slab model with a stable configuration;

[0101] A grain boundary model building module is used to build a grain boundary model of a target crystal plane based on a primitive cell crystal structure data file of the target metal;

[0102] A grain boundary model relaxation module performs a first principle relaxation calculation on the grain boundary model to obtain structural information of the grain boundary model of a stable configuration;

[0103] An adsorption model building module is used to visualize the structural information of the stable slab model; based on the slab model structure file of the stable configuration, an adsorption model of adsorbed impurity atoms or molecules on the target crystal surface is established;

[0104] An adsorption model relaxation module, used to perform first-principles relaxation calculations on the adsorption models to obtain structural information of the adsorption models with stable configurations;

[0105] A defect model building module is used to visualize the structural information of the slab model of the stable configuration; based on the slab model structure file of the stable configuration, establish a defect model of the target crystal surface;

[0106] A defect model relaxation module performs first principle relaxation calculation on the defect model to obtain structural information of the defect model with a stable configuration;

[0107] The electronic property module is used to perform first-principles electronic property calculations based on the slab model structure information of the stable configuration, the grain boundary model structure information of the stable configuration, the adsorption model structure information of the stable configuration and the defect model structure information of the stable configuration, so as to obtain the work function of the slab model of the stable configuration, the grain boundary model of the stable configuration, the adsorption model of the stable configuration and the defect model of the stable configuration; thereby detecting the Patch effect on the surface of the metal block of the main load of the inertial sensor.

[0108] For the system embodiment, since it basically corresponds to the method embodiment, the relevant parts can refer to the partial description of the method embodiment, and the implementation methods of the remaining modules will not be repeated here. The system embodiment described above is only schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of the present invention. Ordinary technicians in this field can understand and implement it without paying creative work.

[0109] The above-mentioned embodiments only express several implementation methods of the present invention, and the description is relatively specific and detailed, but it cannot be understood as limiting the scope of the present invention. For ordinary technicians in this field, several modifications and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention.

Claims

1. A metal surface patch effect detection method based on first principles; characterized in that: The following steps are involved: 1) Obtain the actual unit cell crystal structure of the target metal surface; 2) Obtaining a unit cell crystal structure data file corresponding to the actual unit cell crystal structure from a material database; 3) cutting a target crystal plane based on the primitive cell crystal structure data file, and constructing a grain boundary model of the target crystal plane based on the cut target crystal plane and a slab model with a vacuum layer; 4) performing first principle relaxation calculations on the slab model and the grain boundary model respectively to obtain structural information of the slab model with a stable configuration and structural information of the grain boundary model with a stable configuration, and then performing visualization to obtain the slab model with a stable configuration and the grain boundary model with a stable configuration; 5) Based on the structural information of the slab model of the stable configuration, the adsorption model of impurity atoms or molecules and the defect model with point defects and defect clusters are established; 6) performing first principle relaxation calculation on the adsorption model and the defect model to obtain structural information of the adsorption model with a stable configuration and the defect model with a stable configuration; and then performing visualization to obtain the adsorption model with a stable configuration and the defect model with a stable configuration; 7) Based on the structural information of the slab model of the stable configuration, the grain boundary model of the stable configuration, the adsorption model of the stable configuration and the defect model of the stable configuration, the first-principles electronic property calculation is performed to obtain the corresponding work function, thereby realizing the detection of the Patch effect on the target metal surface.

2. The metal surface patch effect detection method according to claim 1, characterized in that: The slab model is subjected to first principle relaxation calculation to obtain the slab model structure information of the stable configuration, including: Performing format conversion on the structural data file of the metal primitive cell to obtain a first pseudopotential file that matches a preset density functional calculation tool; The first pseudopotential file is analyzed based on a preset density functional calculation tool to obtain the maximum plane wave cutoff energy information of the metal element in the slab model structure; The slab model structure is subjected to truncation energy setting for the maximum plane wave truncation energy information to obtain slab structure information of a stable configuration.

3. The metal surface patch effect detection method according to claim 1, characterized in that: The grain boundary model is subjected to first principle relaxation calculation to obtain structural information of the grain boundary model of a stable configuration, including: Converting the data file of the grain boundary model structure into a format to obtain a second pseudopotential file that matches a preset density functional calculation tool; The second pseudopotential file is analyzed based on a preset density functional calculation tool to obtain the maximum plane wave cutoff energy information of each element in the grain boundary model structure; The grain boundary model structure is truncated based on the maximum plane wave truncation energy information to obtain grain boundary model structure information of a stable configuration.

4. The metal surface patch effect detection method according to claim 1, characterized in that: Based on the slab model structure file of the stable configuration, an adsorption model with impurity atoms or molecules is established. Specifically, the slab model structure file of the stable configuration is visualized, and the adsorbed impurity atoms or molecules are set above the visualized slab model. At this point, an adsorption model with impurity atoms or molecules is obtained, wherein the impurity atoms or molecules include H, -OH, O, and O2.

5. The metal surface patch effect detection method according to claim 1, characterized in that: Based on the slab model structure file of the stable configuration, a defect model with point defects and defect clusters is established as follows: the slab model structure file of the stable configuration is visualized, a metal atom is removed from the surface of the visualized slab model to simulate the point defects on the metal surface, and multiple continuous adjacent metal atoms are removed to simulate the defect clusters, thereby obtaining a defect model with point defects and defect clusters.

6. The metal surface patch effect detection method according to claim 1, characterized in that: Step 5) shown includes the following sub-steps: Converting the formats of the data files of the adsorption model structure and the defect model structure respectively to obtain a third pseudopotential file and a fourth pseudopotential file that match a preset density functional calculation tool; The third pseudopotential file and the fourth pseudopotential file are analyzed based on a preset density functional calculation tool to obtain the maximum plane wave cutoff energy information of each element in the adsorption model structure and the defect model structure respectively; The adsorption model and defect model structure are truncated based on the maximum plane wave truncation energy information to obtain the adsorption model and defect model structure information of a stable configuration.

7. According to the metal surface patch effect detection method, adsorption model and defect model construction method of claim 1, it is characterized in that: When performing first-principles relaxation calculations on the slab model, adsorption model, and defect model, the density functional used is the PBE hybrid density functional, which allows relaxation of the three-layer atoms and adsorbed atoms on the surface, and the specific energy convergence value is 1×10 -5 eV, when the maximum interatomic force is less than End of structural optimization.

8. The metal surface patch effect detection method according to any one of claims 2 to 5, characterized in that: The maximum plane wave cutoff energy is set to 400-500 eV.

9. The metal surface patch effect detection method according to claim 1, characterized in that: The thickness of the vacuum layer of the slab model is When establishing the adsorption model, the adsorbed atoms or molecules are established directly above the slab model of the target metal. Place.

10. A system for implementing the metal surface patch effect detection method based on first principles as claimed in claim 1, characterized in that: include: A unit cell crystal structure acquisition module is used to obtain the actual unit cell crystal structure of the target metal surface; A data file acquisition module is used to acquire a unit cell crystal structure data file corresponding to the actual unit cell crystal structure from a material database; A slab model building module, used to build a slab model of a target crystal surface based on a primitive cell crystal structure data file of the target metal; A slab model relaxation module is used to perform first principle relaxation calculation on the slab model to obtain structural information of the slab model with a stable configuration; A grain boundary model building module is used to build a grain boundary model of a target crystal plane based on a primitive cell crystal structure data file of the target metal; A grain boundary model relaxation module performs a first principle relaxation calculation on the grain boundary model to obtain structural information of the grain boundary model of a stable configuration; An adsorption model building module is used to visualize the structural information of the stable slab model; based on the slab model structure file of the stable configuration, an adsorption model of adsorbed impurity atoms or molecules on the target crystal surface is established; An adsorption model relaxation module is used to perform first-principles relaxation calculations on the adsorption models to obtain structural information of the adsorption models with stable configurations; A defect model building module is used to visualize the structural information of the slab model of the stable configuration; based on the slab model structure file of the stable configuration, establish a defect model of the target crystal surface; A defect model relaxation module performs a first principle relaxation calculation on the defect model to obtain structural information of the defect model with a stable configuration; The electronic property module is used to perform first-principles electronic property calculations based on the slab model structure information of the stable configuration, the grain boundary model structure information of the stable configuration, the adsorption model structure information of the stable configuration and the defect model structure information of the stable configuration, so as to obtain the work function of the slab model of the stable configuration, the grain boundary model of the stable configuration, the adsorption model of the stable configuration and the defect model of the stable configuration; thereby detecting the Patch effect on the target metal surface.

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