A processing method and system for flatness photomask substrate
By scanning the substrate surface with a laser interferometer and fitting it with the least squares method, combined with counterweights and annealing, the problem of minute undulations on the photomask substrate surface was solved, achieving efficient and precise substrate flatness and reducing material loss and processing steps.
Patent Information
- Application Number
- CN202610598960.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-04-30
- Publication Date
- 2026-07-14
AI Technical Summary
Existing technologies in photomask substrate processing cannot effectively solve the wavefront aberration problem caused by minute surface undulations, resulting in uneven linewidth and misalignment of photolithographic patterns, and the abrasion process causes significant substrate damage.
A flatness map is generated by scanning the substrate surface with a laser interferometer. The reference plane data is then fitted using the least squares method. Deviation points are calculated, and counterweights are applied for flattening. Combined with annealing to eliminate stress, multiple polishing processes are avoided.
It achieves efficient and precise substrate flattening, reduces material waste, simplifies the processing flow, and avoids over-processing and edge correction effects.
Smart Images
Figure CN122386574A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of photomask substrate processing technology, and specifically to a method and system for processing a photomask substrate with flatness. Background Technology
[0002] With the evolution of advanced process technologies such as extreme ultraviolet (EUV) lithography, chip manufacturing has placed extremely stringent requirements on the surface flatness of photomask substrates. Any slight local undulations may cause wavefront aberrations in the projection lens, resulting in uneven linewidth, misalignment, or even fatal defects in the lithographic pattern, severely restricting the yield and performance limits of chip manufacturing.
[0003] Existing technologies typically apply uniform pressure to the entire substrate, relying on the difference in grinding amount caused by the height difference on the substrate surface to make the substrate flat after grinding. The flatness effect after grinding places too high requirements on the substrate material, and in order to ensure the accuracy of the flatness of the substrate after grinding, multiple rounds of "rough polishing-fine polishing-final polishing" are usually required, which causes a lot of damage to the substrate. Summary of the Invention
[0004] The purpose of this invention is to provide a method and system for processing photomask substrates with high flatness, so as to overcome the above-mentioned shortcomings in the prior art.
[0005] To achieve the above objectives, the present invention provides the following technical solution: a method for processing a flatness photomask substrate, comprising the following steps:
[0006] S1. After cleaning the substrate to remove particles, oil, or residues from the substrate surface, the substrate surface is scanned using a laser interferometer to generate a flatness map.
[0007] S2. Using the least squares method, perform plane fitting on the non-edge data in the flatness Map to obtain the substrate reference plane data;
[0008] S3. Based on the flatness map and substrate reference plane data, calculate the deviation between the substrate and the substrate reference plane data, collect the flatness map coordinates where the deviation is greater than the set deviation threshold, and generate a target deviation point data set.
[0009] S4. Determine whether the number of data in the target deviation point data set is greater than or equal to 1. If not, the substrate is qualified; if yes, proceed to the next step.
[0010] S5. Collect the parameter data required for calibration, analyze and process the mass of the counterweight block to be applied at the corresponding position of the target deviation point data in the target deviation point data set, and obtain the corresponding target deviation point counterweight block mass data.
[0011] S6. Based on the target deviation point counterweight mass data and the corresponding flatness Map coordinates, apply a counterweight block with the corresponding counterweight mass at the corresponding coordinate position of the substrate.
[0012] S7. After applying the counterweight, the substrate is flattened and then returned to S1.
[0013] Furthermore, S2 includes the following steps:
[0014] S2.1. In the flatness map, set the coordinate points within the edge exclusion width (e.g., 5-10% of the substrate diameter or a fixed width such as 5-8 mm) to generate a non-edge flatness map from the remaining coordinate points in the flatness map.
[0015] S2.2. Based on the coordinate points within the non-edge flatness map, construct the reference plane equation: Where z, x, and y are the height, x, and y coordinates of the non-edge flatness Map, respectively, and a, b, and c are the parameters to be solved.
[0016] S2.3. Using the least squares method, minimize the sum of squares of the differences between the z-values output by the reference plane equations corresponding to any x and y in the non-edge flatness Map and the actual z-values in the non-edge flatness Map to generate substrate reference plane data, i.e., the reference plane equations determined by the values of a, b, and c.
[0017] Furthermore, S3 includes the following steps:
[0018] S3.1 Calculate the deviation between the height coordinate (i.e., z-axis coordinate) of each coordinate in the flatness Map and the height coordinate of the same coordinate (i.e., x-axis and y-axis coordinate) in the substrate reference plane data to obtain the corresponding coordinate deviation data;
[0019] S3.2 Compare each coordinate deviation data with the set deviation threshold to determine whether it is greater than the set deviation threshold;
[0020] S3.3 If so, then set the flatness Map coordinates corresponding to the coordinate deviation data as the target deviation point data, and collect all target deviation point data to generate a target deviation point data set. Further, the coordinate deviation data = flatness Map height coordinate - substrate reference plane data height coordinate. If the coordinate deviation data is positive, it indicates that there is a protrusion at the corresponding coordinate position on the substrate, and the protrusion height is the coordinate deviation data value; if the coordinate deviation data is negative, it indicates that there is a depression at the corresponding coordinate position on the substrate, and the depression depth is the absolute value of the coordinate deviation data. This invention only processes protrusion defects.
[0021] Furthermore, S5 includes the following steps:
[0022] S5A.1. Collect the elastic modulus, Poisson's ratio, and thickness of the substrate; wherein, the elastic modulus and Poisson's ratio of the substrate can be obtained from the physical property data sheet provided by the material supplier, or measured by standard material mechanics experiments (such as ultrasonic method, bending resonance method); the thickness of the substrate can be obtained from the substrate processing specifications, or measured by a precision thickness gauge (such as a dual-probe interferometer or contact thickness gauge) before processing.
[0023] S5A.2. Based on Kirchhoff-Love thin plate theory, the bending stiffness of the substrate is calculated using the elastic modulus, Poisson's ratio, and thickness.
[0024] S5A.3. Based on the target deviation point data set, the defect area, equivalent feature size, and target deformation are extracted. Specifically, the 8-connected component labeling algorithm in image processing can be used to identify each independent defect region in the target deviation point data set. Then, the total number of pixels contained in each defect region is counted, and combined with the pixel size calibration of the measurement system, the actual physical area of the region, i.e., the defect area, is calculated. Assuming that the effect of each defect region can be approximated as a circular region of equal area, its equivalent radius is calculated to obtain the equivalent feature size. Target deformation = target deviation point data - deviation threshold.
[0025] S5A.4. Based on Kirchhoff-Lov thin plate theory, a dimensionless correction factor pre-calibrated through finite element analysis is introduced. Combined with the bending stiffness, equivalent characteristic size, and target deformation, the required unit area pressure is calculated. Specifically, a base plate, support, and local loading model completely consistent with the actual processing platform can be established using finite element analysis software. Then, a known pressure is applied to a circular region of known area in the model, and the deformation generated at its center is simulated and calculated. The result is obtained through the formula: Correction factor = (Deformation × Bending stiffness) / (Known pressure × Radius of the circular region of known area^2).
[0026] S5A.5. Based on the static equilibrium equation, the mass of the counterweight is calculated using the defect area and pressure per unit area to obtain the mass data of the counterweight block at the target deviation point.
[0027] Furthermore, S6 and S7 include the following steps:
[0028] S6A. Place the substrate on a support bearing plate of the gravity leveling device that is resistant to the annealing temperature, and make the substrate protrusion corresponding to the target deviation point data set face downwards. Apply counterweights corresponding to the target deviation point counterweight mass data at all target deviation point data points in the target deviation point data set on the upper surface of the substrate, so that the protrusions press on the support bearing plate. The support bearing plate is a bearing plate with extremely high flatness (about one order of magnitude higher than the flatness requirement of the substrate) that has been precisely leveled and is resistant to the annealing temperature.
[0029] S7A. Place the support plate containing the substrate with the applied counterweight into the annealing furnace. Heat the substrate to its annealing point temperature within the set heating time range and hold for the set holding time. After the substrate undergoes permanent plastic deformation under the action of the counterweight, slowly cool it to room temperature in the furnace at a set cooling rate, then remove it, remove the counterweight, and return to S1. Furthermore, the annealing furnace can be selected with temperature uniformity better than ±3 degrees Celsius, temperature control accuracy better than ±1 degree Celsius, and multiple-segment eccentric temperature profiles for precise control of heating, holding, and cooling rates. Even further, an annealing furnace using high-purity materials (such as high-purity quartz, graphite, and silicon carbide) for the furnace lining and heating elements can be selected to prevent secondary contamination such as metal ions.
[0030] Furthermore, S5 includes the following steps:
[0031] S5B.1. Obtain the polishing base pressure, relative linear velocity, standard polishing time, and system Preston constant; all parameters are taken from the equipment's standard processing parameter table and are fixed.
[0032] S5B.2. Based on the largest target deviation point data in the target deviation point data set, the defect area is analyzed and extracted, and the target removal amount of the corresponding deviation point is calculated in conjunction with the set deviation threshold so that the deviation of the corresponding point just meets the set deviation threshold. This allows the target removal amount of the deviation point to be removed during the subsequent polishing and grinding process so that the point just enters the tolerance zone and avoids unnecessary material loss.
[0033] S5B.3. Based on the relative linear velocity, standard polishing time, and system Preston constant, calculate the global conversion coefficient. Global conversion coefficient = system Preston constant × relative linear velocity × standard polishing time.
[0034] S5B.4. Based on the Preston material removal equation, the additional unit area pressure to be applied is calculated using the target removal amount at the deviation point and the global conversion coefficient.
[0035] S5B.5. Based on the static equilibrium equation, using the additional unit area pressure and defect area, calculate the required mass of the counterweight and obtain the mass data of the counterweight at the target deviation point.
[0036] Furthermore, S6 and S7 include the following steps:
[0037] S6B. Place the substrate on the support platform of the gravity leveling device, and make the substrate protruding downwards, corresponding to the largest target deviation point data in the target deviation point data set. Apply a counterweight block with the corresponding target deviation point counterweight block mass data to the largest target deviation point data in the target deviation point data set on the upper surface of the substrate.
[0038] S7B: Press the underside of the substrate after applying the counterweight onto the polishing disc of a chemical mechanical polishing (CMP) machine, run the polishing program, and use the additional pressure generated by the counterweight to selectively remove material from the raised area, so that the raised area is precisely ground to the target removal amount of the deviation point, remove the counterweight, and return to S1.
[0039] A processing system for a flatness photomask substrate includes a laser interferometer, a data storage module, a smart chip, a gravity flattening device, and a display.
[0040] The output of the laser interferometer is connected to the data storage module for measuring the flatness map of the substrate and transmitting the measured flatness map data to the data storage module for storage.
[0041] The data storage module is also used to store computer programs, with its input end connected to a laser interferometer and its output end connected to a smart chip.
[0042] The input end of the smart chip is connected to the data storage module, and the output end is connected to the gravity leveling device and the display respectively. It is used to run the computer program, execute the processing method of the flatness photomask substrate according to the claim, and send control commands to the gravity leveling device according to the processing results.
[0043] The input end of the gravity leveling device is connected to a smart chip, which is used to apply a counterweight of appropriate mass to the corresponding position of the substrate according to the processing result of the smart chip, and to perform leveling treatment on the substrate.
[0044] The input terminal of the display is connected to the smart chip, which is used to visualize the processing results of the smart chip.
[0045] Beneficial effects:
[0046] Compared with the prior art, the present invention provides a processing method and system for flatness photomask substrates. By collecting and scanning the substrate to obtain a map image, the bumps of the substrate are analyzed, and the mass of the counterweight block required to flatten the bumps is calculated. By applying the corresponding mass of counterweight block to the bump position to perform force leveling, and then performing a cycle of stress elimination through tempering and shaping, the flatness of the substrate is ensured while avoiding wear on the substrate.
[0047] Alternatively, by balancing and polishing only the highest convex point in each cycle, over-processing and repeated trial and error are avoided. The path planning is direct and efficient, and global issues such as edge correction that need to be considered in the iterative process of multiple rounds of "coarse polishing-fine polishing-final polishing" are avoided, simplifying the analysis process. Attached Figure Description
[0048] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.
[0049] Figure 1 The method steps provided by this invention are illustrated.
[0050] Figure 2 The system structure block diagram provided by the present invention. Detailed Implementation
[0051] To enable those skilled in the art to better understand the technical solution of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings.
[0052] Exemplary embodiments will be described more fully below with reference to the accompanying drawings; however, these exemplary embodiments may be embodied in different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will enable those skilled in the art to fully understand the scope of this disclosure.
[0053] Where there is no conflict, the various embodiments of this disclosure and the features thereof in the embodiments may be combined with each other.
[0054] As used herein, the term “and / or” includes any and all combinations of one or more related enumerated entries.
[0055] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. As used herein, the singular forms “a” and “the” are also intended to include the plural forms unless the context clearly indicates otherwise. It will also be understood that when the terms “comprising” and / or “made of” are used in this specification, the presence of the stated feature, integral, step, operation, element, and / or component is specified, but the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or groups thereof is not excluded.
[0056] The embodiments described herein can be described with reference to plan views and / or cross-sectional views using the ideal schematic diagrams of this disclosure. Therefore, the example illustrations can be modified according to manufacturing techniques and / or tolerances. Therefore, the embodiments are not limited to those shown in the drawings, but include modifications to configurations formed based on manufacturing processes. Therefore, the areas illustrated in the drawings are schematic in nature, and the shapes of the areas shown in the figures illustrate specific shapes of areas of an element, but are not intended to be limiting.
[0057] Unless otherwise specified, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art. It will also be understood that terms such as those defined in commonly used dictionaries should be interpreted as having the same meaning as they have in the context of the relevant art and this disclosure.
[0058] Please see Figure 1 A method for processing a flatness photomask substrate includes the following steps:
[0059] S1. After cleaning the substrate to remove particles, oil, or residues from the substrate surface, the substrate surface is scanned using a laser interferometer to generate a flatness map.
[0060] S2. Using the least squares method, perform plane fitting on the non-edge data in the flatness map to obtain the substrate reference plane data, including the following steps:
[0061] S2.1. In the flatness map, set the coordinate points within the edge exclusion width (e.g., 5-10% of the substrate diameter or a fixed width such as 5-8 mm) to generate a non-edge flatness map from the remaining coordinate points in the flatness map.
[0062] S2.2 Construct the reference plane equation based on the coordinate points within the non-edge flatness map: Where z, x, and y are the height, x, and y coordinates of the non-edge flatness Map, respectively, and a, b, and c are the parameters to be solved.
[0063] S2.3. Using the least squares method, minimize the sum of squares of the differences between the z-values output by the reference plane equations corresponding to any x and y in the non-edge flatness Map and the actual z-values in the non-edge flatness Map to generate substrate reference plane data, i.e., the reference plane equations determined by the values of a, b, and c.
[0064] S3. Based on the flatness map and substrate reference plane data, calculate and process the deviation between the substrate and the substrate reference plane data, collect the flatness map coordinates where the deviation is greater than the set deviation threshold, and generate a target deviation point data set, including the following steps:
[0065] S3.1 Calculate the deviation between the height coordinate (i.e., z-axis coordinate) of each coordinate in the flatness Map and the height coordinate of the same coordinate (i.e., x-axis and y-axis coordinate) in the substrate reference plane data, and obtain the corresponding coordinate deviation data;
[0066] S3.2 Compare each coordinate deviation data with the set deviation threshold to determine whether it is greater than the set deviation threshold;
[0067] S3.3 If so, then set the flatness Map coordinates corresponding to the coordinate deviation data as the target deviation point data, and collect all target deviation point data to generate a target deviation point data set. Further, the coordinate deviation data = flatness Map height coordinate - substrate reference plane data height coordinate. If the coordinate deviation data is positive, it indicates that there is a protrusion at the corresponding coordinate position on the substrate, and the protrusion height is the coordinate deviation data value; if the coordinate deviation data is negative, it indicates that there is a depression at the corresponding coordinate position on the substrate, and the depression depth is the absolute value of the coordinate deviation data. This invention only processes protrusion defects.
[0068] S4. Determine whether the number of data points in the target deviation point data set is greater than or equal to 1. If not, the substrate is qualified; if yes, proceed to the next step.
[0069] S5. Collect the parameter data required for calibration, analyze and process the mass of the counterweight block to be applied at the corresponding position of the target deviation point data in the target deviation point data set, and obtain the corresponding target deviation point counterweight block mass data.
[0070] S6. Based on the target deviation point counterweight mass data and the corresponding flatness Map coordinates, apply a counterweight block with the corresponding counterweight mass at the corresponding coordinate position of the substrate.
[0071] S7. After applying the counterweight, the substrate is flattened and then returned to S1.
[0072] In one embodiment, steps S5-S7 are as follows:
[0073] S5A.1. Collect the elastic modulus, Poisson's ratio, and thickness of the substrate; wherein, the elastic modulus and Poisson's ratio of the substrate can be obtained from the physical property data sheet provided by the material supplier, or measured by standard material mechanics experiments (such as ultrasonic method, bending resonance method); the thickness of the substrate can be obtained from the substrate processing specifications, or measured by a precision thickness gauge (such as dual-probe interferometer or contact thickness gauge) before processing.
[0074] S5A.2. Based on Kirchhoff-Love thin plate theory, the bending stiffness of the substrate is calculated using elastic modulus, Poisson's ratio and thickness.
[0075] S5A.3. Based on the target deviation point data set, the defect area, equivalent feature size, and target deformation are extracted. Specifically, the 8-connected component labeling algorithm in image processing can be used to identify each independent defect region in the target deviation point data set. Then, the total number of pixels contained in each defect region is counted, and combined with the pixel size calibration of the measurement system, the actual physical area of the region, i.e., the defect area, is calculated. Assuming that the effect of each defect region can be approximated as a circular region of equal area, its equivalent radius is calculated to obtain the equivalent feature size. Target deformation = target deviation point data - deviation threshold.
[0076] S5A.4. Based on Kirchhoff-Lov thin plate theory, a dimensionless correction factor pre-calibrated through finite element analysis is introduced. Combined with bending stiffness, equivalent characteristic size, and target deformation, the required pressure per unit area is calculated. Specifically, a base plate, support, and local loading model completely consistent with the actual processing platform can be established using finite element analysis software. Then, a known pressure is applied to a circular region of known area in the model, and the deformation generated at its center is simulated and calculated. The result is obtained through the formula: Correction factor = (Deformation × Bending stiffness) / (Known pressure × Radius of the circular region of known area^2).
[0077] S5A.5. Based on the static equilibrium equation, the mass of the counterweight is calculated using the defect area and pressure per unit area to obtain the mass data of the counterweight block at the target deviation point.
[0078] S6A. Place the substrate on a support bearing plate that can withstand the annealing temperature of the gravity leveling device, with the substrate protrusion corresponding to the target deviation point data set facing downwards. Apply counterweights corresponding to the target deviation point counterweight mass data at all target deviation point data points in the target deviation point data set on the upper surface of the substrate, so that the protrusions press on the support bearing plate. The support bearing plate is a bearing plate with extremely high flatness (about one order of magnitude higher than the flatness requirement of the substrate) that has been precisely leveled and can withstand the annealing temperature.
[0079] S7A. Place the support plate containing the substrate with the applied counterweight into the annealing furnace. Heat the substrate to its annealing point temperature within the set heating time range and hold for the set holding time. After the substrate undergoes permanent plastic deformation under the action of the counterweight, slowly cool it to room temperature in the furnace at a set cooling rate, then remove it, remove the counterweight, and return to S1. Furthermore, the annealing furnace can be selected with temperature uniformity better than ±3 degrees Celsius, temperature control accuracy better than ±1 degree Celsius, and multiple-segment eccentric temperature profiles for precise control of heating, holding, and cooling rates. Even further, an annealing furnace using high-purity materials (such as high-purity quartz, graphite, and silicon carbide) for the furnace lining and heating elements can be selected to prevent secondary contamination such as metal ions.
[0080] In another embodiment, steps S5-S7 are as follows:
[0081] S5B.1 Obtain the polishing base pressure, relative linear velocity, standard polishing time, and system Preston constant; all parameters are taken from the equipment's standard processing parameter table and are fixed. The system Preston constant (unit: m² / N or 1 / Pa) is calculated by using a standard sample with the same material as the product, under constant polishing base pressure, relative linear velocity, and standard polishing time, by adding an additional known weight, measuring the additional removal depth, and back-calculating the Preston equation coefficients. System Preston constant = measured additional removal depth / (gravity of the additional known weight × relative linear velocity × standard polishing time).
[0082] S5B.2. Based on the largest target deviation point data in the target deviation point data set, the defect area is analyzed and extracted, and the target removal amount of the corresponding deviation point is calculated in conjunction with the set deviation threshold so that the deviation of the corresponding point just meets the set deviation threshold. This allows the target removal amount of the deviation point to be removed during the subsequent polishing and grinding process so that the point just enters the tolerance zone and avoids unnecessary material loss.
[0083] S5B.3. Based on the relative linear velocity, standard polishing time, and system Preston constant, calculate the global conversion coefficient. Global conversion coefficient = system Preston constant × relative linear velocity × standard polishing time.
[0084] S5B.4. Based on the Preston material removal equation, the additional unit area pressure required is calculated using the target removal amount at the deviation point and the global conversion coefficient.
[0085] S5B.5. Based on the static equilibrium equation, using the additional unit area pressure and defect area, calculate the required mass of the counterweight and obtain the mass data of the counterweight at the target deviation point.
[0086] S6B. Place the substrate on the support platform of the gravity leveling device, and make the substrate protruding downwards, corresponding to the largest target deviation point data in the target deviation point data set. Apply a counterweight corresponding to the target deviation point counterweight mass data at the largest target deviation point data in the target deviation point data set on the upper surface of the substrate.
[0087] S7B: Press the underside of the substrate after applying the counterweight onto the polishing disc of the chemical mechanical polishing (CMP) machine, run the polishing program, use the additional pressure generated by the counterweight to selectively remove material from the raised areas, so that the raised areas are precisely ground to remove the target amount of deviation points, remove the counterweight, and return to S1.
[0088] Please refer to Figure 2 A processing system for a flatness photomask substrate includes a laser interferometer, a data storage module, a smart chip, a gravity flattening device, and a display.
[0089] The output of the laser interferometer is connected to the data storage module to measure the flatness map of the substrate and transmit the measured flatness map data to the data storage module for storage.
[0090] The data storage module is also used to store computer programs; its input end is connected to the laser interferometer, and its output end is connected to the smart chip.
[0091] The input end of the smart chip is connected to the data storage module, and the output end is connected to the gravity leveling device and the display respectively. It is used to run a computer program, execute a processing method for a flatness photomask substrate, and send control commands to the gravity leveling device according to the processing results.
[0092] The input end of the gravity leveling device is connected to a smart chip, which is used to apply a counterweight of appropriate mass to the corresponding position of the substrate and to perform leveling treatment on the substrate according to the processing result of the smart chip.
[0093] The input terminal of the display is connected to the smart chip to visualize the processing results of the smart chip.
[0094] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.
Claims
1. A method for processing a photomask substrate with improved flatness, characterized in that, Includes the following steps: S1. After cleaning the substrate, the surface morphology of the substrate is scanned by a laser interferometer to generate a flatness map. S2. Using the least squares method, perform plane fitting on the non-edge data in the flatness Map to obtain the substrate reference plane data; S3. Based on the flatness map and substrate reference plane data, calculate the deviation between the substrate and the substrate reference plane data, collect the flatness map coordinates where the deviation is greater than the set deviation threshold, and generate a target deviation point data set. S4. Determine whether the number of data in the target deviation point data set is greater than or equal to 1. If not, the substrate is qualified; if yes, proceed to the next step. S5. Collect the parameter data required for calibration, analyze and process the mass of the counterweight block to be applied at the corresponding position of the target deviation point data in the target deviation point data set, and obtain the corresponding target deviation point counterweight block mass data. S6. Based on the target deviation point counterweight mass data and the corresponding flatness Map coordinates, apply a counterweight block with the corresponding counterweight mass at the corresponding coordinate position of the substrate. S7. After applying the counterweight, the substrate is flattened and then returned to S1.
2. The method for processing a flatness photomask substrate according to claim 1, characterized in that, S2 includes the following steps: S2.
1. In the flatness map, exclude the coordinate points within the edge exclusion width range and generate a non-edge flatness map from the remaining coordinate points in the flatness map. S2.
2. Based on the coordinate points within the non-edge flatness map, construct the reference plane equation: Where z, x, and y are the height, x, and y coordinates of the non-edge flatness Map, respectively, and a, b, and c are the parameters to be solved. S2.
3. Using the least squares method, minimize the sum of squares of the differences between the z-values output by the reference plane equations corresponding to any x and y in the non-edge flatness Map and the actual z-values in the non-edge flatness Map to generate substrate reference plane data.
3. The method for processing a flatness photomask substrate according to claim 1, characterized in that, S3 includes the following steps: S3.1 Calculate the deviation between the height coordinate of each coordinate in the flatness Map and the height coordinate of the coordinate with the same plane coordinate in the substrate reference plane data to obtain the corresponding coordinate deviation data; S3.2 Compare each coordinate deviation data with the set deviation threshold to determine whether it is greater than the set deviation threshold; S3.3 If so, then set the flatness Map coordinates corresponding to the coordinate deviation data as the target deviation point data, and collect all target deviation point data to generate a target deviation point data set.
4. The method for processing a flatness photomask substrate according to claim 1, characterized in that, S5 includes the following steps: S5A.
1. Collect the elastic modulus, Poisson's ratio, and thickness of the substrate; S5A.
2. Based on Kirchhoff-Love thin plate theory, the bending stiffness of the substrate is calculated using the elastic modulus, Poisson's ratio, and thickness. S5A.
3. Based on the target deviation point data set, the defect area, equivalent feature size, and target deformation are analyzed and extracted; S5A.
4. Based on Kirchhoff-Lov thin plate theory, a dimensionless correction factor pre-calibrated through finite element analysis is introduced, and the required unit area pressure is calculated by combining the bending stiffness, equivalent characteristic size and target deformation. S5A.
5. Based on the static equilibrium equation, the mass of the counterweight is calculated using the defect area and pressure per unit area to obtain the mass data of the counterweight block at the target deviation point.
5. The method for processing a flatness photomask substrate according to claim 4, characterized in that, S6 and S7 include the following steps: S6A. Place the substrate on the support bearing plate of the gravity leveling device that can withstand the annealing temperature, and make the substrate protrusion corresponding to the target deviation point data set face downward. Apply the corresponding target deviation point counterweight mass data to all target deviation point data in the target deviation point data set on the upper surface of the substrate, so that the protrusion presses on the support bearing plate. S7A. Place the support plate on which the counterweight has been applied into the annealing furnace, heat it to the annealing point temperature of the substrate within the set heating time range, and hold it for the set holding time. After the substrate undergoes permanent plastic deformation under the action of the counterweight, slowly cool it to room temperature in the furnace at the set cooling rate, remove it, remove the counterweight, and return to S1.
6. The method for processing a flatness photomask substrate according to claim 1, characterized in that, S5 includes the following steps: S5B.1 Obtain the polishing base pressure, relative linear velocity, standard polishing time, and system Preston constant, wherein the system Preston constant refers to the proportionality coefficient of the Preston equation obtained through experimental calibration under specific polishing system conditions; S5B.
2. Based on the largest target deviation point data in the target deviation point data set, the defect area is analyzed and extracted, and the target removal amount of the corresponding deviation point is calculated in conjunction with the set deviation threshold so that the deviation of the corresponding point just meets the set deviation threshold. S5B.
3. Based on the relative linear velocity, standard polishing time, and system Preston constant, calculate the global conversion coefficient. Global conversion coefficient = system Preston constant × relative linear velocity × standard polishing time. S5B.
4. Based on the Preston material removal equation, the additional unit area pressure to be applied is calculated using the target removal amount at the deviation point and the global conversion coefficient. S5B.
5. Based on the static equilibrium equation, using the additional unit area pressure and defect area, calculate the required mass of the counterweight and obtain the mass data of the counterweight at the target deviation point.
7. The method for processing a flatness photomask substrate according to claim 6, characterized in that, S6 and S7 include the following steps: S6B. Place the substrate on the support platform of the gravity leveling device, and make the substrate protruding downwards, corresponding to the largest target deviation point data in the target deviation point data set. Apply a counterweight block with the corresponding target deviation point counterweight block mass data to the largest target deviation point data in the target deviation point data set on the upper surface of the substrate. S7B: Press the underside of the substrate after applying the counterweight onto the polishing disc of the chemical mechanical polishing machine, run the polishing program, and use the additional pressure generated by the counterweight to selectively remove material from the raised area, so that the raised area is precisely ground to the target removal amount of the deviation point, remove the counterweight, and return to S1.
8. A processing system for a flatness photomask substrate, used to perform the processing method for a flatness photomask substrate according to any one of claims 1-7, characterized in that, It includes a laser interferometer, a data storage module, a smart chip, a gravity leveling device, and a display. The output of the laser interferometer is connected to the data storage module for measuring the flatness map of the substrate and transmitting the measured flatness map data to the data storage module for storage. The data storage module is also used to store computer programs, with its input end connected to a laser interferometer and its output end connected to a smart chip. The input end of the smart chip is connected to the data storage module, and the output end is connected to the gravity leveling device and the display respectively. It is used to run the computer program, execute the processing method of flatness photomask substrate according to any one of claims 1-7, and send control commands to the gravity leveling device according to the processing results. The input end of the gravity leveling device is connected to a smart chip, which is used to apply a counterweight of appropriate mass to the corresponding position of the substrate according to the processing result of the smart chip, and to perform leveling treatment on the substrate. The input terminal of the display is connected to the smart chip, which is used to visualize the processing results of the smart chip.