Method and device for determining surface finish analysis results, equipment, medium and product

Abstract

This invention provides a method, apparatus, device, medium, and product for determining surface polishing analysis results, relating to the field of simulation technology. The method includes: acquiring initial morphological parameters corresponding to measurement points of the workpiece to be polished; generating a self-affine rough surface based on all initial morphological parameters corresponding to all measurement points; constructing a molecular dynamics model based on the self-affine rough surface; performing simulated polishing based on the molecular dynamics model and a simulator to obtain target morphological parameters; and analyzing the polishing condition of the workpiece to be polished based on the target morphological parameters to determine the surface polishing analysis results. The technical solution of this invention constructs a molecular dynamics model based on initial morphological parameters from multiple measurement points, obtains target morphological parameters through simulated polishing, and finally analyzes the polishing condition of the workpiece to be polished based on the target morphological parameters, thereby achieving an evaluation of the surface morphological changes of the workpiece to be polished during polishing simulation based on the surface polishing analysis results.

Description

Technical Field

[0001] This invention relates to the field of simulation technology, and in particular to a method, apparatus, equipment, medium, and product for determining surface polishing analysis results. Background Technology

[0002] Even sub-nanometer variations in wafer surface roughness can significantly alter the electrical transport behavior, quantum effect interference, and thermal conduction of materials, ultimately leading to performance degradation and shortened lifespan of chip devices. Therefore, achieving sub-nanometer-level ultra-smooth surface polishing technology has become a key bottleneck in chip manufacturing. Furthermore, the relentless pursuit of feature size miniaturization and 3D integration in advanced processes is pushing the surface roughness threshold to atomic-level precision, making ultra-smooth surface polishing technology a crucial process in chip manufacturing.

[0003] Currently, existing molecular dynamics simulations of abrasive machining generally use single abrasive grains for surface polishing analysis, neglecting the fact that actual polishing involves the combined action of a group of abrasive grains and ignoring the cooperative / competitive mechanisms among these grains (such as stress field superposition and debris clogging). Furthermore, the abrasive grains in the simulation are often set to move at a constant depth, failing to reflect the parameter settings in real polishing, and even less so the dynamic changes in penetration depth caused by multi-directional loads and workpiece surface topological undulations. Moreover, only changes in crystal damage are investigated, neglecting core surface morphology parameters (roughness, etc.) and failing to evaluate changes in workpiece surface morphology.

[0004] Therefore, there is an urgent need for a method to determine the results of surface polishing analysis, enabling the evaluation of surface morphology changes in the workpiece under polishing simulation based on these results. This would allow for a deeper understanding of the microscopic material behavior mechanisms during polishing and provide guidance for process optimization. Summary of the Invention

[0005] This invention provides a method, apparatus, equipment, medium, and product for determining surface polishing analysis results. It addresses the shortcomings of existing technologies that only use single abrasive grains for simulation, neglecting the combined effect of abrasive grain groups to achieve surface processing, and only exploring the influence of abrasive grains on crystal structure without evaluating changes in workpiece surface morphology. The invention constructs a molecular dynamics model based on initial morphology parameters from multiple measurement points, obtains target morphology parameters through polishing simulation, and finally analyzes the polishing status of the workpiece based on these target morphology parameters to determine the surface polishing analysis results. This enables the evaluation of surface morphology changes in the workpiece during polishing simulation based on the surface polishing analysis results.

[0006] This invention provides a method for determining the results of surface polishing analysis, comprising the following steps.

[0007] Obtain the initial morphological parameters corresponding to the measurement points of the workpiece to be polished; wherein, there are at least two measurement points.

[0008] A self-affine rough surface is generated based on all initial topographic parameters corresponding to all measurement points.

[0009] A molecular dynamics model is constructed based on the self-affine rough surface; the molecular dynamics model is used to simulate and analyze the polishing of the workpiece to be polished.

[0010] Polishing was simulated using molecular dynamics models and simulators to obtain the target morphology parameters.

[0011] The polishing condition of the workpiece to be polished is analyzed based on the target morphology parameters to determine the surface polishing analysis results.

[0012] According to a method for determining the surface polishing analysis results provided by the present invention, a self-affine rough surface is generated based on all initial morphology parameters corresponding to all measurement points, including: reconstructing each initial morphology parameter to obtain the surface height of the workpiece to be polished corresponding to each measurement point; and generating a self-affine rough surface based on all surface heights.

[0013] According to the method for determining surface polishing analysis results provided by the present invention, the initial morphology parameters include a first morphology parameter, a second morphology parameter, and a third morphology parameter, wherein the first morphology parameter is... The parameters of the shaft, the second morphology parameter is The parameters of the axis are defined, and the third morphological parameter is the parameter of the Z-axis. Each initial morphological parameter is reconstructed to obtain the surface height of the workpiece to be polished corresponding to each measurement point, including: reconstructing each initial morphological parameter to obtain the root mean square height value, root mean square slope, and fractal dimension corresponding to each initial morphological parameter; where the root mean square height value... root mean square slope , This indicates the total number of measurement points. This represents the third morphological parameter. Indicates the first morphological parameter. The second morphological parameter is represented; all Hearst exponents are determined based on each fractal dimension and a preset threshold; where, the Hearst exponent... , Indicates the preset threshold. The fractal dimension is represented; the surface height of the workpiece to be polished corresponding to each measurement point is determined based on each root mean square height value, each root mean square slope, and each Hearst exponent.

[0014] According to a method for determining surface polishing analysis results provided by the present invention, a molecular dynamics model is constructed based on a self-affine rough surface, comprising: constructing an initial ideal crystal bulk supercell; wherein the initial ideal crystal bulk supercell is a model constructed based on workpieces with the same workpiece attribute information as the workpiece to be polished; generating a target atomic model based on the initial ideal crystal bulk supercell and the self-affine rough surface; wherein the target atomic model is an atomic model with self-affine fractal surface characteristics; and constructing a molecular dynamics model in a simulator by setting model parameters based on the target atomic model; wherein the model parameters include the model Hurst exponent.

[0015] According to the method for determining the surface polishing analysis results provided by the present invention, after setting the model parameters based on the target atomic model and constructing the molecular dynamics model in the simulator, the method further includes: determining whether the model Hurst exponent is the same as all Hurst exponents; if the model Hurst exponent is not the same as all Hurst exponents, determining the surface height of the workpiece to be polished corresponding to each measurement point based on each root mean square height value, each root mean square slope and the model Hurst exponent; if the model Hurst exponent is the same as all Hurst exponents, continuing to perform the step of simulating polishing based on the molecular dynamics model and the simulator to obtain the target morphology parameters.

[0016] According to the present invention, a method for determining the surface polishing analysis result is provided, which analyzes the polishing condition of the workpiece to be polished based on the target morphology parameters to determine the surface polishing analysis result. The method includes: analyzing and processing the target morphology parameters to obtain analysis and processing parameters; and analyzing the polishing condition of the workpiece to be polished based on the analysis and processing parameters to determine the surface polishing analysis result.

[0017] The present invention also provides a device for determining the results of surface polishing analysis, comprising the following modules.

[0018] The parameter acquisition module is used to acquire the initial morphological parameters corresponding to the measurement points of the workpiece to be polished; wherein, there are at least two measurement points.

[0019] The surface generation module is used to generate a self-affine rough surface based on all initial morphology parameters corresponding to all measurement points.

[0020] The model building module is used to construct a molecular dynamics model based on the self-affine rough surface; the molecular dynamics model is used to simulate and analyze the polishing of the workpiece to be polished.

[0021] The simulated polishing module is used to perform simulated polishing based on molecular dynamics models and simulators to obtain the target morphology parameters.

[0022] The result determination module is used to analyze the polishing condition of the workpiece to be polished based on the target morphology parameters and determine the surface polishing analysis results.

[0023] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement any of the methods described above for determining surface polishing analysis results.

[0024] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a method for determining the surface polishing analysis results as described above.

[0025] The present invention also provides a computer program product, including a computer program, which, when executed by a processor, implements a method for determining any of the surface polishing analysis results described above.

[0026] This invention provides a method, apparatus, device, medium, and product for determining surface polishing analysis results. The method involves acquiring initial morphological parameters corresponding to measurement points on a workpiece to be polished; wherein there are at least two measurement points; generating a self-affine rough surface based on all initial morphological parameters corresponding to all measurement points; constructing a molecular dynamics model based on the self-affine rough surface; wherein the molecular dynamics model is used for simulating polishing analysis of the workpiece to be polished; performing simulated polishing based on the molecular dynamics model and the simulator to obtain target morphological parameters; and analyzing the polishing condition of the workpiece to be polished based on the target morphological parameters to determine the surface polishing analysis results. The technical solution of this invention addresses the shortcomings of existing technologies that use single abrasive grains for simulation, neglecting the combined effect of abrasive grain groups to achieve surface processing, and only exploring the influence of abrasive grains on crystal structure without evaluating changes in workpiece surface morphology. This invention achieves the construction of a molecular dynamics model based on initial morphology parameters of surface morphologies with different statistical characteristics, obtaining target morphology parameters through simulated polishing, and finally analyzing the polishing status of the workpiece to be polished based on the target morphology parameters to determine the surface polishing analysis results. This enables the evaluation of surface morphology changes in the workpiece to be polished during polishing simulation based on the surface polishing analysis results. Attached Figure Description

[0027] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0028] Figure 1 This is a flowchart illustrating the method for determining the surface polishing analysis results provided by the present invention.

[0029] Figure 2This is a schematic diagram of the relevant parameters for power spectrum calculation provided by the present invention.

[0030] Figure 3 This is a schematic diagram of the self-affine rough surface provided by the present invention.

[0031] Figure 4 This is a schematic diagram of the target atom model provided by the present invention.

[0032] Figure 5 This is a schematic diagram of the molecular dynamics model provided by the present invention.

[0033] Figure 6 This is a schematic diagram of an atomic model of surface morphology with different statistical characteristics provided by the present invention.

[0034] Figure 7 This is a schematic diagram of different abrasive concentration settings provided by the present invention.

[0035] Figure 8 This is a schematic diagram of the evolution of polished surface morphology provided by the present invention.

[0036] Figure 9 This is a schematic diagram of the structure of the device for determining the surface polishing analysis results provided by the present invention.

[0037] Figure 10 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0038] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0039] The following is combined Figure 1 The method for determining the surface polishing analysis results provided by this invention is described below. This method is applicable to atomic-scale mechanism studies of ultra-precision polishing processes, specifically for the ultra-smooth surface polishing analysis of workpieces to be polished. The execution subject of this method can be an electronic device or a device for determining the surface polishing analysis results installed in the electronic device. The device for determining the surface polishing analysis results can be implemented by software, hardware, or a combination of both. Figure 1 This is a flowchart illustrating the method for determining surface polishing analysis results provided by the present invention, as shown below. Figure 1 As shown, the method includes the following steps 101, 102, 103, 104 and 105.

[0040] Step 101: Obtain the initial morphological parameters corresponding to the measurement points of the workpiece to be polished.

[0041] In this step, at least two measurement points are used. The workpiece to be polished can be, for example, monocrystalline silicon; this embodiment does not limit this.

[0042] Specifically, for a workpiece to be polished, initial topographic data corresponding to the measurement points of the workpiece are obtained using a topographic measurement tool. Such tools can be, for example, a non-contact white light interferometer, a contact atomic force microscope, and other commonly used measuring tools. When obtaining initial topographic data using a non-contact white light interferometer, an image is formed on the light-receiving element by measuring the workpiece, thus generating interference fringes. The initial topographic data is obtained by counting the interference fringes. The process of obtaining initial topographic data using a contact atomic force microscope involves measuring the surface height using the atomic forces generated between atoms at the tip of a fine probe and surface atoms, thereby obtaining the initial topographic data.

[0043] Step 102: Generate a self-affine rough surface based on all initial topographic parameters corresponding to all measurement points.

[0044] Among them, the self-affine rough surface is a parameterizable surface generated for the atomic-scale mechanism study of the ultra-precision polishing process.

[0045] In one specific embodiment, generating a self-affine rough surface based on all initial topography parameters corresponding to all measurement points includes: reconstructing each initial topography parameter to obtain the surface height of the workpiece to be polished corresponding to each measurement point; and generating a self-affine rough surface based on all surface heights.

[0046] In one specific embodiment, the initial topography parameters are reconstructed to obtain the surface height of the workpiece to be polished corresponding to each measurement point. This includes: reconstructing each initial topography parameter to obtain the root mean square height value, root mean square slope, and fractal dimension corresponding to each initial topography parameter; wherein, the root mean square height value... root mean square slope , This indicates the total number of measurement points. This represents the third morphological parameter. Indicates the first morphological parameter. The second morphological parameter is represented; all Hearst exponents are determined based on each fractal dimension and a preset threshold; where, the Hearst exponent... , Indicates the preset threshold. The fractal dimension is represented; the surface height of the workpiece to be polished corresponding to each measurement point is determined based on each root mean square height value, each root mean square slope, and each Hearst exponent.

[0047] Furthermore, the calculated root mean square height value of the generated surface is compared with the input target root mean square height value. The ratio of the absolute value of the difference between the root mean square height value and the target root mean square height value to the target root mean square height value is less than or equal to 0.1. Otherwise, the surface height is regenerated.

[0048] In this step, the initial morphology parameters include a first morphology parameter, a second morphology parameter, and a third morphology parameter. The first morphology parameter is... The parameters of the shaft, the second morphology parameter is The parameters of the axis are as follows: the third morphology parameter is the parameter of the Z-axis.

[0049] Specifically, for any initial topographic parameters of a measurement point, after obtaining the initial topographic parameters, each initial topographic parameter is reconstructed, and the root mean square height value and root mean square slope are obtained through statistical calculation. and root mean square slope ,in, This indicates the total number of measurement points. This represents the third morphological parameter. Indicates the first morphological parameter. This represents the second morphological parameter. Then, the initial morphological parameters are further analyzed. By importing the third morphological parameter from the initial morphological parameters into Matlab (which integrates powerful functions such as numerical analysis, matrix computation, scientific data visualization, and modeling and simulation of nonlinear dynamic systems into an easy-to-use window environment, providing a comprehensive solution for scientific research, engineering design, and many scientific fields that require effective numerical computation, and largely eliminating the editing mode of traditional non-interactive programming languages), and using the box counting method, a three-dimensional contour of the surface of the workpiece to be polished is generated. The three-dimensional contour is represented by the fractal dimension. ,in, It is the smallest cubic box. Let be the side length of the box, with x-axis coordinate Let be the y-axis coordinate. The slope of the line fitted by the least squares linear regression method is the fractal dimension D. This represents the third morphological parameter. These are pre-defined constant coefficients. After determining the fractal dimension D corresponding to all measurement points, all Hearst exponents are determined based on each fractal dimension and a preset threshold. , Indicates the preset threshold. M represents the fractal dimension; M can be, for example, 3, but this embodiment does not limit this. Then, the surface height of the workpiece to be polished corresponding to each measurement point is determined according to each root mean square height value, each root mean square slope value, and each Hearst exponent. For the calculated root mean square height value of the surface, it is compared with the input target root mean square height value. The root mean square height value and the target root mean square height value may be different. The surface height is generated through multiple iterations until the absolute value of the difference between the root mean square height value and the target root mean square height value and the ratio of the target root mean square height value are less than or equal to 0.1. Otherwise, the surface height is regenerated.

[0050] Specifically, based on the root mean square height value and each Hearst exponent, the surface height of the workpiece to be polished corresponding to each measurement point is determined. First, the power spectrum of the measurement surface of the workpiece to be polished (the polishing space to be simulated) is obtained, and the roll-off wave vector is obtained by calculating the basic wave vector parameters. Long-range cutoff wave vector and short-range cutoff wave vector Long-range cutoff wave vector , The length of the rough surface of the workpiece to be polished is used to simulate this. Short-range cutoff wave vector. , It is twice the characteristic atomic spacing of the simulated workpiece to be polished. a0 is the lattice constant of the material. Taking single-crystal silicon as an example, a0 = 0.543 nanometers. This embodiment does not limit this value.

[0051] Figure 2 This is a schematic diagram of the relevant parameters for power spectrum calculation provided by the present invention, as shown below. Figure 2 As shown, the obtained roll-off wave vector is plotted on the horizontal axis. Long-range cutoff wave vector and short-range cutoff wave vector The corresponding points are represented by the ordinate logC, which indicates the logarithm of the constant C, and the abscissa log wavevector, which indicates the logarithm of the wave vector. logq indicates the logarithm of the wave vector value q. The wave vector value of the workpiece to be polished is determined to ascertain the power spectral parameters. The calculation is shown in formula (1).

[0052] (1) In formula (1), C is a constant coefficient. coefficient. Indicates the wave vector value. This refers to the Hearst index. Represents a constant.

[0053] Determining the root mean square height value and the Hearst exponent Then, the root mean square height value and the Hearst exponent. and The coefficients are related, as shown in formula (2).

[0054] (2) Formula (2) can be used to derive The results of the coefficients. Finally, under the assumption... In this case, calculate the surface height of the workpiece to be polished. ,in, Indicates power spectral parameters, This represents the wave vector value. The power spectral parameters are derived using a formula. The calculation process is shown in formulas (3) and (4).

[0055] (3) (4) In formula (4), the coefficients The calculation process is shown in formula (5).

[0056] (5) Furthermore, after obtaining the surface height of the workpiece to be polished corresponding to each measurement point, a self-affine rough surface is generated based on all surface heights.

[0057] Specifically, it involves generating a power spectral density parameter that satisfies a specific requirement. ) Statistical properties of random height fields This is the third morphological parameter. This process is completed in the frequency domain by introducing a random phase and forcing Hermitian symmetry to ensure that the inverse Fourier transform result is a real value.

[0058] (1) First, define a discrete wave vector grid in the frequency domain corresponding to the real space grid. Let the size of the real space grid be N×N and the physical size be L×L. Then the wave vector resolution and range are determined by the Fourier transform specification as shown below.

[0059] Wave vector resolution As shown in formula (6): , (6) Where m and n are both integer indices. In the standard Discrete Fourier Transform (DFT), the index is usually taken as shown in the following formula (7): (7) radial modulus of wave vector As shown in the following formula (8): (8) (2) Constructing a system that satisfies The goal is to construct a complex frequency domain field G(q) = G(qx, qy), whose expected value of the square of its modulus is... Equal to the set power spectral density parameter (q) is shown in formula (9).

[0060] (9) At the same time, a random phase is assigned to it to generate a self-affine rough surface morphology.

[0061] Define a phase field Θ(q), where each component is a uniformly distributed and independent random variable on the interval [0, 2π). Based on this, a complex random phase field with unit amplitude is formed. As shown in formula (10).

[0062] (10) Construct the initial complex frequency domain field As shown in formula (11).

[0063] (11) In formula (11), S is the scaling factor, which is determined by formula (12).

[0064] (12) In formula (12), = =L / N is the spacing between real space grid cells.

[0065] (3) To ensure the random height field of the result after the inverse Fourier transform For a function to be real, G(q) must satisfy Hermitian symmetry for any (m, n): G(q) = G*(-q), where * denotes complex conjugation. The resulting... Forced to become As shown in formula (13).

[0066] (13) (4) Performing a two-dimensional inverse discrete Fourier transform (2D Inverse DFT) on the complex frequency domain field G(q) that satisfies Hermitian symmetry, the height field can be obtained. .

[0067] This process can be implemented using Python (a high-level dynamic programming language). Alternatively, the fourier_synthesis function in SurfaceTopography software (a software specifically designed for processing terrain data) can be used to reconstruct the surface heights of all surfaces of the workpiece to be polished corresponding to each measurement point, thus obtaining a self-affine rough surface. This embodiment does not limit this approach.

[0068] Because it is generated using the fast Fourier transform (FFT), the height map of the face height is itself periodic.

[0069] Furthermore, the actual root mean square height Sq2 of the generated surface is calculated as shown in formula (14).

[0070] (14) Then, calculate the gradients: dz / dx, dz / dy, and calculate the slope magnitude. As shown in formula (15).

[0071] (15) Continue to calculate the actual root mean square slope Sdq2 as shown in formula (16).

[0072] (16) Then slope calibration is performed: because the generated rough surface is required to have the target Sdq, the surface height map is scaled: scaling factor Calibrationfactor = Sdq / Sdq², where Sdq is the actual root mean square height field. The calculation is shown in formula (17).

[0073] (17) Because the surface height is also scaled after scaling, the actual root mean square height Sq2_calibrated needs to be recalculated. It is then checked whether Sq2_calibrated satisfies the requirement that the error between it and the target root mean square height value is within 10%. If so, the generated surface is accepted as a simulated surface; otherwise, the above steps are performed: regenerate the random phase, regenerate the height map, recalibrate the slope, and recheck.

[0074] When regenerating the random phase, other parameters (including C0) remain unchanged, so each iteration yields a different random surface, but with the same characteristics. Functions (i.e., the same statistical properties).

[0075] For example, in the process of creating a self-affine rough surface, the self-affine rough surface can be reconstructed using the fourier_synthesis function in Python or SurfaceTopography software (a software specifically designed for processing terrain data). This is achieved by setting the spatial grid size to N×N (surface topography resolution), the simulation size to L×L, and the Hearst exponent. The lattice constant of the material, first magnification Second magnification Roll-off wavelength The root mean square slope is Sdq. After obtaining the self-affine roughened surface, the surface height corresponding to the self-affine roughened surface is written into a height file at each fixed size according to a fixed resolution. In file 'a' (e.g., file 'a'), import it into MATLAB, and then generate an image corresponding to the self-affine rough surface. Figure 3 This is a schematic diagram of the self-affine rough surface provided by the present invention, as shown below. Figure 3 As shown, Figure 3 The raised and recessed sections are formed by varying surface heights. The first magnification, second magnification, and roll-off wavelength are all adjusted in the software, along with the root mean square slope value. The calculation is shown in formula (18).

[0076] (18) The advantage of this setting is that it allows for the control of the polishing process by adjusting the first magnification factor, the second magnification factor, and the roll-off wavelength.

[0077] Step 103: Construct a molecular dynamics model based on the self-affine rough surface.

[0078] In this step, the molecular dynamics model is used to simulate and analyze the polishing of the workpiece to be polished.

[0079] Specifically, after obtaining the self-affine rough surface, a molecular dynamics model is constructed based on the self-affine rough surface.

[0080] In one specific embodiment, constructing a molecular dynamics model based on a self-affine rough surface includes: constructing an initial ideal bulk crystal supercell; wherein the initial ideal bulk crystal supercell is constructed based on workpieces with the same workpiece attribute information as the workpiece to be polished; generating a target atomic model based on the initial ideal bulk crystal supercell and the self-affine rough surface; wherein the target atomic model is an atomic model with self-affine fractal surface characteristics. Figure 4 This is a schematic diagram of the target atom model provided by the present invention, as shown below. Figure 4As shown; in the simulator, the model parameters are set based on the target atom model to construct a molecular dynamics model; the model parameters include the Hurst exponent, which is not limited in this embodiment.

[0081] Specifically, the process begins by constructing a primitive cell using the Atomic Simulation Environment (ASE) Python library. Specifically, in the Building module, the primitive cell is defined by specifying parameters such as the model name of the target material (e.g., single-crystal silicon), space group or Bravais lattice type (e.g., diamond structure), and lattice constant (e.g., 5.431 Å). Then, the number of primitive cells in each of the three dimensions is defined to create a supercell, thus constructing the initial ideal bulk crystal supercell. After constructing the initial ideal bulk crystal supercell, all atomic coordinates of the supercell are written into a file (e.g., a .b file) in LAMMPS (Large-scale Atomic / Molecular Massively Parallel Simulator) data readable format. The model file is then imported into MATLAB, and the surface height function is analyzed. Define a heightmap (such as file A) that satisfies periodic boundary conditions along the x and y axes of a two-dimensional region. Using appropriate interpolation methods (such as bilinear interpolation or cubic spline interpolation), it can be transformed into a continuous function to determine the height value at any continuous coordinate (x, y). Then, based on the height function... Screening bulk atomic crystal models yielded the following results: Figure 4 The target atomic model shown: For each atom in the bulk supercell, its vertical projection is... Plane, calculate the surface height corresponding to this point. Comparing atomic height with surface height Then, each atom located above the height profile of the rough surface in the crystal model is deleted, due to the bulk supercell and surface height function. All with The plane is periodic, and the above screening process automatically ensures that the generated target atomic model is within the periodic plane. The plane satisfies periodic boundary conditions. All atomic information from the target atom set is written to a file (file c), such as the LAMMPS data file format. This file typically contains: total number of atoms, simulation box size, atom identity document (ID), atom type, charge (if applicable), and coordinates. Thus, a target atomic model with self-affine fractal surface characteristics is established. Finally, in the simulator, the model parameters are set based on the target atomic model to construct a molecular dynamics model; the model parameters include the Hurst exponent, which is not limited in this embodiment.

[0082] In this step, the simulator can be, for example, the large-scale atomic / molecular parallel simulator LAMMPS, and the molecular dynamics model is a molecular dynamics model for polishing single-crystal silicon workpieces with diamond abrasive grains; this embodiment does not limit this to the specific model. Model parameters include, but are not limited to, the Hurst exponent.

[0083] Figure 5 This is a schematic diagram of the molecular dynamics model provided by the present invention, as shown below. Figure 5 As shown, the molecular dynamics model for polishing a single-crystal silicon workpiece with diamond abrasive particles consists of an atomic model of the workpiece to be polished (e.g., polishing can be performed on the orientation surface of a single-crystal silicon (001) crystal) and a diamond abrasive particle group as the polishing tool (the abrasive particle group consists of multiple diamond spherical abrasive particles with adjustable radii; in this example, it consists of 9 abrasive particles. The advantage of this setting is that, compared to the traditional method of considering the shape of the tool as the abrasive particle, the spherical abrasive particles act on the material with a large negative rake angle, which is closer to the real polishing situation; and it is generated by the lammps command; the abrasive particle group is evenly distributed on the surface, the number of abrasive particles is adjusted according to the concentration of the polishing slurry, and the particle size range is adjusted by changing the abrasive particles). This embodiment does not limit this aspect.

[0084] The number of abrasive grains to be set can be adjusted according to the abrasive concentration of the polishing slurry; however, this embodiment does not limit this.

[0085] For example, when diamond abrasive groups are used as polishing tools, the number and size of abrasive grains in the simulation settings can be adjusted according to the concentration of the polishing slurry and the selected abrasive grain size. This embodiment does not limit this.

[0086] Furthermore, the setting of model parameters mainly includes (1) determining the solution algorithm for the molecular dynamics equations of motion (such as the fourth-order Runge-Kutta method, the Leap-Frog method, the Verlet method, the Velocity-Verlet method (a numerical integration method for solving equations of motion in classical mechanics), etc. This technical solution comprehensively considers efficiency and accuracy and adopts the Velocity-Verlet algorithm), and selecting the potential energy function describing the polishing simulation system (Te is used for the interaction between diamond and silicon atoms (C-Si). rsoff (a widely used function in materials science to control interatomic interactions); the diamond abrasive grain (CC) is Lennard-Jones (an empirical potential widely used to describe the interaction between two unbonded atoms); an ensemble for simulating the experimental environment is set (an isobaric and isothermal ensemble is chosen during the relaxation stage to obtain a structurally stable model at 300 Kelvin room temperature and 0 bar (Pascal); after the simulation begins, a microcanonical ensemble is set); and boundary conditions are set (periodic boundary conditions are set on the xy plane, i.e., in the main interaction directions). The trajectory of each atom within the system follows classical Newtonian motion. The target atom model and potential energy function are imported from outside into LAMMPS, and the rest are set in LAMMPS. (2) The influence of the environment on polishing is taken into account in the simulation settings. This is achieved by setting the Langevin thermostat in the simulator (for example, considering the viscous resistance of the polishing liquid to the abrasive grains, a viscous damping term proportional to the particle velocity is set according to the viscosity of the polishing liquid, and the force generated by the random collision of particles with the carrier liquid). (3) The system is subjected to energy minimization operation, followed by system relaxation operation, and then loads are applied to multiple abrasive grains in the abrasive grain group (in the example, different loads or asymptotic loads can be applied separately). The system ensures that the normal force FN acting on each abrasive grain reaches a set value and stabilizes. Then, a constant tangential force FX or a variable tangential force (affecting the abrasive grain's movement speed, determined by the polishing head's rotation speed) is applied to move or rotate the abrasive grain within the system, while maintaining a constant normal force FN. This simulates a similar setup in polishing experiments (where a constant normal force / pressure and a variable tangential force / rotation speed are typically set). In this simulation, a load can be applied to each abrasive grain. Existing simulations only set the movement speed of the abrasive grains, rather than driving them with force, and therefore cannot reflect the actual movement of the abrasive grains during polishing. This embodiment does not limit this aspect.

[0087] Meanwhile, in the simulation system, in order to avoid the same spot on the surface being repeatedly polished by the same abrasive grain or the abrasive grain group being over-polished, a certain lateral force FY is applied to ensure that the abrasive grain will move obliquely at a certain angle. The setting of the lateral force FY is directly related to the angle at which the abrasive grain is to move. The advantage of this setting is that it avoids excessive surface polishing and can simulate the polishing effect achieved by having 𝑈×𝐴 abrasive grains in a plane with a range of U times.

[0088] Because in The atomic model on the plane has periodic boundary conditions. The angle of motion of the abrasive grains is related to the number of times (U) that abrasive grain A crosses the boundary to return to its initial position. When the abrasive grain moves from... When it rolls out from one side of the boundary, it will immediately roll in from the other side, which can simulate a plane with a range U times larger. exist The polishing effect is achieved by individual abrasive grains. The coordinates of the atomic model and the abrasive grain atoms are then compared at each simulation time step. Write to a LAMMPS readable data file. (4) To conduct process research, the effects of rough surface parameters, abrasive concentration, abrasive particle size, and polishing force on surface morphology, material interior, and polishing effect in polishing simulation were studied. Different settings were made for the model. Rough surface parameters: When reconstructing the self-affine rough surface, the Hurst exponent was adjusted. ( (Generally 0.5-0.9), first magnification Second magnification Atomic models with different statistical characteristics of surface morphology are constructed for simulation. In the simulation settings, model settings or simulation settings, such as rough surface parameters, abrasive concentration, abrasive particle size, polishing force, etc., can be adjusted to carry out process research. This embodiment does not limit this.

[0089] Figure 6 This is a schematic diagram of an atomic model of surface morphology with different statistical characteristics provided by the present invention, such as... Figure 6 As shown, Figure 6 In the diagram, ①, ②, ③, and ④ represent the Hearst index. When increasing sequentially or by magnification Atomic models of statistically characteristic surface morphology are derived by decreasing the size sequentially. Abrasive concentration: In the LAMMPS system, different numbers (generally greater than or equal to one) of abrasive spheres can be constructed using the LAMMPS command to characterize the differentiated abrasive concentration used in polishing. Figure 7 This is a schematic diagram of different abrasive concentration settings provided by the present invention, such as... Figure 7 As shown, ① represents the case of low abrasive concentration, ② represents the case of medium abrasive concentration, and ③ represents the case of high abrasive concentration. Abrasive particle size: In the LAMMPS system, the diameter of the abrasive particles can be set using the LAMMPS command; Polishing force: During the setting stage of applying force to each abrasive particle, the values ​​of the normal force and tangential force are adjusted. This embodiment does not limit this.

[0090] The advantage of this setup is that the surface morphology of the generated atomic model strictly follows the height map. Since the reconstructed self-affine rough surface is periodic, the selected molecular dynamics model is also periodic in the x and y directions. This means that when an atom moves out from one side in the x and y directions, it will re-enter from the other side. In polishing simulations, this eliminates the effects of boundaries; and the smaller surface created can also represent processes occurring on an infinitely large surface.

[0091] In one specific implementation, after setting model parameters based on the target atomic model and constructing a molecular dynamics model in the simulator, the process further includes: determining whether the model Hurst exponent is the same as all Hurst exponents; if the model Hurst exponent is not the same as all Hurst exponents, determining the surface height of the workpiece to be polished corresponding to each measurement point based on each root mean square height value, each root mean square slope, and the model Hurst exponent; if the model Hurst exponent is the same as all Hurst exponents, continuing to perform simulation polishing based on the molecular dynamics model and the simulator to obtain the target morphology parameters.

[0092] Specifically, in the simulator, after setting the model parameters based on the target atomic model and constructing the molecular dynamics model, it is determined whether the model Hurst exponent is the same as all Hurst exponents. If the model Hurst exponent is different from all Hurst exponents, the surface height of the workpiece to be polished corresponding to each measurement point is re-determined based on the root mean square height value and the root mean square slope model Hurst exponent. If the model Hurst exponent is the same as all Hurst exponents, the simulation polishing based on the molecular dynamics model and the simulator is continued to obtain the target morphology parameters.

[0093] Step 104: Perform simulation polishing based on molecular dynamics model and simulator to obtain target morphology parameters.

[0094] Specifically, after obtaining the molecular dynamics model, the molecular dynamics model is simulated and analyzed using a simulator to obtain the target morphology parameters.

[0095] For example, it typically runs on a personal workstation or supercomputing center (depending on the requirements of different computational examples). LAMMPS is commonly deployed on an operating system (such as Linux), and an .in file (executable code file) and a .data file (data file) are prepared in a designated directory. The .in file mainly contains the LAMMPS commands required in step 103. It also includes settings for the output results after calculation, generally including at least the spatial coordinates of each atom, and may output, depending on post-processing needs, such as the forces acting on each atom in three directions. The .data file mainly includes information about external atoms, such as the atomic model built using the Atomic Simulation Environment (a Python library) in step 103. It also includes boundary conditions, atom types, masses, spatial coordinates, etc. In the Linux system, the number of cores to be called is set, and commands are used to start multi-core execution of LAMMPS. This embodiment does not limit this.

[0096] Step 105: Analyze the polishing condition of the workpiece to be polished based on the target morphology parameters, and determine the surface polishing analysis results.

[0097] In one specific embodiment, the surface polishing analysis result is determined by analyzing the polishing condition of the workpiece to be polished based on the target morphology parameters. This includes: analyzing and processing the target morphology parameters to obtain analysis and processing parameters; and analyzing the polishing condition of the workpiece to be polished based on the analysis and processing parameters to determine the surface polishing analysis result.

[0098] In this step, the parameters analyzed include visualized data, surface roughness and height probability density, friction coefficient of abrasive grains, surface power spectral density, material damage during polishing and the mechanism of smooth surface formation during material polishing, diamond abrasive grain concentration, polishing force, etc. This embodiment does not limit these parameters.

[0099] Specifically, after obtaining the target morphology parameters, these parameters are analyzed and processed to obtain analytical parameters. Based on this analysis, the surface morphology is quantitatively characterized, and the root mean square height (i.e., surface roughness value) is recalculated. The statistical distribution of all height values ​​(i.e., height probability density) is obtained through histogram statistics. The shape of this distribution (e.g., symmetry, peak-to-valence ratio) reveals the polishing uniformity effect. A two-dimensional discrete Fourier transform is performed on the height map to calculate its surface power spectral density, revealing the intensity of surface fluctuations at different spatial frequencies. By comparing this with the PSD curve before polishing, the roughness removal efficiency can be quantified. For each abrasive grain, its friction coefficient is defined by the time average of the ratio of the tangential force to the normal force it experiences throughout the polishing process. This parameter is directly related to the energy consumption and heat generation during the polishing process. The atomic strain analysis methods built into LAMMPS (such as centrosymmetry parameter (CSP), coordination number (CN), or affine strain tensor) are used to identify plastic deformation characteristics such as dislocations and lattice distortion, thereby obtaining the damage to the material during polishing and analyzing the plastic deformation of the material. The data can be visualized using Ovito software, and combined with the processed results, the mechanism of smooth surface formation during material polishing can be analyzed. Surface polishing analysis results are obtained through multivariate data analysis and statistical inference analysis. The final surface polishing analysis result is a comprehensive correlation analysis of all the above quantitative indicators and input process parameters.

[0100] Figure 8 This is a schematic diagram of the evolution of polished surface morphology provided by the present invention, such as... Figure 8 As shown, Figure 8 It demonstrates the polishing process simulating an infinitely large surface. Figure 8 ① represents the initial state of the polishing simulation (i.e., when polishing begins), which can characterize the polishing process of an infinitely large surface. Figure 8 Figure ② shows a schematic diagram of the polishing process at any given moment. An atomic model can be selected at any moment to observe the polishing process or to analyze the surface state at any given moment. Figure 8 ③ The surface condition after polishing (i.e., after polishing is completed). Figure 8 Figures ①-③ illustrate the process of simulating polishing of a rough surface within a periodic range.

[0101] This invention provides a method for determining surface polishing analysis results. The method involves obtaining initial morphology parameters corresponding to measurement points on the workpiece to be polished (at least two measurement points); generating a self-affine rough surface based on all initial morphology parameters corresponding to all measurement points; constructing a molecular dynamics model based on the self-affine rough surface; using the molecular dynamics model for simulating polishing analysis of the workpiece; performing simulated polishing based on the molecular dynamics model and the simulator to obtain target morphology parameters; and analyzing the polishing condition of the workpiece based on the target morphology parameters to determine the surface polishing analysis results. This invention addresses the shortcomings of existing technologies that use single abrasive grains for simulation, neglecting the combined effect of abrasive grain groups to achieve surface processing, and only exploring the influence of abrasive grains on crystal structure without evaluating changes in workpiece surface morphology. The invention constructs a molecular dynamics model based on initial morphology parameters with different statistical characteristics, obtains target morphology parameters through simulated polishing, and finally analyzes the polishing condition of the workpiece based on the target morphology parameters to determine the surface polishing analysis results. This achieves the evaluation of surface morphology changes in the workpiece during polishing simulation based on the surface polishing analysis results.

[0102] The apparatus for determining the surface polishing analysis results provided by the present invention will be described below. The apparatus for determining the surface polishing analysis results described below and the method for determining the surface polishing analysis results described above can be referred to in correspondence with each other.

[0103] Figure 9 This is a schematic diagram of the structure of the device for determining the surface polishing analysis results provided by the present invention, with reference to... Figure 9 As shown, the surface polishing analysis result determination device 900 includes: parameter acquisition module 901, surface generation module 902, model construction module 903, simulated polishing module 904, and result determination module 905.

[0104] The parameter acquisition module 901 is used to acquire the initial morphological parameters corresponding to the measurement points of the workpiece to be polished; wherein, there are at least two measurement points.

[0105] The surface generation module 902 is used to generate a self-affine rough surface based on all initial morphology parameters corresponding to all measurement points.

[0106] Model building module 903 is used to build a molecular dynamics model based on the self-affine rough surface; wherein, the molecular dynamics model is used to simulate and analyze the polishing of the workpiece to be polished.

[0107] The simulated polishing module 904 is used to perform simulated polishing based on molecular dynamics models and simulators to obtain target morphology parameters.

[0108] The result determination module 905 is used to analyze the polishing condition of the workpiece to be polished based on the target morphology parameters and determine the surface polishing analysis results.

[0109] In one example embodiment, the surface generation module 902 is specifically used to: reconstruct each initial morphology parameter to obtain the surface height of the workpiece to be polished corresponding to each measurement point; and generate a self-affine rough surface based on all surface heights.

[0110] In one example embodiment, the initial morphology parameters include a first morphology parameter, a second morphology parameter, and a third morphology parameter, wherein the first morphology parameter is... The parameters of the shaft, the second morphology parameter is The parameters of the axis are as follows: the third morphology parameter is the parameter of the Z-axis.

[0111] In one example embodiment, the surface generation module 902 reconstructs each initial topography parameter to obtain the surface height of the workpiece to be polished corresponding to each measurement point. Specifically, it is used to: reconstruct each initial topography parameter to obtain the root mean square height value, root mean square slope, and fractal dimension corresponding to each initial topography parameter; wherein, the root mean square height value... The root mean square slope , This indicates the total number of measurement points. This represents the third morphological parameter. Indicates the first morphological parameter. The second morphological parameter is represented; all Hearst exponents are determined based on each fractal dimension and a preset threshold; where, the Hearst exponent... , Indicates the preset threshold. The fractal dimension is represented; the surface height of the workpiece to be polished corresponding to each measurement point is determined based on each root mean square height value, each root mean square slope, and each Hearst exponent.

[0112] In one example embodiment, the model building module 903 is specifically used for: constructing an initial ideal crystal bulk supercell; wherein the initial ideal crystal bulk supercell is a model constructed based on a workpiece with the same workpiece attribute information as the workpiece to be polished; generating a target atomic model based on the initial ideal crystal bulk supercell and the self-affine rough surface; wherein the target atomic model is an atomic model with self-affine fractal surface features; and in the simulator, setting model parameters based on the target atomic model to construct a molecular dynamics model; wherein the model parameters include the model Hurst exponent.

[0113] In one example embodiment, the device further includes a loop module. The loop module is configured to: in the simulator, after setting model parameters based on the target atomic model and constructing a molecular dynamics model, determine whether the model's Hurst exponent is the same as all Hurst exponents; if the model's Hurst exponent is different from all Hurst exponents, determine the surface height of the workpiece to be polished corresponding to each measurement point based on each root mean square height value, each root mean square slope, and the model's Hurst exponent; if the model's Hurst exponent is the same as all Hurst exponents, continue executing the step of simulating polishing based on the molecular dynamics model and the simulator to obtain the target morphology parameters.

[0114] In one example embodiment, the result determination module 905 is specifically used to: analyze and process the target morphology parameters to obtain analysis and processing parameters; analyze the polishing condition of the workpiece to be polished based on the analysis and processing parameters, and determine the surface polishing analysis result.

[0115] The apparatus of this embodiment can be used to execute the method of any embodiment in the side embodiment of the method for determining surface polishing analysis results. Its specific implementation process and technical effects are similar to those in the side embodiment of the method for determining surface polishing analysis results. For details, please refer to the detailed description in the side embodiment of the method for determining surface polishing analysis results, which will not be repeated here.

[0116] Figure 10 This is a schematic diagram of the structure of the electronic device provided by the present invention, such as... Figure 10 As shown, the electronic device may include a processor 1010, a communications interface 1020, a memory 1030, and a communication bus 1040, wherein the processor 1010, the communications interface 1020, and the memory 1030 communicate with each other via the communication bus 1040. The processor 1010 can call logical instructions in the memory 1030 to execute a method for determining the surface polishing analysis results. This method includes: acquiring initial morphological parameters corresponding to measurement points of the workpiece to be polished; wherein there are at least two measurement points; generating a self-affine rough surface based on all initial morphological parameters corresponding to all measurement points; constructing a molecular dynamics model based on the self-affine rough surface; wherein the molecular dynamics model is a model used for simulating polishing analysis of the workpiece to be polished; performing simulated polishing based on the molecular dynamics model and the simulator to obtain target morphological parameters; and analyzing the polishing condition of the workpiece to be polished based on the target morphological parameters to determine the surface polishing analysis results.

[0117] Furthermore, the logical instructions in the aforementioned memory 1030 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, 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. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0118] On the other hand, the present invention also provides a computer program product, which 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 surface polishing analysis results provided by the above methods. The method includes: obtaining initial morphological parameters corresponding to measurement points of the workpiece to be polished; wherein, there are at least two measurement points; generating a self-affine rough surface based on all initial morphological parameters corresponding to all measurement points; constructing a molecular dynamics model based on the self-affine rough surface; wherein, the molecular dynamics model is a model used for simulating polishing analysis of the workpiece to be polished; performing simulated polishing based on the molecular dynamics model and the simulator to obtain target morphological parameters; and analyzing the polishing condition of the workpiece to be polished based on the target morphological parameters to determine the surface polishing analysis results.

[0119] In another aspect, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements a method for determining the surface polishing analysis results provided by the methods described above. This method includes: acquiring initial morphological parameters corresponding to measurement points of the workpiece to be polished; wherein the measurement points are at least two; generating a self-affine rough surface based on all initial morphological parameters corresponding to all measurement points; constructing a molecular dynamics model based on the self-affine rough surface; wherein the molecular dynamics model is a model used for simulating polishing analysis of the workpiece to be polished; performing simulated polishing based on the molecular dynamics model and the simulator to obtain target morphological parameters; and analyzing the polishing condition of the workpiece to be polished based on the target morphological parameters to determine the surface polishing analysis results.

[0120] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0121] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, 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. This 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 to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0122] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for determining the results of surface polishing analysis, characterized in that, include: Obtain the initial morphological parameters corresponding to the measurement points of the workpiece to be polished; wherein, there are at least two measurement points; A self-affine rough surface is generated based on all the initial topography parameters corresponding to all the measurement points; A molecular dynamics model is constructed based on the self-affine rough surface; wherein, the molecular dynamics model is used to simulate and analyze the polishing of the workpiece to be polished; The target morphology parameters were obtained by performing a simulation polishing based on the molecular dynamics model and the simulator. The polishing condition of the workpiece to be polished is analyzed based on the target morphology parameters to determine the surface polishing analysis results.

2. The method for determining the surface polishing analysis results according to claim 1, characterized in that, The step of generating a self-affine rough surface based on all the initial topography parameters corresponding to all the measurement points includes: Each of the initial morphology parameters is reconstructed to obtain the surface height of the workpiece to be polished corresponding to each measurement point; The self-affine rough surface is generated based on all the surface heights.

3. The method for determining the surface polishing analysis results according to claim 2, characterized in that, The initial morphology parameters include a first morphology parameter, a second morphology parameter, and a third morphology parameter, wherein the first morphology parameter is... The parameters of the shaft, the second morphology parameter is The parameters of the axis, wherein the third morphological parameter is the parameter of the Z-axis; The step of reconstructing each of the initial morphology parameters to obtain the surface height of the workpiece to be polished corresponding to each measurement point includes: Each of the initial topographic parameters is reconstructed to obtain the root mean square height value, root mean square slope, and fractal dimension corresponding to each initial topographic parameter; wherein, the root mean square height value... The root mean square slope , This indicates the number of all the measurement points. This represents the third morphological parameter. This represents the first morphological parameter. This represents the second morphological parameter; All Hearst exponents are determined based on the respective fractal dimensions and preset thresholds; wherein, the Hearst exponents , This represents the preset threshold. Denotes the fractal dimension; The surface height of the workpiece to be polished corresponding to each measurement point is determined based on the root mean square height value, the root mean square slope, and the Hearst exponent.

4. The method for determining the surface polishing analysis results according to claim 3, characterized in that, The construction of the molecular dynamics model based on the self-affine rough surface includes: Construct an initial ideal crystal bulk supercell; wherein, the initial ideal crystal bulk supercell is a model constructed based on a workpiece with the same workpiece attribute information as the workpiece to be polished; A target atomic model is generated based on the initial ideal crystal bulk supercell and the self-affine rough surface; wherein, the target atomic model is an atomic model with self-affine fractal surface features; In the simulator, the molecular dynamics model is constructed by setting model parameters based on the target atom model; wherein, the model parameters include the model Hurst exponent.

5. The method for determining the surface polishing analysis results according to claim 4, characterized in that, After setting the model parameters based on the target atom model and constructing the molecular dynamics model in the simulator, the process further includes: Determine whether the model's Hearst exponent is the same as all the Hearst exponents; When the model Hearst exponent is not the same as all the Hearst exponents, the surface height of the workpiece to be polished corresponding to each measurement point is determined according to the model Hearst exponent based on each root mean square height value and each root mean square slope. If the model's Hurst exponent is the same as all the Hurst exponents, continue with the step of performing simulation polishing based on the molecular dynamics model and the simulator to obtain the target morphology parameters.

6. The method for determining the surface polishing analysis results according to claim 1, characterized in that, The step of analyzing the polishing condition of the workpiece to be polished based on the target morphology parameters and determining the surface polishing analysis results includes: The target morphology parameters are analyzed and processed to obtain the analysis and processing parameters; The polishing condition of the workpiece to be polished is analyzed based on the analysis and processing parameters to determine the surface polishing analysis result.

7. A device for determining the results of surface polishing analysis, characterized in that, include: The parameter acquisition module is used to acquire the initial morphological parameters corresponding to the measurement points of the workpiece to be polished; wherein, there are at least two measurement points; A surface generation module is used to generate a self-affine rough surface based on all the initial morphology parameters corresponding to all the measurement points. The model building module is used to construct a molecular dynamics model based on the self-affine rough surface; wherein, the molecular dynamics model is used to perform simulation polishing analysis on the workpiece to be polished; The simulated polishing module is used to perform simulated polishing based on the molecular dynamics model and the simulator to obtain the target morphology parameters; The result determination module is used to analyze the polishing condition of the workpiece to be polished based on the target morphology parameters and determine the surface polishing analysis result.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the method for determining the surface polishing analysis results as described in any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the method for determining the surface polishing analysis results as described in any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the method for determining the surface polishing analysis results as described in any one of claims 1 to 6.

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