Simulation prediction analysis method for microscopic topography and roughness of laser polished diamond surface

Abstract

The application provides a simulation prediction analysis method for laser polishing of a microtopography and roughness of a diamond surface, and comprises the following steps: creating a mapping relationship data table of laser parameters and laser spot size and power density; establishing a mapping relationship model diagram of laser spot power density, pulse width, laser incidence angle and diamond surface ablation pit depth; constructing an analysis model of a laser spot stacking state; generating a simulation image of the microtopography of the laser polished diamond surface; and predicting the roughness of the laser polished diamond surface. The application takes the machining parameters of laser spot power, pulse width, repetition frequency, defocusing amount, incidence angle, transverse scanning rate and longitudinal stepping interval as inputs, takes the microtopography and roughness of the laser polished diamond surface as outputs, and establishes a mapping relationship between the inputs and the outputs through simulation analysis of the size of the ablation pit, the spot scanning path and the spot stacking state, so as to guide the optimization of the laser polishing process parameters.

Description

Technical Field

[0001] This invention relates to the technical field of diamond processing, and in particular to a method for simulating and predicting the microstructure and roughness of laser-polished diamond surfaces. Background Technology

[0002] Diamond, known as the "king of materials," possesses exceptional properties in mechanical, thermal, optical, electrical, and chemical aspects, and has long been a focus of attention for scholars both domestically and internationally. While diamond is widely used in abrasives and grinding tools, its application in high-tech fields such as military, aerospace, and micro / nano sensors is gaining increasing importance as chemical vapor deposition (CVD) technology for growing diamond matures. Optical, electronic, and heat sink-grade diamond wafers require extremely high surface quality, demanding micron- or submicron-level surface accuracy and nanometer-level surface roughness. However, due to the columnar growth characteristics of CVD polycrystalline diamond, the diamond surface exhibits coarse and inconsistent grain sizes and crystal orientations, resulting in extremely rough surfaces that cannot meet the high-quality requirements of these fields. Therefore, polishing is essential before use to reduce the surface roughness to within specified limits.

[0003] The high hardness, brittleness, wear resistance, and chemical inertness of diamond make traditional mechanical polishing methods extremely time-consuming and inefficient, with a high risk of scratches, breakage, and fragmentation, severely impacting processing costs and yield. Therefore, these methods are unsuitable for polishing high-quality diamond sheets. Subsequent thermochemical mechanical polishing methods improved efficiency, but their stringent requirements for equipment and process conditions, coupled with difficulty in controlling the polishing process, prevented widespread adoption. New laser polishing technology effectively eliminates these drawbacks of mechanical polishing, offering advantages such as high processing efficiency, high precision control, small area affected by degradation, and no mechanical stress. Furthermore, it disregards the complexity of the initial surface, providing high flexibility.

[0004] Laser polishing operates on two principles: one is the remelting polishing of metallic materials, based on the thermodynamics and rapid melting mechanism of laser materials. By precisely controlling the laser to melt the rough metal surface and optimizing the non-equilibrium solid-liquid-gas phase transition, under the influence of gravity and surface tension of the molten material, and without affecting the original geometric dimensions, the rough surface becomes smooth after remelting, ultimately optimizing the surface roughness. The other is the refining polishing of refractory crystal materials, which focuses a fine laser onto the micro-peaks on the surface of the material. Under the influence of laser photon energy, the surface material undergoes a qualitative change or vaporization, achieving precise ablation and removal of the tiny surface particles. This reduces the micro-peaks on the rough surface, reshaping the microscopic topography of the material surface and thus reducing roughness. Laser polishing of diamond belongs to the latter category.

[0005] For example, patent application number CN201811415381.4 discloses a method for laser-assisted polishing of CVD diamond, which utilizes laser rough polishing and mechanical fine polishing to achieve the required precision and efficiency, solving the problems of low efficiency and poor quality in diamond polishing. However, laser polishing is an innovative new technology that has been developed in recent years. It lacks sufficient empirical data and theoretical guidance, and involves numerous parameters and complex processes. Therefore, a large number of experimental analyses are needed to optimize process parameters. However, high-quality optical-grade and electronic-grade diamond sheets are extremely expensive, leaving no room for trial and error. Therefore, it is necessary to establish a mapping relationship between laser polishing process parameters and diamond surface topography and roughness, and to predict and analyze the surface quality of laser-polished diamond to minimize experimental trial and error costs.

[0006] Patent application number 201910108452.4 discloses a method for predicting surface roughness using laser impact, training a roughness prediction model, and verifying the accuracy of the prediction model using test samples. However, this method relies on real-time measurement of the energy spatial distribution in the laser and focuses on the analysis of the laser's own stability, without specifically considering the influence of process methods and laser parameters, making it unsuitable for optimizing the laser polishing process of CVD diamond. Currently, there are no publicly reported methods for simulating the micro-topography and predicting the roughness of laser-polished diamond surfaces. Summary of the Invention

[0007] To address the technical problem of the inability to systematically predict the surface results of laser-polished diamonds, this invention proposes a method for simulating and predicting the micro-topography and roughness of laser-polished diamond surfaces. This method establishes a mapping relationship between laser polishing process parameters and the surface topography and roughness of diamonds, enabling rapid, accurate, and predictive determination of laser polishing results. It guides the optimization of laser polishing process parameters and reduces the trial-and-error costs of laser polishing diamonds.

[0008] To achieve the above objectives, the technical solution of the present invention is as follows: a method for simulating and predicting the microstructure and roughness of laser-polished diamond surfaces, comprising the following steps:

[0009] S1: Under different laser parameters, a single point on the test sample is ablated with a single shot to reflect the laser spot size. The laser spot size is obtained and the laser spot power density is calculated. A mapping relationship data table between laser spot size and laser spot power density is created.

[0010] S2: A single-point, single-pass ablation test was conducted on the surface of a diamond sheet to establish a mapping relationship model between the laser spot power density and the depth of the ablation pits on the diamond surface under different pulse widths and laser incident angles.

[0011] S3: Construct an analytical model of the laser spot stacking state based on the mapping relationship data table and mapping relationship model diagram;

[0012] S4: Using an analysis model of the stacked state of laser spots, generate a simulated image of the micro-topography of the laser-polished diamond surface;

[0013] S5: Predict the surface roughness of laser-polished diamond based on data from simulated images of the micro-topography of the laser-polished diamond surface.

[0014] The method for creating the mapping relationship data table between laser spot size and power density in step S1 is as follows:

[0015] S11: Under different combinations of laser parameters such as power, pulse width, repetition frequency, defocusing amount, and incident angle, a laser is used to perform single-point single-shot sampling on the surface of the test sample.

[0016] S12: For the ablation pits formed under different combinations of laser parameters on the test sample, the length and width of each ablation pit are detected one by one using a precision three-dimensional contour detection instrument, which serves as a reflection of the corresponding laser spot size.

[0017] S13: Calculate the laser spot power density using average power, pulse width, repetition frequency, and laser spot size;

[0018] S14: Summarize the laser spot size and laser spot power density detected under different combinations of laser parameters such as power, pulse width, repetition frequency, defocusing amount, and incident angle, and create a mapping data table of laser spot size and laser spot power density corresponding to different laser parameters.

[0019] The method for detecting the length and width of the ablation pit in step S12 is as follows: if the laser incident angle is 0°, the laser ablation pit is circular, and the length and width of the laser ablation pit are both the diameter of the circle. If the laser incident angle is not 0°, the laser ablation pit is elliptical. The major axis of the ellipse is recorded as the length of the laser ablation pit, and the minor axis of the ellipse is recorded as the width of the laser ablation pit.

[0020] Step S2 establishes the mapping relationship model between laser spot power density, pulse width, laser incident angle, and the depth of ablation pits on the diamond surface as follows:

[0021] S21: Using a laser, single-point single-time ablation tests were performed on the surface of a diamond sheet under different combinations of laser spot power density, pulse width, and laser incident angle.

[0022] S22: The depth of the ablation pits formed under different parameter combinations on the surface of the diamond sheet is detected. The depth of a single ablation pit is measured three times. If the laser incident angle is 0°, the average value of the three depth measurements is taken. If the laser incident angle is not 0°, the depth is measured once at the beginning, middle and end of the major axis of the elliptical ablation pit, and the depth value of the three equally divided segments is recorded.

[0023] S23: Regression analysis was performed on the laser spot power density and the depth of ablation pits on the diamond surface under different incident angles and pulse widths, and the mapping relationship model diagram was obtained.

[0024] Step S23: The method for performing regression analysis and obtaining the mapping relationship model diagram is as follows:

[0025] When the laser incident angle is 0°:

[0026] S231.1: Nonlinear regression analysis was performed on different laser spot power densities and corresponding ablation pit depths under the same pulse width conditions. The laser spot power density was taken as an equally spaced increasing value, with the laser spot power density as the X-axis and the ablation pit depth as the Z-axis. B-spline fitting was used to obtain the fitting curve I; (sentence order adjustment)

[0027] S231.2: Nonlinear regression analysis was performed on the laser spot power density and corresponding ablation pit depth under various pulse width conditions to obtain multiple fitting curves;

[0028] S231.3: Using the pulse width as the Y-axis, plot the fitting curve obtained in step S231.2 in a three-dimensional rectangular coordinate system I to obtain a model diagram of the mapping relationship between the laser spot power density and the pulse width and the ablation pit depth when the laser incident angle is 0°.

[0029] S231.4: Repeat steps S231.1 to S231.3 to obtain a model diagram of the mapping relationship between laser spot power density, pulse width and ablation pit depth for each available laser incident angle;

[0030] When the laser incident angle is not 0°:

[0031] S232.1: Set the laser incident angle, and perform nonlinear regression analysis on different laser spot power densities and corresponding ablation pit three-segment depth values ​​under the same pulse width conditions. The laser spot power density is taken as an equally spaced increasing value. The laser spot power density is the X-axis and the ablation pit depth is the Z-axis. The corresponding ablation pit three-segment depth values ​​are fitted with B-splines to obtain three fitting curves.

[0032] S232.2: Nonlinear regression analysis was performed on the laser spot power density and the corresponding ablation pit depth under various pulse width conditions, and three fitting curves were obtained for the three-segment depth values ​​of the ablation pit.

[0033] S232.3: Using the pulse width as the Y-axis, plot the fitting curve obtained in step S232.2 in the same three-dimensional rectangular coordinate system II to obtain the mapping relationship model between the laser spot power density and pulse width and the three-segment depth value of the ablation pit under a specific laser incident angle condition;

[0034] S232.4: Repeat steps S232.1 to S232.3 to obtain a mapping model of the laser spot power density and pulse width to the three-segment depth of the ablation pit for each available laser incident angle.

[0035] The method for constructing the analytical model of the laser spot stacking state in step S3 is as follows:

[0036] S31: Based on the mapping relationship data table created in step S1 and the obtained mapping relationship model diagram obtained in step S2, obtain the laser spot length, laser spot width, laser spot power density and diamond surface ablation pit depth under specific parameter combinations of power, pulse width, repetition frequency, defocus amount and incident angle. Generate a simulated spot pattern of equal size according to the laser spot length and laser spot width, and uniformly set pixels inside the simulated spot pattern. The distance between adjacent pixels is set to λ. Assign the value of the corresponding diamond surface ablation pit depth to each pixel in the simulated spot pattern, where λ=1μm.

[0037] S32: Based on the horizontal scanning rate and vertical step interval of the laser spot, calculate the horizontal spot overlap rate and the vertical spot overlap rate, set the two-dimensional plane of the diamond polishing surface, and arrange the simulated spot pattern in the two-dimensional plane according to the horizontal spot overlap rate and the vertical spot overlap rate to obtain a rectangular two-dimensional plane pixel pattern.

[0038] S33: Adjust the pixel values ​​according to the overlap of the simulated light spot patterns within the two-dimensional plane pixel graphic. If a pixel is not in the overlapping area of ​​the simulated light spot patterns, the pixel value remains unchanged. If a pixel is in the overlapping area of ​​the simulated light spot patterns, the pixels in the overlapping area are superimposed and converted into new pixels. The new pixel value is the sum of the pixel values ​​of the corresponding pixels in the overlapping area of ​​the simulated light spot patterns. After adjusting the pixel values ​​of the two-dimensional plane pixel graphic, generate a height map of the simulated light spot stacking state based on the pixel values ​​of the two-dimensional plane pixel graphic.

[0039] The method for arranging simulated light spot patterns in a two-dimensional plane based on the lateral and longitudinal light spot overlap rates, as described in step S32, is as follows: based on the lateral scanning rate of the laser light spot... V s Longitudinal step interval T w Calculate the overlap rate of the light spots in the horizontal and vertical directions respectively:

[0040]

[0041] in, V s This refers to the lateral scanning rate of the laser spot. T w The longitudinal step interval of the laser spot. a The length of the laser spot. b The width of the laser spot. Q The repetition frequency, This refers to the lateral beam overlap rate. This refers to the longitudinal beam overlap rate;

[0042] Based on the horizontal spot overlap rate Overlap rate with longitudinal light spot Simulated light spot patterns are arranged in a two-dimensional plane, with the center-to-center distance between two adjacent light spots being [value missing]. The center distance between two adjacent light spots in the longitudinal direction is T w .

[0043] The method for generating a simulated image of the micro-topography of the laser-polished diamond surface in step S4 is as follows:

[0044] S41: Obtain the maximum and minimum values ​​of the pixel values ​​assigned in the height map of the light spot stacking state generated in step S33. Add the maximum and minimum values ​​and divide by two to obtain the median surface value of the height map of the light spot stacking state. Subtract the median surface value from the assigned value of each pixel in the height map of the light spot stacking state to obtain the simulated height map of the light spot stacking state with the median surface set to zero.

[0045] S42: Invert the values ​​in the height map of the simulated spot stacking state with the mid-plane zeroed out to obtain the height map after inversion.

[0046] S43: Generate a simulated image of the micro-topography of the laser-polished diamond surface based on the height map after the inversion operation.

[0047] The method for generating a simulated image of the micro-topography of the laser-polished diamond surface in step S43 is as follows:

[0048] All values ​​in the height map after the inversion operation in step S42 are taken as Z values. Then, position coordinates X and Y values ​​are added one by one according to the corresponding position of each value in the height map. Set the X and Y values ​​of the first value point at the lower left corner of the height map to 0. The X and Y values ​​of other pixels are increased sequentially. The X and Y values ​​are all positive. The difference between the X and Y values ​​of adjacent value points is λ. Each Z value and its X and Y coordinates can determine a scatter point in the three-dimensional rectangular coordinate system. All Z values ​​and their coordinates are represented as scatter points and displayed in the three-dimensional rectangular coordinate system III. Adjacent scatter points are connected to form a surface. The obtained three-dimensional graphic is the simulated image of the micro-landscape of the laser-polished diamond surface.

[0049] The method for predicting the surface roughness of laser-polished diamond in step S5 is as follows:

[0050] S51: Export the X, Y, and Z coordinates of all scattered points in the simulated image of the micro-topography of the laser-polished diamond surface in step S43, calculate the arithmetic mean of all Z value data, and take the plane that is parallel to the XY plane of the three-dimensional rectangular coordinate system III and equal to the arithmetic mean on the Z axis as the contour mid-surface of the simulated image of the micro-topography of the laser-polished diamond surface, and calculate the surface roughness value of the laser-polished diamond surface using the three-dimensional surface roughness evaluation method of the contour surface morphology of the simulated image.

[0051] S52: Sequentially export the Z-values ​​and X-values ​​or Y-values ​​of the scattered points in a specific row or column of the simulated image of the micro-topography of the laser-polished diamond surface. Calculate the arithmetic mean of all Z-values ​​for that row or column of data. Use the straight line parallel to the X-axis or Y-axis and equal to the arithmetic mean on the Z-axis as the roughness evaluation midline. Then calculate the line roughness value of the laser-polished diamond surface according to the evaluation method of the line roughness standard.

[0052] The beneficial effects of the present invention are as follows: (1) The present invention provides a method for simulating and predicting the micro-topography and roughness of the surface of laser-polished diamond. Through a series of analysis and processing of input parameters such as laser spot power, pulse width, incident angle, and scanning rate, the simulated image of the micro-topography of the surface of laser-polished diamond and the roughness prediction value can be obtained. The mapping relationship between input process parameters and output processing results is innovatively established. The laser polishing results are quickly, accurately, and proactively determined, which guides the optimization of laser polishing diamond process parameters and reduces the trial and error cost of laser polishing diamond.

[0053] (2) This invention is not only applicable to the simulation and prediction of laser polished diamond surfaces, but also suitable for laser polishing of other non-remelting materials, providing new support, new ideas and new methods for laser polishing technology research. Attached Figure Description

[0054] To more clearly illustrate the technical solutions in the embodiments of the present 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 only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0055] Figure 1 This is a schematic diagram of the method flow of the present invention.

[0056] Figure 2 This is a schematic diagram of the motion scanning trajectory of the laser spot on the diamond surface according to the present invention.

[0057] Figure 3 This is a schematic diagram of the overlapping circular laser spots of the present invention.

[0058] Figure 4 This is a height map of the simulated light spot stacking state generated under different parameters of the present invention.

[0059] In the figure, 1 represents the laser beam, 2 represents the motion scanning trajectory of the laser spot, 3 represents the diamond, 4 represents the longitudinal stepping direction of the laser spot scanning, and 5 represents the removal depth. Detailed Implementation

[0060] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0061] Laser processing of diamond surfaces involves the ablation and impact of a series of regularly pulsed laser spots with equal intervals and identical properties. Under sufficient processing time, the microscopic topography of the laser-polished diamond surface is essentially a stack of countless laser pulse ablation pits. The size of the ablation pits, the laser spot scanning path, and the laser spot overlap state are the direct influencing factors on the microscopic topography of the laser-polished surface. This embodiment uses processing parameters such as laser spot power, pulse width, repetition frequency, defocusing amount, incident angle, lateral scanning rate, and longitudinal step interval as inputs, and the microscopic topography and roughness results of the laser-polished diamond surface as outputs. Through simulation analysis of the ablation pit size, laser spot scanning path, and laser spot stacking state, a mapping relationship between input parameters and output results is established. This allows for the rapid, accurate, and leading determination of the laser polishing results, guiding the optimization of laser polishing process parameters.

[0062] like Figure 1 As shown, a method for simulating and predicting the microstructure and roughness of laser-polished diamond surfaces includes the following steps:

[0063] S1: The method for creating a data table mapping the laser parameters to the laser spot size and power density is as follows:

[0064] S11: Under different combinations of laser parameters—power, pulse width, repetition frequency, defocusing amount, and incident angle—single-point, single-shot sampling is performed on the surface of the test sample using a laser, i.e., single-pulse laser sampling. The test sample should be made of a material with a low removal threshold and easy vaporization, such as a uniformly coated aluminum sheet. This avoids situations where the laser energy is too low to produce ablation marks on the sample surface, ensuring that laser spots with different parameter combinations can create noticeable ablation pits on the test sample surface.

[0065] S12: For the ablation pits formed under different laser parameter combinations on the test sample, the length and width of each ablation pit are measured individually using a precision 3D contour detection instrument. A white light interferometric profilometer can be used as the precision 3D contour detection instrument. The length and width of the ablation pits on the test sample surface are used to reflect the corresponding laser spot size. If the laser incident angle is 0°, the laser ablation pit is circular, and the length and width of the laser spot are both the diameter of the circular ablation pit. If the laser incident angle is not 0°, the laser ablation pit is elliptical. The major axis of the ellipse is recorded as the laser spot length, and the minor axis as the laser spot width.

[0066] S13: Calculate the laser spot power density.

[0067] Specifically, based on average power P Pulse width repetition frequency Q Length of ablation pit aWidth of the burn pit b The power density of the laser spot is calculated using the following formula:

[0068]

[0069] in, I The light spot power density is expressed in W / mm². 2 ; a The length of the ablation pit is in mm; b Width of the ablation pit, in mm; P The average power of the laser is expressed in watts (W). Pulse width, in nanoseconds (ns); Q The repetition frequency is expressed in Hz. Pi is a constant.

[0070] S14: Summarize the laser spot size and power density detected under different combinations of laser parameters (power, pulse width, repetition frequency, defocusing amount, and incident angle) to create a mapping data table of laser spot size and power density corresponding to the laser parameters. The selection of power, pulse width, repetition frequency, defocusing amount, and incident angle should include all available parameter combinations to ensure that the data sample size of the mapping data table is large enough for easy subsequent lookup.

[0071] S2: Establish a mapping model of the relationship between laser spot power density, pulse width, laser incident angle, and the depth of ablation pits on the diamond surface. The specific method is as follows:

[0072] S21: Using a laser, single-point single-pass ablation tests are performed on the surface of a diamond sheet under different combinations of laser spot power density, pulse width, and laser incident angle. That is, the diamond surface is ablated once by lasers with different combinations of laser spot power density, pulse width, and laser incident angle.

[0073] S22: The depth of ablation pits created on the surface of a diamond sheet under different parameter combinations is measured using a precision 3D profile inspection instrument. Three depth measurements are performed on each individual ablation pit. A confocal profilometer can be used as the precision 3D profile inspection instrument. The depth of the laser ablation pit is determined by three factors: laser spot power density, pulse width, and laser incident angle.

[0074] If the laser incident angle is 0°, the ablation pit created by the laser will be circular, and the depth inside the ablation pit will be consistent. The average value of three depth measurements will be taken during the measurement.

[0075] If the laser incident angle is not 0°, the ablation pit created by the laser will be elliptical. The depth inside the elliptical ablation pit is inconsistent, with shallow depths at both ends of the major axis and deep depths in the middle. During measurement, the depth should be measured once at the beginning, middle, and end of the major axis of the elliptical ablation pit, and the depth values ​​should be recorded in three segments according to the major axis. Recording the depth values ​​in three segments helps to improve the accuracy of laser polishing result prediction.

[0076] S23: Regression analysis was performed on the laser spot power density and the depth of ablation pits on the diamond surface under different incident angles and pulse widths, and the mapping relationship model diagram was obtained.

[0077] Specifically, when the laser incident angle is 0°:

[0078] S231.1: The laser spot power density is set as the X-axis and the ablation pit depth is set as the Z-axis. The laser spot power density is taken in an equally spaced incremental manner. Nonlinear regression analysis is performed on different laser spot power densities and corresponding ablation pit depths under the same pulse width conditions. The fitting curve I is obtained by B-spline fitting. The fitting curve I obtained by B-spline fitting is smoother and has better continuity.

[0079] S231.2: When the laser incident angle is 0°, the ablation pit is circular. The ablation pit depth is a fixed value. For different laser spot power densities under various pulse width conditions, nonlinear regression analysis is performed using B-spline fitting with the corresponding ablation pit depth to obtain multiple fitting curves.

[0080] S231.3: Using the pulse width as the Y-axis, plot the fitting curve obtained in step S231.2 in a three-dimensional rectangular coordinate system I to obtain a model diagram of the mapping relationship between laser spot power density, pulse width and ablation pit depth when the laser incident angle is 0°.

[0081] S231.4: Repeat steps S231.1 to S231.3 to obtain a mapping model of the relationship between laser spot power density, pulse width and ablation pit depth for each available laser incident angle parameter.

[0082] When the laser incident angle is not 0°:

[0083] S232.1: Given a specific laser incident angle, nonlinear regression analysis is performed using B-spline fitting for different laser spot power densities and corresponding three-segment ablation pit depths under the same pulse width conditions. The laser spot power density is set in an equally spaced increasing manner, with the laser spot power density as the X-axis and the ablation pit depth as the Z-axis. When the laser incident angle is not 0°, the ablation pit is elliptical, and the corresponding ablation pit depth has three segments, resulting in three fitting curves for the three-segment ablation pit depth values.

[0084] S232.2: Nonlinear regression analysis was performed on the laser spot power density and the corresponding ablation pit depth under various pulse width conditions. The three-segment depth values ​​of the corresponding ablation pit were fitted with B-spline to obtain three fitting curves.

[0085] S232.3: Using the pulse width as the Y-axis, plot the fitting curve obtained in step S232.2 in the same three-dimensional rectangular coordinate system II. This will yield a model diagram showing the mapping relationship between the laser spot power density and pulse width and the three-segment depth value of the ablation pit under a specific laser incident angle.

[0086] S232.4: Repeat the above method to obtain a mapping model of the relationship between laser spot power density and pulse width and the three-segment depth value of the ablation pit for each available laser incident angle parameter.

[0087] In nonlinear regression analysis, B-spline fitting is used to smooth the dataset of laser spot power density and corresponding ablation pit depth. The optimal B-spline fit is calculated by minimizing the residuals according to the following equation. x Values ​​and best B-spline fit z The value is used to obtain the best-fit curve.

[0088]

[0089] In the formula, N It is the number of data points used in the fitting process. w i It is the weight of the first i 1 element, ( x i , z i ) is the first of the data sequences involved in the fitting process. i A pair of values, ( x i ' , z i ' ) is the th best B-spline fit i For each pair of values, the norm vector is calculated using the norm sign (||) at both ends of the function. The B-spline fitting curve is established using the standard B-spline basic function. Using nonlinear regression analysis for data fitting allows for the continuity of the relationship between laser spot power density and the corresponding ablation pit depth. B-spline fitting is a high-order, nonlinear curve fitting method that produces smoother curves with good locality and continuity, making it particularly suitable for fitting and analyzing complex curve relationships in this scheme.

[0090] S3: Construct an analytical model for the stacking state of laser spots. The specific steps are as follows:

[0091] S31: Based on the mapping relationship data table created in step S14 and the obtained mapping relationship model diagram obtained in S23, obtain the laser spot length, laser spot width, laser spot power density, and diamond surface ablation pit depth under specific parameter combinations of power, pulse width, repetition frequency, defocusing amount, and incident angle. Generate a proportionally sized simulated spot pattern based on the laser spot length and width, and within the simulated spot pattern, every 1μm... 2 A pixel is uniformly placed within a certain range, with an adjacent pixel spacing of 1μm. Each pixel within the simulated light spot pattern is assigned the corresponding diamond surface ablation pit depth value. If it is a circular light spot, each pixel is assigned the same diamond surface ablation pit depth value; if it is an elliptical light spot, the pixels at the corresponding positions are assigned the ablation pit depth values ​​in a three-segment manner: pixels in the front segment of the major axis are assigned the depth value at the beginning of the ellipse's major axis, pixels in the middle segment of the major axis are assigned the depth value at the middle of the ellipse's major axis, and pixels in the rear segment of the major axis are assigned the depth value at the end of the ellipse's major axis.

[0092] S32: Based on the horizontal scanning rate and vertical stepping interval of the laser spot, calculate the horizontal spot overlap rate and the vertical spot overlap rate, set the two-dimensional plane of the diamond polished surface, and arrange the simulated spot pattern in the two-dimensional plane according to the horizontal spot overlap rate and the vertical spot overlap rate to obtain a rectangular two-dimensional plane pixel pattern.

[0093] Specifically, such as Figure 2 As shown, in laser polishing of diamond, the laser spot moves and scans the diamond polishing surface in a zigzag pattern with multiple parallel straight lines under the action of a high-speed galvanometer or motion platform, so that the laser spot is evenly distributed on the diamond polishing surface.

[0094] Based on the lateral scanning rate of the laser spot V s Longitudinal step interval T w Calculate the overlap rate of the light spots in the horizontal and vertical directions:

[0095]

[0096] in, V s This refers to the lateral scanning rate of the laser spot. T w The longitudinal step interval of the laser spot. a The length of the laser spot. b The width of the laser spot. Q The repetition frequency, This refers to the lateral beam overlap rate. This refers to the longitudinal beam overlap rate;

[0097] like Figure 3 As shown, simulated light spot patterns are arranged in a two-dimensional plane according to the horizontal and vertical light spot overlap rates. The center distance between two adjacent horizontal light spots is... The center distance between two adjacent light spots in the longitudinal direction is T w .

[0098] S33: Adjust the pixel values ​​according to the overlap of the simulated light spot pattern in the two-dimensional plane pixel graphic. If a pixel does not overlap with other pixels, the pixel value remains unchanged. If a pixel overlaps with at least one other pixel, the overlapping pixel is converted into a new pixel. The new pixel is assigned the sum of the values ​​of the overlapping pixels. After adjusting the pixel values ​​of the two-dimensional plane pixel graphic, generate a height map of the simulated light spot stacking state based on the pixel values ​​of the two-dimensional plane pixel graphic.

[0099] In the height map, numerical values ​​are represented using color gradients or shades of color. The values ​​in the height map correspond to the pixel values ​​of the two-dimensional planar pixel graphic, representing the simulated depth of laser beam irradiation. Larger values ​​indicate greater laser beam irradiation depth, and correspondingly, lower terrain elevation. The numerical values ​​in the height map correspond one-to-one with the pixel positions of the two-dimensional planar pixel graphic. Height maps showing the simulated beam stacking state under different parameters are shown below. Figure 4 As shown, from Figure 4 The process can produce horizontal lines, vertical lines, dotted pits, and relatively uniform stacking states of different light spots. The height map is an intuitive representation of the pixel values ​​of a two-dimensional planar pixel graphic, and it is a necessary step to inherit the two-dimensional planar pixel graphic and lead to the subsequent simulation image of the micro-topography of the polished surface.

[0100] S4: Generate a simulated image of the microscopic topography of the laser-polished diamond surface. The specific steps are as follows:

[0101] S41: The maximum and minimum values ​​of the pixel points assigned in the light spot stacking state height map generated in step S33 are added together and divided by two to obtain the median surface value of the light spot stacking state height map. The median surface value is then subtracted from the assigned value of each pixel point in the light spot stacking state height map to obtain the light spot stacking state height map with the median surface set to zero.

[0102] S42: Invert the values ​​in the height map of the simulated light spot stacking state with the median plane zeroed out, that is, take the negative value of all values ​​in the height map to replace the original value, and obtain the height map after the inversion operation.

[0103] S43: Generate a simulated image of the micro-topography of the laser-polished diamond surface based on the height map after the inversion operation.

[0104] The method for generating a simulated image of the micro-topography of the laser-polished diamond surface in step S43 is as follows:

[0105] All values ​​in the heightmap after the inversion operation in step S42 are taken as Z values, and position coordinates X and Y values ​​are added one by one according to the corresponding positions of all values ​​in the heightmap. The X and Y values ​​of the first value point at the lower left corner of the heightmap are both set to 0, and the X and Y values ​​of other pixels are increased sequentially, all of which are positive values. The difference between the X and Y values ​​of adjacent value points is 1 μm. Each Z value and its X and Y coordinates can determine a scatter point in a three-dimensional rectangular coordinate system. All Z values ​​and their coordinates are represented as scatter points and displayed in the three-dimensional rectangular coordinate system III. Adjacent scatter points are connected to form a surface, and the obtained three-dimensional graphic is a simulated image of the micro-topography of the laser-polished diamond surface.

[0106] S5: Predict the surface roughness of laser-polished diamond. The specific steps are as follows:

[0107] S51: Export the X, Y, and Z coordinates of all scattered points in the simulated image of the micro-topography of the laser-polished diamond surface in sequence. Calculate the arithmetic mean of all Z-value data. The plane parallel to the XY plane of the three-dimensional rectangular coordinate system III and equal to the arithmetic mean on the Z-axis is taken as the contour mid-surface of the simulated image of the micro-topography of the laser-polished diamond surface. Calculate the surface roughness value of the laser-polished diamond surface using the three-dimensional surface roughness evaluation method of the simulated image contour surface morphology.

[0108] S 'a' represents the surface arithmetic mean height, which is the arithmetic mean of the distances between points on the contour surface and the mid-surface. Within the sampling area, it is the arithmetic mean of the absolute Z-values ​​between the contour surface and the established contour mid-surface. The mathematical expression is shown below.

[0109]

[0110] In the formula, l x 、l y M, N Indicates the sampling area range. The contour surface of a simulated image representing the microscopic topography of a laser-polished diamond surface. The mid-surface of the contour image representing the micro-topography of a laser-polished diamond surface.

[0111] S z represents the height at ten points on the surface, which is the sum of the average absolute values ​​of the heights of the peaks from the highest point to the fifth peak on the contour surface, and the average absolute values ​​of the heights of the troughs from the lowest point to the fifth trough. The mathematical expression is shown below.

[0112]

[0113] In the formula, The distance from the contour surface to the mid-surface is the height of the peaks decreasing from the highest peak to the fifth peak. The height of the troughs increases from the lowest trough on the contour surface to the fifth trough.

[0114] remove S a and S In addition to z, other characterization parameters can be calculated based on the specifications for the three-dimensional characterization parameters of the profile surface in the surface roughness standard, thereby obtaining the surface roughness prediction results of the laser-polished diamond surface.

[0115] S52: Predicted line roughness.

[0116] The Z-values ​​and X-values ​​or Y-values ​​of scatter points in a specific row or column of a simulated image of the micro-topography of a laser-polished diamond surface are sequentially exported. The arithmetic mean of all Z-values ​​for that row or column is calculated. A straight line parallel to the X-axis or Y-axis and equal to this arithmetic mean on the Z-axis is used as the roughness evaluation line. The line roughness value of the laser-polished diamond surface is then calculated according to the evaluation method of the line roughness standard, including but not limited to... R a and R z.

[0117] R 'a' represents the arithmetic mean deviation of the contour line, which is the arithmetic mean of the distances between points on the contour line and the center line, and the arithmetic mean of the absolute Z-values ​​between the contour line and the center line within the sampling length.

[0118] R z is the ten-point average height of the contour line, which is the sum of the average absolute height of the peaks from the highest peak to the fifth peak and the average absolute height of the troughs from the lowest peak to the fifth trough.

[0119] S a, S z、 R a and R z are all commonly used indicators in roughness assessment. Through analysis of... S a, S z、 R a and R z can be used to predict the surface roughness of laser-polished diamond, and the prediction of surface roughness can also provide leading data reference for the selection of laser polishing process parameters.

[0120] The above steps and algorithms are programmed into simulation analysis software using the LabVIEW programming language. The computer automatically executes the analysis and processing algorithms of the above steps to obtain simulated images of the micro-topography of the laser-polished diamond surface and predicted roughness values.

[0121] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for simulating and predicting the microstructure and roughness of laser-polished diamond surfaces, characterized in that, Includes the following steps: S1: Under different laser parameters, a single point is created on the test sample to form an ablation pit as a reflection of the laser spot size. The laser spot size is obtained and the laser spot power density is calculated. A mapping relationship data table between laser parameters and laser spot size and laser spot power density is created. S2: A single-point, single-pass ablation test was conducted on the surface of a diamond sheet to establish a mapping relationship model between the laser spot power density and the depth of the ablation pit on the diamond surface under different pulse widths and laser incident angles. S3: Construct an analytical model of the laser spot stacking state based on the mapping relationship data table and mapping relationship model diagram; The method for constructing the analytical model of the laser spot stacking state in step S3 is as follows: S31: Based on the mapping relationship data table created in step S1 and the obtained mapping relationship model diagram obtained in step S2, obtain the laser spot length, laser spot width, laser spot power density and diamond surface ablation pit depth under the parameter combination conditions of power, pulse width, repetition frequency, defocus amount and incident angle. Generate a simulated spot pattern of equal size according to the laser spot length and laser spot width, and uniformly set pixels inside the simulated spot pattern. The distance between adjacent pixels is set to λ. Assign the value of the corresponding diamond surface ablation pit depth to each pixel in the simulated spot pattern. S32: Based on the horizontal scanning rate and vertical step interval of the laser spot, calculate the horizontal spot overlap rate and the vertical spot overlap rate, set the two-dimensional plane of the diamond polishing surface, and arrange the simulated spot pattern in the two-dimensional plane according to the horizontal spot overlap rate and the vertical spot overlap rate to obtain a rectangular two-dimensional plane pixel pattern. S33: Adjust the pixel values ​​according to the overlap of the simulated light spot graphics within the two-dimensional plane pixel graphics. If a pixel is not in the overlapping area of ​​the simulated light spot graphics, the pixel value remains unchanged. If a pixel is in the overlapping area of ​​the simulated light spot graphics, the pixels in the overlapping area are superimposed and converted into new pixels. The new pixel value is the sum of the pixel values ​​of the corresponding pixels in the overlapping area of ​​the simulated light spot graphics. After adjusting the pixel values ​​of the two-dimensional plane pixel graphics, generate a height map of the simulated light spot stacking state based on the pixel values ​​of the two-dimensional plane pixel graphics. S4: Using an analytical model of laser spot stacking, a simulated image of the micro-topography of the laser-polished diamond surface is generated; S5: Predict the surface roughness of laser-polished diamond based on the contour mid-surface of the simulated image of the micro-topography of the laser-polished diamond surface.

2. The method for simulating and predicting the microstructure and roughness of laser-polished diamond surfaces according to claim 1, characterized in that, The method for creating the mapping relationship data table between laser parameters and laser spot size and laser spot power density, as described in step S1, is as follows: S11: Under different combinations of laser parameters such as power, pulse width, repetition frequency, defocusing amount, and incident angle, a laser is used to perform single-point single-shot sampling on the surface of the test sample. S12: For the ablation pits formed under different combinations of laser parameters on the test sample, the length and width of each ablation pit are detected one by one using a precision three-dimensional contour detection instrument, which serves as a reflection of the corresponding laser spot size. S13: Calculate the laser spot power density using average power, pulse width, repetition frequency, and laser spot size; S14: Summarize the laser spot size and laser spot power density detected under different combinations of laser parameters such as power, pulse width, repetition frequency, defocusing amount, and incident angle, and create a mapping data table of laser spot size and laser spot power density corresponding to different laser parameters.

3. The method for simulating and predicting the microstructure and roughness of laser-polished diamond surfaces according to claim 2, characterized in that, The method for detecting the length and width of the ablation pit in step S12 is as follows: if the laser incident angle is 0°, the laser ablation pit is circular, and the length and width of the laser ablation pit are both the diameter of the circle. If the laser incident angle is not 0°, the laser ablation pit is elliptical. The major axis of the ellipse is recorded as the length of the laser ablation pit, and the minor axis of the ellipse is recorded as the width of the laser ablation pit.

4. The method for simulating and predicting the microstructure and roughness of laser-polished diamond surfaces according to claim 3, characterized in that, Step S2 establishes the mapping relationship model between laser spot power density, pulse width, laser incident angle, and the depth of ablation pits on the diamond surface as follows: S21: Using a laser, single-point single-time ablation tests were performed on the surface of a diamond sheet under different combinations of laser spot power density, pulse width, and laser incident angle. S22: The depth of the ablation pits formed under different parameter combinations on the surface of the diamond sheet is detected. The depth of a single ablation pit is measured three times. If the laser incident angle is 0°, the average value of the three depth measurements is taken. If the laser incident angle is not 0°, the depth is measured once at the beginning, middle and end of the major axis of the elliptical ablation pit, and the depth value of the three equally divided segments is recorded. S23: Regression analysis was performed on the laser spot power density and the depth of ablation pits on the diamond surface under different incident angles and pulse widths, and the mapping relationship model diagram was obtained.

5. The method for simulating and predicting the microstructure and roughness of laser-polished diamond surfaces according to claim 4, characterized in that, Step S23: The method for performing regression analysis and obtaining the mapping relationship model diagram is as follows: When the laser incident angle is 0°: S231.1: Nonlinear regression analysis was performed on different laser spot power densities and corresponding ablation pit depths under the same pulse width conditions. The laser spot power density was taken as an equally spaced increasing value. The laser spot power density was the X-axis and the ablation pit depth was the Z-axis. The fitting curve I was obtained by B-spline fitting. S231.2: Nonlinear regression analysis was performed on the laser spot power density and corresponding ablation pit depth under various pulse width conditions to obtain multiple fitting curves; S231.3: Using the pulse width as the Y-axis, plot the fitting curve obtained in step S231.2 in a three-dimensional rectangular coordinate system I to obtain a model diagram of the mapping relationship between the laser spot power density and the pulse width and the ablation pit depth when the laser incident angle is 0°. S231.4: Repeat steps S231.1 to S231.3 to obtain a model diagram of the mapping relationship between laser spot power density, pulse width and ablation pit depth for each available laser incident angle; When the laser incident angle is not 0°: S232.1: Set the laser incident angle, and perform nonlinear regression analysis on different laser spot power densities and corresponding ablation pit three-segment depth values ​​under the same pulse width conditions. The laser spot power density is taken as an equally spaced increasing value. The laser spot power density is the X-axis and the ablation pit depth is the Z-axis. The corresponding ablation pit three-segment depth values ​​are fitted with B-splines to obtain three fitting curves. S232.2: Nonlinear regression analysis was performed on the laser spot power density and the corresponding ablation pit depth under various pulse width conditions, and three fitting curves were obtained for the three-segment depth values ​​of the ablation pit. S232.3: Using the pulse width as the Y-axis, plot the fitting curve obtained in step S232.2 in the same three-dimensional rectangular coordinate system II to obtain the mapping relationship model between the laser spot power density and pulse width and the three-segment depth value of the ablation pit under the laser incident angle condition; S232.4: Repeat steps S232.1 to S232.3 to obtain a mapping model of the laser spot power density and pulse width to the three-segment depth of the ablation pit for each available laser incident angle.

6. The method for simulating and predicting the microstructure and roughness of laser-polished diamond surfaces according to any one of claims 1-5, characterized in that, The method for arranging simulated light spot patterns in a two-dimensional plane according to the lateral and longitudinal light spot overlap rates, as described in step S32, is as follows: based on the lateral scanning rate of the laser light spot... Longitudinal step interval T w Calculate the overlap rate of the light spots in the horizontal and vertical directions respectively: in, This refers to the lateral scanning rate of the laser spot. T w The longitudinal step interval of the laser spot. a The length of the laser spot. b The width of the laser spot. Q The repetition frequency, This refers to the lateral beam overlap rate. This refers to the longitudinal beam overlap rate; Based on the horizontal spot overlap rate Overlap rate with longitudinal light spot Simulated light spot patterns are arranged in a two-dimensional plane, with the center-to-center distance between two adjacent light spots being [value missing]. The center distance between two adjacent light spots in the longitudinal direction is .

7. The method for simulating and predicting the microstructure and roughness of laser-polished diamond surfaces according to claim 6, characterized in that, The method for generating a simulated image of the micro-topography of the laser-polished diamond surface in step S4 is as follows: S41: Obtain the maximum and minimum values ​​of the pixel values ​​assigned in the height map of the light spot stacking state generated in step S33. Add the maximum and minimum values ​​and divide by two to obtain the median surface value of the height map of the light spot stacking state. Subtract the median surface value from the assigned value of each pixel in the height map of the light spot stacking state to obtain the simulated height map of the light spot stacking state with the median surface set to zero. S42: Invert the values ​​in the height map of the simulated spot stacking state with the mid-plane zeroed out to obtain the height map after inversion. S43: Generate a simulated image of the micro-topography of the laser-polished diamond surface based on the height map after the inversion operation.

8. The method for simulating and predicting the microstructure and roughness of laser-polished diamond surfaces according to claim 7, characterized in that, The method for generating a simulated image of the micro-topography of the laser-polished diamond surface in step S43 is as follows: All values ​​in the height map after the inversion operation in step S42 are taken as Z values. Then, position coordinates X and Y values ​​are added one by one according to the corresponding position of each value in the height map. Set the X and Y values ​​of the first value point at the lower left corner of the height map to 0. The X and Y values ​​of other pixels are increased sequentially. The X and Y values ​​are all positive. The difference between the X and Y values ​​of adjacent value points is λ. Each Z value and its X and Y coordinates can determine a scatter point in the three-dimensional rectangular coordinate system. All Z values ​​and their coordinates are represented as scatter points and displayed in the three-dimensional rectangular coordinate system III. Adjacent scatter points are connected to form a surface. The obtained three-dimensional graphic is the simulated image of the micro-landscape of the laser-polished diamond surface.

9. The method for simulating and predicting the microstructure and roughness of laser-polished diamond surfaces according to claim 7 or 8, characterized in that, The method for predicting the surface roughness of laser-polished diamond in step S5 is as follows: S51: Export the X, Y, and Z coordinates of all scattered points in the simulated image of the micro-topography of the laser-polished diamond surface in step S43, calculate the arithmetic mean of all Z value data, and take the plane that is parallel to the XY plane of the three-dimensional rectangular coordinate system III and equal to the arithmetic mean on the Z axis as the contour mid-surface of the simulated image of the micro-topography of the laser-polished diamond surface, and calculate the surface roughness value of the laser-polished diamond surface using the three-dimensional surface roughness evaluation method of the contour surface morphology of the simulated image. S52: Export the Z-values ​​and X-values ​​or Y-values ​​of the scattered points in the row or column of the simulated image of the micro-topography of the laser-polished diamond surface in sequence. Calculate the arithmetic mean of all Z-values ​​for that row or column of data. Use the straight line parallel to the X-axis or Y-axis and equal to the arithmetic mean on the Z-axis as the roughness evaluation midline. Then calculate the line roughness value of the laser-polished diamond surface according to the evaluation method of the line roughness standard.

Images