WO2024045029A1 - 显示面板的工艺数据的验证方法、显示面板的生产方法和电子设备 - Google Patents

显示面板的工艺数据的验证方法、显示面板的生产方法和电子设备 Download PDF

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WO2024045029A1
WO2024045029A1 PCT/CN2022/116149 CN2022116149W WO2024045029A1 WO 2024045029 A1 WO2024045029 A1 WO 2024045029A1 CN 2022116149 W CN2022116149 W CN 2022116149W WO 2024045029 A1 WO2024045029 A1 WO 2024045029A1
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data
actual
display panel
model
simulation
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PCT/CN2022/116149
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English (en)
French (fr)
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刘楠
林雪梅
吴建民
王洪
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京东方科技集团股份有限公司
北京中祥英科技有限公司
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Priority to PCT/CN2022/116149 priority Critical patent/WO2024045029A1/zh
Priority to CN202280002969.5A priority patent/CN117957596A/zh
Publication of WO2024045029A1 publication Critical patent/WO2024045029A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/30—Circuit design
    • G06F30/36—Circuit design at the analogue level
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/30—Circuit design
    • G06F30/36—Circuit design at the analogue level
    • G06F30/367—Design verification, e.g. using simulation, simulation program with integrated circuit emphasis [SPICE], direct methods or relaxation methods
    • G—PHYSICS
    • G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09F—DISPLAYING; ADVERTISING; SIGNS; LABELS OR NAME-PLATES; SEALS
    • G09F9/00—Indicating arrangements for variable information in which the information is built-up on a support by selection or combination of individual elements

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  • the present disclosure relates to the technical field of process verification, and in particular to a verification method of process data of a display panel, a production method of a display panel, electronic equipment, storage media and computer program products.
  • display products need to undergo strict standard verification before being launched on the market.
  • the backplane manufacturing process stage, evaporation packaging process stage and module process stage of OLED products all need to be rationally verified. Due to the process fluctuation problem of the equipment, it needs to be adjusted multiple times to achieve the process parameters required for the design. This will lead to a very long verification phase, especially for new products, which will take longer, affecting the development progress of new products.
  • the present disclosure provides a verification method of process data of a display panel, a production method of a display panel, electronic equipment, storage media and computer program products.
  • the present disclosure provides a method for verifying process data of a display panel, including: generating simulation process data for executing the process based on design data of any process of the display panel; using a process model to simulate the use of simulating the process data to perform the process; and using the measurement model to verify whether the simulated process data can be used for actual production based on the simulation results, where the process model is constructed based on the actual process data generated during the actual manufacturing process of the display panel, and the measurement model is Built based on actual process data and actual measurement data generated during the actual manufacturing process of the display panel.
  • using a process model to simulate executing a process using simulated process data includes using the process model to determine characteristic data of a display panel that can be obtained if the process is executed using simulated process data.
  • using the measurement model to verify whether the simulated process data can be used for actual production based on the simulation results includes: using the measurement model to determine, among the actual process data, the actual process data whose similarity to the simulated process data is higher than a preset similarity threshold as Similar process data; determine the characteristic data of the display panel obtained by actually executing the process using similar process data among the actual measurement data as the actual characteristic data; and respond to the fact that the difference between the actual characteristic data and the characteristic data output by the process model is less than the predicted Set a difference threshold to determine that the simulation process data can be used for actual production.
  • the verification method also includes: before using the measurement model to verify whether the simulated process data can be used for actual production based on the simulation results, using the control model to apply a feedback parameter algorithm to the actual process data to calculate process fluctuations, and applying the process fluctuations to the process model Output feature data.
  • the feedback parameter algorithm includes one of the moving average algorithm, the weighted moving average algorithm, and the exponential moving average algorithm.
  • a moving average algorithm involves calculating the average value of a process parameter over a number of consecutive cycles according to the following formula:
  • C 1 , C 2 ,...C n are the values of the process parameters of each cycle, and n is an integer greater than 1.
  • weighted moving average algorithms include one of the doomsday weighting algorithm, the linear weighting algorithm, the trapezoidal weighting algorithm, and the square coefficient weighting algorithm.
  • the doomsday weighting algorithm involves calculating a weighted average of process parameters for consecutive cycles according to the following formula:
  • C 1 , C 2 ,...C n are the values of the process parameters of each cycle, and n is an integer greater than 1.
  • a linear weighting algorithm involves calculating a weighted average of process parameters for consecutive cycles according to the following formula:
  • C 1 , C 2 ,...C n are the values of the process parameters of each cycle, and n is an integer greater than 1.
  • the ladder weighting algorithm involves calculating a weighted average of process parameters for consecutive cycles according to the following formula:
  • C 1 , C 2 ,...C n are the values of the process parameters of each cycle, and n is an integer greater than 1.
  • the square coefficient weighting algorithm involves calculating a weighted average of process parameters for consecutive cycles according to the following formula:
  • C 1 , C 2 ,...C n are the values of the process parameters of each cycle, and n is an integer greater than 1.
  • the exponential moving average algorithm involves calculating a weighted average of process parameters for multiple consecutive cycles according to the following formula:
  • C 1 , C 2 ,...C n are the values of the process parameters of each cycle, n is an integer greater than 1, and ⁇ is the weighted index.
  • any process of a display panel includes a backplane manufacturing process.
  • any process of the display panel includes a photolithography process used to form a film layer in the backplane manufacturing process
  • the design data includes a design drawing of the mask.
  • a method for executing The simulation process data of the process includes at least one of the following operations: simulating at least part of the design drawing of the mask to obtain a test pattern; generating exposure process parameters according to the received exposure parameter setting information; The received resist parameter setting information is used to generate resist process parameters; and the development process parameters are generated according to the received development parameter setting information.
  • generating exposure process parameters includes at least one of the following: numerical aperture, wavelength, coherence factor, illumination type, exposure magnification, and focus position.
  • the process parameters for generating the resist include at least one of the following: type of photoresist, thickness and development rate of the photoresist, base material, and photosensitive compound PAC concentration distribution.
  • generating simulation process data for executing the process based on the design data of any process of the display panel also includes at least one of the following: performing lens projection simulation on the test pattern based on the exposure process parameters to obtain spatial image data; and based on Development parameters are used to generate graphic data of the developed film layer.
  • the verification method further includes: displaying at least one of the spatial image data and the graphic data through a user interaction interface and receiving user input, and adjusting the exposure process parameters, the resist process parameters, and the development process parameters according to the user input. at least one of.
  • the actual measurement data includes data measured before any process starts and data measured after any process starts.
  • the method further includes: updating actual process data and actual measurement data; and updating the process model and measurement model according to the updated actual process data and actual measurement data.
  • the method further includes: in response to verifying that the simulated process data can be used for actual production through verification, applying the simulated process data to the displayed actual manufacturing process.
  • the verification method also includes: forming simulation process data that has been verified and can be used for actual production into a manufacturing process file.
  • the present disclosure provides an electronic device, including a memory and a processor, the memory stores instructions executable by the processor, and the instructions are executed by the processor, so that the processor can perform a method according to an embodiment of the present disclosure. .
  • the present disclosure provides a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause a computer to perform a method according to an embodiment of the present disclosure.
  • the present disclosure provides a computer program product, including a computer program that, when executed by a processor, implements a method according to an embodiment of the present disclosure.
  • the present disclosure provides a production method of a display panel, including a physical manufacturing process and a digital processing process, wherein,
  • the verification method is performed using a process model and a measurement model generated based on the actual process data and actual measurement data to verify whether the simulated process data can be used for actual production.
  • performing at least one process process of the display panel during the physical manufacturing process includes: sequentially executing a pre-measurement operation, a preparation operation, a loading process data operation, a process processing operation and a post-measurement operation, wherein in the loading process data The actual process data is loaded in the operation, and at least one of the front measurement operation, the process processing operation and the backside measurement operation generates the actual measurement data.
  • the production method further includes: in response to verifying that the simulation process data can be used for actual production, applying the simulation data as actual process data to a loading process data operation in the physical manufacturing process.
  • the production method further includes: executing the physical manufacturing process again to generate new actual process data and new actual measurement data; and updating the process model and the measurement model based on the new actual process data and new actual measurement data.
  • Figure 1 is a flow chart of a method for verifying process data of a display panel according to one embodiment of the present disclosure
  • 2A is a flow chart of a method for verifying process data of a display panel according to another embodiment of the present disclosure
  • FIG. 2B is a schematic diagram of a production method of a display panel according to an embodiment of the present disclosure
  • Figure 3 is a schematic diagram of a verification process of photolithography process data according to an embodiment of the present disclosure
  • Figure 4 is a flow chart for generating photolithography process simulation process data according to one embodiment of the present disclosure
  • 5A and 5B are schematic diagrams of test pattern generation functions in photolithography design simulation according to one embodiment of the present disclosure
  • Figure 5C is a schematic diagram of the layout Boolean operation function in photolithography design simulation according to an embodiment of the present disclosure
  • 5D and 5E are schematic diagrams of the process window analysis function in lithography design simulation according to one embodiment of the present disclosure
  • Figure 5F is a schematic diagram of the reflectivity analysis function of the process stack in photolithography design simulation according to an embodiment of the present disclosure
  • Figure 5G is a schematic diagram of the lithography optical imaging simulation function in lithography design simulation according to an embodiment of the present disclosure.
  • FIG. 6 is a block diagram of an electronic device suitable for implementing a verification method of process data of a display panel according to an embodiment of the present disclosure.
  • FIG. 1 is a flow chart of a method for verifying process data of a display panel according to one embodiment of the present disclosure.
  • the verification method of process data may include operations S110 to S130.
  • simulation process data for executing the process is generated based on the design data of any process of the display panel.
  • design data may include design files.
  • the design file includes information related to the design of the process of the display panel, such as but not limited to the design drawings and design parameters of one or more components to be used or generated by the process of manufacturing the display panel.
  • the design data may also include other data related to the design of the display panel, such as parameters, conditions, and the like related to the manufacturing process of the display panel.
  • the design data may include at least one of the following data involved in the photolithography process: mask design drawings, exposure parameter setting information, resist parameter setting information, and Development parameter setting information.
  • Various design data input by the user can be received through, for example, a user interaction interface, and corresponding process data can be generated as simulation process data based on the received design data.
  • the computer can select and segment the design drawings received from the mask to obtain test drawings suitable for the designer to view.
  • the computer can also generate exposure process parameters based on the exposure parameter setting information, generate resist process parameters based on the resist parameter setting information, and generate highlight process parameters based on the highlight parameter setting information.
  • the computer can also generate various simulation result diagrams through model deduction or calculation based on various received design data for the designer to view.
  • Designers can adjust the design data through the interactive interface based on the simulation result diagram.
  • the computer can regenerate the simulation process data based on the designer's adjusted design data. Through repeated adjustments, simulation process data that is more in line with actual needs can finally be obtained. This process is also called the product design simulation process.
  • the product design simulation process can be realized with the help of simulation design software.
  • simulation software can select photoresist based on process requirements.
  • the simulation software can simulate and design the mask image according to the required lithography image.
  • the simulation software can also simulate the photochemical reaction that occurs after the photoresist is irradiated by light (exposure).
  • exposure The internal structures of the parts of the photoresist that are irradiated by light and the parts that are not irradiated by light will undergo different chemical changes, so that the parts of the photoresist that are irradiated by light and the parts that are not irradiated by light change in the developer solution.
  • the dissolution rates vary greatly.
  • the simulation software can simulate this characteristic of the photoresist and combine it with the pattern of the mask to obtain an image formed on the photoresist corresponding to the mask.
  • the simulation software can simulate the exposure process using a high-precision alignment lithography machine, simulating different exposure times, different exposure light sources, different types of photoresists, different viscosities and thicknesses of photoresists, etc.
  • the process data used by the simulation software to simulate the photolithography process can be output as simulation process data corresponding to the photolithography process. For example, mask pattern, exposure time, exposure light source, photoresist type, photoresist viscosity and thickness, etc.
  • the measurement model is used to verify whether the simulated process data can be used for actual production based on the simulation results.
  • the process model is built based on actual process data generated during the actual manufacturing process of the display panel
  • the measurement model is built based on actual process data and actual measurement data generated during the actual manufacturing process of the display panel.
  • the actual process data and the actual measurement data may be historical data generated during the actual manufacturing process of the display panel. Due to the influence of equipment process fluctuations in the actual production process, the actual process data and actual measurement data also fluctuate. Therefore, the process model established based on the actual process data and the measurement model established based on the actual process model and actual measurement data can characterize the equipment process fluctuations in the actual production process. By performing virtual verification simulation on the simulated process data based on the process model and measurement model, we can obtain process data that is close to the actual production situation.
  • the actual measurement data includes data measured before any process starts and data measured after any process starts.
  • the data measured before the start of any process may include current static data of the process equipment and raw material data for preparing the display panel, etc.
  • Data measured after the start of any process can include current operational operating data of the process equipment, sample data, etc.
  • the verification method of the embodiment of the present disclosure is applicable to any process in the display panel manufacturing process. It can generate simulated process data for executing the process based on the design data and verify the simulated process data based on the process model and measurement model constructed with actual data. Virtually verify the feasibility of the display panel, thereby interconnecting the design simulation data of the display panel and the virtual verification simulation data to achieve a complete process digital twin. Compared with manual verification in traditional technology, the design and verification time of the display panel is shortened.
  • FIG. 2A is a flow chart of a verification method of process data of a display panel according to another embodiment of the present disclosure. As shown in FIG. 2A , the verification method of process data may include operations S210 to S260.
  • simulation process data for executing the process is generated based on the design data of any process of the display panel.
  • simulation software may be used to generate simulated process data for executing the process based on the design data of any process of the display panel.
  • the user can start the interface of the simulation software and set parameters in the interface, so that the computer generates simulation process data for executing the process of the display panel based on the design data of the display panel and the parameters set by the user.
  • Simulation process data can include a variety of simulation process parameters, such as but not limited to GDS design drawings, dose (Dose), feature size (CD, Critical Dimension), mechanical design drawings, circuit design drawings, structural design drawings, exposure wavelength, and spectral specific gravity. , light source type, aperture value, photoresist thickness, developer concentration, soft bake temperature, pre-bake temperature and time, etc.
  • the computer can generate a test pattern based on the design drawing of the display panel, and generate various simulation process parameters such as exposure wavelength, aperture value, photoresist thickness, and developer concentration according to the parameters set by the user.
  • the parameters input by the user can characterize the user's requirements for display panel specifications.
  • a simulation result graph can also be generated based on the test graph and/or the generated various process parameters for the user to view.
  • the user can adjust the input according to the simulation result diagram, and the computer can adjust the various generated process parameters accordingly according to the adjusted user input. Users can also debug the simulation process on the interface of the simulation software.
  • the simulation process of the simulation software can be to simulate various environmental parameters, equipment parameters, material parameters, chemical reactions and physical reactions of the process, and perform simulation calculations in the form of numerical calculations through a solver.
  • the design data of the display panel may include the design data of any process of the display panel.
  • the display panel process includes backplane manufacturing process, evaporation packaging process, module process, etc.
  • the design data of the display panel can include GDS design drawings, circuit design drawings, structural design drawings, mechanical design drawings, dosage, feature dimensions, etc.
  • Different simulation software can be used at different process stages. For each process, the simulation software will generate corresponding simulation process parameters. The type of simulation process parameters corresponding to each process may be the same or different.
  • the design data input to the simulation software can include GDS design drawings, feature dimensions, recommended dosage, etc.
  • the above process can be called a display panel design simulation process.
  • the simulation process data can be used to execute the process based on the mathematical model, and based on the simulation results, it can be verified whether the simulation process data can be used for actual production.
  • This process is also called virtualization. Verify simulation.
  • the simulation process data output by the simulation software can be used as input to the virtual verification simulation process.
  • the simulation process data that will be verified and used for actual production can form manufacturing process files.
  • Manufacturing process documents can be displayed in the form of drawings, diagrams, text content or tables.
  • the process data included in the manufacturing process file is process data that can be used for actual production. Manufacturing process documents may also include process specifications and process cards.
  • the process specification may include the operation method of the process, and the process card may include the process parameters and process standards involved in the process.
  • the manufacturing process file includes simulation process data that meets the needs of the display panel after verifying the simulation process data output by the simulation software, including dose information, exposure wavelength, spectral specific gravity, light source type, aperture value, photoresist thickness, developer solution Concentration, soft baking temperature, pre-baking temperature and time, etc.
  • simulation process data After obtaining the simulation process data, it is also necessary to perform virtual verification simulation on the simulation process data.
  • data model simulation uses simulated process data to execute the process, and based on the simulation results, it is verified whether the simulated process data can be used for actual production.
  • Mathematical models can include process models and measurement models.
  • the mathematical model may also include a control model. The virtual verification simulation will be described below in conjunction with the following steps S220 to S240.
  • the process model is used to determine the characteristic data of the display panel that can be obtained if the process is executed using the simulated process data.
  • the process model may be a process mechanism model constructed based on actual process data.
  • the process model can take simulated process data as input and feature data of the display panel as output, and simulate the execution of the process by establishing a linear or nonlinear relationship between input and output.
  • the process mechanism model for example, the physical model of photolithography, the drift diffusion model of etching and chemical vapor deposition
  • an accurate mathematical formula is established to identify the relationship between input and output (linear or nonlinear).
  • the mathematical formula is optimized through experiments or mass production process parameters to obtain the process model. Therefore, the process model can generate characteristic data corresponding to any process of the display panel based on the linear or non-linear relationship between various simulated process parameters and characteristic data.
  • a feedback parameter algorithm is applied to the actual process data using the control model to calculate process fluctuations, and the process fluctuations are applied to the characteristic data output by the process model.
  • the control model can be a fluctuation law model constructed based on actual process data.
  • the control model is used to apply process fluctuations calculated based on actual process data to the simulation results to produce adjusted simulation results.
  • the control model can simulate the operating logic of the process to be simulated and implement the management of the model state (data filtering, control logic).
  • the control model may select a feedback parameter algorithm in an optimized process control model to calculate process fluctuations based on process data and/or measurement data generated during the actual manufacturing process. Feedback parameter algorithms enable automatic correction of process fluctuations.
  • the running logic can be abstracted from the business process into the model by process engineers. Model state management can include filtering the sources of process data required by each business process. Changes to business processes require adjustments to control logic such as add, delete, change, and query.
  • the feedback parameter algorithm may include one of a moving average algorithm, a weighted moving average algorithm, and an exponential moving average algorithm.
  • the measurement model is used to compare the difference between the actual characteristic data and the characteristic data output by the process model.
  • the measurement model may be a statistical model constructed based on actual measurement data and actual process data.
  • a measurement model can be built based on machine learning algorithms (SVM, decision tree, random forest, logistic regression, Bayes, etc.) based on actual measurement data.
  • SVM machine learning algorithms
  • the measurement model is used to verify whether the simulated process data can be used for actual production by comparing the simulation results for the simulated process data with the actual measured data for the actual process data.
  • the measurement model can determine in the actual process data that the similarity between the actual process data and the simulated process data is higher than the preset similarity threshold as similar process data, and determine in the actual measurement data that the similar process data is used to actually execute the process.
  • the obtained characteristic data of the display panel is used as actual characteristic data.
  • the measurement model can compare the above-mentioned actual characteristic data with the above-mentioned characteristic data generated by the process model and after the process fluctuation is imposed by the control model. If the difference between the two is less than the preset difference threshold, it is determined that the simulated process data is available. in actual production.
  • step S250 it is determined whether the simulation process data passes the verification based on the comparison result. If it passes the verification, operation S260 is performed. Otherwise, step S210 can be returned so that the user can adjust the design data or adjust parameter settings.
  • the simulation process data is considered to have passed the verification, otherwise Considered not verified.
  • the verification results pass the manufacturing process standards of the product requirements, and it can be considered that the simulation process data obtained through the product design simulation of the display panel can generate a qualified display panel that meets the preset requirements in real physical process equipment. If the verification result does not pass, it can be considered that the simulation process data obtained through the product design simulation of the display panel may not meet the preset requirements when generating the display panel in the real physical process equipment, so the design data of the display panel needs to be modified. Obtain verification results of manufacturing process standards that meet display panel requirements.
  • the photolithography process is simulated based on the process parameters A1, A2 and A3 in operation S220, by Characteristic data such as the shape and size of the photolithography pattern were calculated.
  • process fluctuations are added to the characteristic data simulated in operation S220.
  • the measurement model can be used to determine the exposure process parameters and resistance values whose differences between A1, A2 and A3 are less than the preset thresholds respectively among the values of various process parameters used in the actual production process. Etch process parameters and highlight process parameters.
  • the actual process data B1, B2, and B3 are used as similar process data to the simulated process data A1, A2, and A3.
  • the characteristic data of the photolithography pattern measured using the exposure process parameter B1, the resist process parameter B2, and the highlight process parameter B3 for the actual photolithography process such as the shape of the photolithography pattern. , size, etc., as actual feature data.
  • the actual characteristic data i.e., the measured shape, size, etc.
  • the characteristic data provided in step S230 i.e., the size, shape, etc., of the photolithography pattern obtained through virtual simulation of the process model. Compare, if the difference between the two is less than the preset threshold, it is considered that the photolithography pattern obtained through virtual simulation based on the simulated process parameters A1, A2 and A3 is similar to the actual process parameters B1, B2 and B3 based on the actual production process.
  • the photolithography patterns obtained by performing the photolithography process are generally consistent, so it can be considered that the simulated process parameters A1, A2, and A3 are feasible in actual manufacturing, that is, they have passed the verification.
  • the simulation process data is applied to the actual manufacturing process of the display panel.
  • the design data will be imported into the real physical process equipment. If the virtual verification simulation data does not meet the conditions for actual physical process production, the design data of the display panel can be modified in time. Through the virtual verification method, the simulation process data that meets the conditions of actual physical process production is applied to the actual manufacturing process of the display panel, which can shorten the display panel design verification time and speed up the launch of new display panels.
  • operation S230 may be optional.
  • operation 230 may be omitted to increase processing speed.
  • the measurement model may compare the difference between the characteristic data of the display panel output by the process model in operation S220 and the actual characteristic data to determine whether the simulated process parameters pass the verification.
  • the actual process data and actual measurement data can also be updated, and the mathematical model can be updated based on the updated actual process data and actual measurement data, such as updating at least one of the above-mentioned process model, measurement model, and control model. .
  • the actual process data and actual measurement data generated by the real manufacturing process can be obtained periodically or after the real manufacturing process is completed to add or replace the existing actual process data and actual measurement data, thereby realizing the actual process data. and updates of actual measurement data.
  • the mathematical model can be adjusted based on updated actual process data and actual measurement data.
  • the virtual verification simulation process can use the updated mathematical model to verify the simulation process data generated by the display panel design simulation process.
  • the production parameters can also be optimized based on the verification results.
  • fault prediction maintenance and failure prediction can also be performed based on the verification results.
  • FIG. 2B is a schematic diagram of a production method of a display panel according to an embodiment of the present disclosure. As shown in Figure 2B, the production of the display panel includes a digital processing process 260 and a physical manufacturing process 270.
  • the digital processing process 260 is also called digital process, which is a virtual process, including display panel design simulation 261 and virtual verification simulation 262 .
  • the physical manufacturing process 270 is also called a physical process and is a real process.
  • the physical manufacturing process 270 includes pre-measurement, preparation work, loading process data, process processing and post-measurement processes.
  • the data generated by the physical manufacturing process 270 may include actual process data and actual measurement data.
  • the pre-measurement process produces actual measurement data before the process
  • the post-measurement process produces actual measurement data after the process.
  • Preparatory work processes and process machining processes can generate process data.
  • the actual data generated by the physical manufacturing process 270 can be used to build and optimize the mathematical models required for the digital processing process 260 .
  • the constructed mathematical model of the virtual verification simulation 262 process may include a process model 2621, a control model 2622, and a measurement model 2623.
  • the process model 2621 may be constructed based on actual process data
  • the control model 2622 may also be constructed based on actual process data
  • the measurement model 2623 may be constructed based on actual measurement data and actual process data.
  • the simulation process data generated by the product design simulation 261 process in the digital processing process 260 includes a variety of simulation process parameters.
  • the process model 2621 can be used to determine the characteristic data of the display panel that can be obtained when executing the process using simulated process data; the control model 2622 can be used to apply a feedback parameter algorithm to the actual process data to calculate the process.
  • the measurement model 2623 determines in the actual process data the actual process data whose similarity to the simulated process data is higher than the preset similarity threshold as similar process data, and determines in the actual measurement data what is obtained by actually executing the process using similar process data.
  • the characteristic data of the display panel is used as the actual characteristic data.
  • y is the dose
  • x is the feature size
  • k can be a linear parameter
  • the linear parameter can be summarized based on historical experience.
  • parameter k can be linear or nonlinear.
  • control model 2622 may be a fluctuation law model formed according to process fluctuations of the equipment.
  • feedback parameter algorithms include moving average algorithms, weighted moving average algorithms, and exponential moving average algorithms. You can select one of the moving average algorithm, weighted moving average algorithm, and exponential moving average algorithm as the optimization algorithm.
  • a moving average algorithm involves calculating the average value of a process parameter over a number of consecutive cycles according to the following formula:
  • C 1 , C 2 ,...C n are the values of the process parameters of each cycle, and n is an integer greater than 1.
  • weighted moving average algorithms include one of the doomsday weighting algorithm, the linear weighting algorithm, the trapezoidal weighting algorithm, and the square coefficient weighting algorithm.
  • the doomsday weighting algorithm involves calculating a weighted average of process parameters for consecutive cycles according to the following formula:
  • C 1 , C 2 ,...C n are the values of the process parameters of each cycle, and n is an integer greater than 1.
  • a linear weighting algorithm involves calculating a weighted average of process parameters for consecutive cycles according to the following formula:
  • C 1 , C 2 ,...C n are the values of the process parameters of each cycle, and n is an integer greater than 1.
  • the ladder weighting algorithm involves calculating a weighted average of process parameters for consecutive cycles according to the following formula:
  • C 1 , C 2 ,...C n are the values of the process parameters of each cycle, and n is an integer greater than 1.
  • the square coefficient weighting algorithm involves calculating a weighted average of process parameters for consecutive cycles according to the following formula:
  • C 1 , C 2 ,...C n are the values of the process parameters of each cycle, and n is an integer greater than 1.
  • the exponential moving average algorithm involves calculating a weighted average of process parameters for multiple consecutive cycles according to the following formula:
  • C 1 , C 2 ,...C n are the values of the process parameters of each cycle, n is an integer greater than 1, and ⁇ is the weighted index.
  • the measurement model 2623 may be a statistical model of device measurements formed from historical measurement data of the device.
  • the historical measurement data is the real measurement data in the actual process generation, and the measurement model is built based on the real measurement data.
  • the measurement model 2623 compares the adjusted characteristic data generated by the control model 2622 with the actual characteristic data, and determines whether the simulation process data passes the verification based on the comparison results.
  • the constructed measurement model 2623 can be used in the verification link in the virtual verification simulation. Because the virtual verification link does not carry out actual production, the measurement model 2623 is needed to perform virtual measurement.
  • the simulation process parameters output by the virtual verification simulation with the historical actual process data. If yes, the simulation process data is considered to have passed the verification, otherwise it is considered to have failed the verification. .
  • the present disclosure can also provide a production method of the display panel.
  • the production method of the display panel includes a physical manufacturing process (eg, the above-mentioned physical manufacturing process 270) and a digital processing process (eg, the above-mentioned digital processing process 260).
  • a physical manufacturing process eg, the above-mentioned physical manufacturing process 270
  • a digital processing process eg, the above-mentioned digital processing process 260.
  • At least one process of the display panel can be performed to obtain actual process data and actual measurement data.
  • a pre-measurement operation, a preparation operation, a process data loading operation, a process processing operation and a post-measurement operation may be performed in sequence, wherein the actual process data is loaded in the loading process data operation.
  • at least one of the front measurement operation, the processing operation and the backside measurement operation generates the actual measurement data.
  • the verification method of any of the above embodiments can be performed using a process model and a measurement model generated based on the actual process data and actual measurement data to verify whether the simulated process data can be used for actual production.
  • the simulated data in response to verifying that the simulated process data can be used for actual production, the simulated data may be used as actual process data in a loading process data operation in the physical manufacturing process.
  • the actual measurement data includes data measured before any process starts and data measured after any process starts.
  • measurement data obtained from pre-measurement operations and measurement data obtained from post-measurement operations of the physical manufacturing process 270 are examples of the actual measurement data.
  • the physical manufacturing process can also be performed again to generate new actual process data and new actual measurement data; and the mathematical model can be updated based on the new actual process data and new actual measurement data.
  • the simulation data of the actual production of the physical manufacturing process 270 this time is used as actual process data for digital processing.
  • Process 260 as updated actual process data and actual measurement data, and update the mathematical model based on the updated actual process data and actual measurement data.
  • the digital process provides real process data according to the physical process to construct and adjust the data model, thereby realizing data sharing and data interaction between the digital process and the physical process.
  • the data of display panel design simulation and virtual verification simulation are interconnected to form a complete process digital twin process, thereby forming a process digital twin closed loop of product design-product design simulation-virtual verification simulation, realizing virtual data and Interconnection of real data.
  • virtual verification simulation the results of product design simulation are verified and the optimization direction of the design data of the display panel is given, so as to modify the design data of the display panel in a timely manner, shorten the display panel design verification time, and speed up the launch of new display panels.
  • the backplane manufacturing process may include coating, photolithography, and etching processes.
  • the coating process includes sputtering process (Sputter) and plasma enhanced chemical vapor deposition process (PECVD, Plasma Enhanced Chemical Vapor Deposition).
  • the sputtering process uses the principle of physical sputtering to deposit a metal film layer.
  • PECVD uses chemical vapor deposition to deposit semiconductor or non-metallic film layers.
  • the photolithography process includes a track process (Track) and a photolithography process (Aligner). The track process coats a light-sensitive photoresist on the substrate. After the exposure is completed, the exposed photoresist is developed.
  • the photolithography process uses ultraviolet light to expose the photoresist without a mask to complete the exposure.
  • the etching process includes dry etching (Dry Etch), wet etching (Wet Etch), stripping process (Strip) and cleaning process (Clearner). Dry etching uses reactive gas to dryly etch away the non-metal or metal film layer, and wet etching uses chemical liquid such as acid to wetly etch away the metal film layer.
  • the stripping process uses chemical liquid to peel off the exposed photoresist.
  • the cleaning process cleans the film layer before deposition.
  • Figure 3 is a schematic diagram of virtual verification simulation according to one embodiment of the present disclosure.
  • the physical lithography process includes multiple lithography processes 310, 320, and 330.
  • a measurement operation can be performed to obtain actual measurement data.
  • a measurement operation 340 is performed after the photolithography process 310
  • a measurement operation 350 is performed after the photolithography process 320 .
  • the process data produced by each photolithography process and the measurement data produced by each measurement operation can be obtained for use in building mathematical models in virtual verification simulations.
  • the photolithography process 310 generates the process data PD1, then the measurement operation 340 generates the measurement data MD1, then the next cycle of the photolithography process 320 generates the process data PD2, then the measurement operation 350 generates the measurement data MD2, then the next cycle of photolithography Process 330 generates process data PD3, and so on.
  • Process data generated from the photolithography process and measurement data generated from measurements against the photolithography process can be used to build the measurement model in the virtual verification simulation 360. In some embodiments, these process data and measurement data can also be used for adjustment and optimization of mathematical models.
  • Figure 4 is a flow chart for generating photolithography process simulation process data according to one embodiment of the present disclosure.
  • Any process of the display substrate includes a photolithography process for forming a film layer in the backplane manufacturing process.
  • the photolithography process may include mask design, exposure, resist and development processes.
  • the design data includes a design drawing of the mask plate, and the step of generating simulation process data of the photolithography process based on the design data of the display panel may include at least one of operations S410 to S440.
  • the design drawing of the mask plate is imported into the design data in the simulation software, and the position of the target pattern that needs to be etched subsequently can be selected and simulated on the substrate to generate a test pattern.
  • exposure process parameters are generated according to the received exposure parameter setting information.
  • the exposure process parameters of the exposure machine equipment are generated in the simulation software.
  • the generated exposure process parameters include at least one of the following: numerical aperture, wavelength, coherence factor, illumination type, exposure magnification and focus position wait.
  • resist process parameters are generated according to the received resist parameter setting information.
  • the process parameters for generating the resist include at least one of the following: type of photoresist, thickness and development rate of the photoresist, base material, and photosensitive compound PAC concentration distributed.
  • the concentration distribution of the photosensitive compound can be obtained.
  • developing process parameters are generated according to the received developing parameter setting information.
  • the method of generating photolithography process simulation process data also includes performing lens projection simulation on the test pattern based on the exposure process parameters to obtain aerial image data; and generating development based on the development parameters. Graphical data of the final film layer.
  • the step of generating simulation process data of the photolithography process based on the design data of the display panel, based on operations S410 to S440 may also include displaying at least one of spatial image data and graphics data through a user interaction interface and receiving user data. input, and adjusting at least one of the exposure process parameters, the resist process parameters, and the development process parameters based on the user input.
  • aerial image data can be derived based on the aerial image distribution after projection through the lens.
  • the development parameters are imported into the development module of the simulation software, and the graphics after development can be output.
  • the user can determine whether the spatial image data and/or image data meet the conditions based on the displayed spatial image data and/or image data. If the conditions are not met, relevant settings are input to adjust at least one of the exposure process parameters, the resist process parameters, and the development process parameters.
  • FIGS. 5A and 5B are schematic diagrams of test pattern generation functions in photolithography design simulation according to one embodiment of the present disclosure.
  • FIG. 5C is a schematic diagram of the layout Boolean operation function in photolithography design simulation according to an embodiment of the present disclosure.
  • 5D and 5E are schematic diagrams of process window analysis functions in lithography design simulation according to one embodiment of the present disclosure.
  • FIG. 5F is a schematic diagram of a process stack reflectance analysis function in photolithography design simulation according to an embodiment of the present disclosure.
  • Figure 5G is a schematic diagram of the lithography optical imaging simulation function in lithography design simulation according to an embodiment of the present disclosure.
  • At least part of the design drawing of the mask plate can be simulated to obtain a test pattern.
  • a regular series of test images can be generated according to set rules.
  • Special test graphics can also be generated according to the specific needs of users.
  • the interactive interface shown in Figure 5A is used to display preset default rules or receive rules input by the user according to special needs.
  • the computer can edit at least part of the design of the mask according to rules (such as the clipping pitch Clip Pitch X and the clipping size Clip Size in the X direction, the clipping pitch Clip Pitch Y and the clipping size Clip Size Y in the X and Y directions, etc.)
  • the location is selected and simulated in the area, and the test chart shown in Figure 5B is obtained.
  • the test pattern can include information such as feature size cd, the number of graphics in the layout, the arrangement spacing space between graphics, the gap spacing between graphics, and the center spacing pitch between graphics.
  • the layout Boolean operation function interface you can view and edit the test chart (such as the test chart shown in Figure 5B) by area and unit, and you can also perform Boolean operations on the graphics in the test chart. And perform operations such as expanding, shrinking, flipping and extracting graphics, as well as providing functions of compression and amplification in the dynamic range.
  • the original test pattern includes three "I"-shaped graphic elements and one "L” graphic element arranged side by side. Through Boolean operations on the original test chart, three "I"-shaped graphic elements arranged side by side are merged into one "I"-shaped graphic element. Boolean operations can also include difference, union, and intersection operations on multiple graphic elements.
  • At least one of the exposure parameter setting information, the resist parameter setting information, and the development parameter setting information may be received through the interactive interface.
  • the exposure parameter setting information input by the user can be received through the interface as shown in FIG. 5D.
  • the computer can generate exposure process parameters based on the received exposure parameter setting information, generate resist process parameters based on the received resist parameter setting information, and generate development process parameters based on the received development parameter setting information.
  • process window analysis can be performed.
  • the computer obtains the photolithography process window corresponding to the simulation graphics based on the exposure dose (Dose Factor) and defocus value (Defocus Values) given by the user.
  • the computer can correlate and analyze the aerial image (Aerial image), photoresist image (bulk image), and photosensitive compound concentration distribution image (PAC image) during the exposure simulation process according to the selection.
  • the exposure focus matrix exposure dose and defocus amount
  • process window measurement method feature size specification (CD specification), sidewall angle specification (sidewall angle specification), and resist specification can also be set for process window analysis.
  • resist less specification exposure latitude specification (expose latitude specification), line edge roughness specification (line edge roughness specification) and other parameters.
  • the computer simulates the parameters set for the process window analysis to ensure that the pattern of the test pattern of the mask can be correctly etched. For example, some simulation results of the photolithography process window are shown in Figure 5E. Using the ellipse as the process window measurement method, the simulation obtains the optimal focus position, optimal dose, and optimal feature size, etc. In addition, parameters such as the shape and constraints of the process window can also be changed to simulate process windows and constraints of various shapes. As shown in Figure 5F, process stack reflectivity analysis can also be performed. For example, the reflectivity of a single photoresist film layer can be analyzed to simulate the thickness of various single photoresist film layers.
  • photoresist and anti-reflection layer it is also possible to simulate the multi-layer film structure of photoresist and anti-reflection layer by analyzing the reflectivity of the substrate and the reflectivity of the multi-layer film. From this, exposure process parameters, such as numerical aperture, wavelength, coherence factor, illumination type, exposure magnification and focus position, etc., as well as resist process parameters, such as photosensitivity, can be obtained through photolithography process window simulation and process stack reflectance simulation. Type of resist, photoresist thickness and development rate, base material and photosensitive compound PAC concentration distribution.
  • lens projection simulation can also be performed on the test pattern based on exposure process parameters to obtain aerial image data.
  • graphic data of the developed film layer can also be generated based on development parameters.
  • PAC/PAG photosensitive compound/photoacid generator
  • it can support the simulation of multiple light source lighting methods, multiple light source distributions, single-wavelength lighting and wide-band lighting methods.
  • two-dimensional thin mask approximate simulation and three-dimensional thick mask analytical simulation can be performed.
  • Kirchhoff approximate simulation and strict coupled wave method simulation can be used.
  • lenses wave aberration analysis simulation and dry system and immersion system simulation can be performed.
  • photoresist the optical effect of photoresist can be modeled through the transmission matrix method.
  • the simulation process can be based on the "L"-shaped graphic elements of the layout shown in Figure 5C.
  • lens projection simulation is performed on the test pattern to obtain aerial image data.
  • at least one of the spatial image data and the graphics data may be displayed through a user interaction interface and user input may be received.
  • at least one of the aerial image data, photoresist mid-image, and photosensitive compound/photoacid generator (PAC/PAG) concentration shown in FIG. 5G is displayed through a user interactive interface for user reference.
  • the user can adjust various parameter setting information through the interactive interface, and the computer can adjust at least one of the exposure process parameters, resist process parameters and development process parameters according to the user input.
  • PAC/PAG photosensitive compound/photoacid generator
  • FIG. 6 is a block diagram of an electronic device suitable for implementing a verification method of process data of a display panel according to an embodiment of the present disclosure.
  • an electronic device 600 includes a processor 601 that can be loaded into a random access memory (RAM) 603 according to a program stored in a read-only memory (ROM) 602 or from a storage part 608 program to perform various appropriate actions and processes.
  • Processor 601 may include, for example, a general purpose microprocessor (eg, CPU), an instruction set processor and/or associated chipset, and/or a special purpose microprocessor (eg, application specific integrated circuit (ASIC)), or the like.
  • Processor 601 may also include onboard memory for caching purposes.
  • the processor 601 may include a single processing unit or multiple processing units for performing different actions of the method flow according to the embodiment of the present disclosure.
  • the processor 601, ROM 602 and RAM 603 are connected to each other through a bus 604.
  • the processor 601 performs various operations according to the method flow of the embodiment of the present disclosure by executing programs in the ROM 602 and/or RAM 603. It should be noted that the program may also be stored in one or more memories other than ROM 602 and RAM 603.
  • the processor 601 may also perform various operations according to the method flow of embodiments of the present disclosure by executing programs stored in the one or more memories.
  • the electronic device 600 may further include an input/output (I/O) interface 605 that is also connected to the bus 604 .
  • Electronic device 600 may also include one or more of the following components connected to I/O interface 605: an input portion 606 including a keyboard, mouse, etc.; including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and an output section 607 of a speaker and the like; a storage section 608 including a hard disk and the like; and a communication section 609 including a network interface card such as a LAN card, a modem and the like.
  • the communication section 609 performs communication processing via a network such as the Internet.
  • Driver 610 is also connected to I/O interface 605 as needed.
  • Removable media 611 such as magnetic disks, optical disks, magneto-optical disks, semiconductor memories, etc., are installed on the drive 610 as needed, so that a computer program read therefrom is installed into the storage portion 608 as needed.
  • the present disclosure also provides a non-transitory computer-readable storage medium.
  • the computer-readable storage medium may be included in the device/device/system described in the above embodiments; it may also exist separately without being assembled into the device/system. in equipment/devices/systems.
  • the above computer-readable storage medium carries one or more programs. When the above one or more programs are executed, the method according to the embodiment of the present disclosure is implemented.
  • the computer-readable storage medium may be a non-volatile computer-readable storage medium, which may include, but is not limited to, portable computer disks, hard disks, random access memory (RAM), and read-only memory (ROM). , erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination of the above.
  • a computer-readable storage medium may be any tangible medium that contains or stores a program for use by or in connection with an instruction execution system, apparatus, or device.
  • the computer-readable storage medium may include one or more memories other than ROM 602 and/or RAM 603 and/or ROM 602 and RAM 603 described above.
  • Embodiments of the present disclosure also include a computer program product including a computer program containing program code for performing the method illustrated in the flowchart.
  • the program code is used to cause the computer system to implement the verification method of the process data of the product provided by the embodiment of the present disclosure.
  • the computer program can rely on tangible storage media such as optical storage devices and magnetic storage devices.
  • the computer program can also be transmitted and distributed in the form of a signal on a network medium, and downloaded and installed through the communication part 609, and/or installed from the removable medium 611.
  • the program code contained in the computer program can be transmitted using any appropriate network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.
  • the computer program may be downloaded and installed from the network via communication portion 609, and/or installed from removable media 611.
  • the computer program is executed by the processor 601, the above-described functions defined in the system of the embodiment of the present disclosure are performed.
  • the systems, devices, devices, modules, units, etc. described above may be implemented by computer program modules.
  • the program code for executing the computer program provided by the embodiments of the present disclosure may be written in any combination of one or more programming languages. Specifically, high-level procedural and/or object-oriented programming may be utilized. programming language, and/or assembly/machine language to implement these computational procedures. Programming languages include, but are not limited to, programming languages such as Java, C++, python, "C" language or similar programming languages.
  • the program code may execute entirely on the user's computing device, partly on the user's device, partly on a remote computing device, or entirely on the remote computing device or server.
  • the remote computing device may be connected to the user computing device through any kind of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device, such as provided by an Internet service. (business comes via Internet connection).
  • LAN local area network
  • WAN wide area network
  • Internet service business comes via Internet connection
  • each block in the flowchart or block diagrams may represent a module, segment, or portion of code that contains one or more logic functions that implement the specified executable instructions.
  • the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown one after another may actually execute substantially in parallel, or they may sometimes execute in the reverse order, depending on the functionality involved.
  • each block in the block diagram or flowchart illustration, and combinations of blocks in the block diagram or flowchart illustration can be implemented by special purpose hardware-based systems that perform the specified functions or operations, or may be implemented by special purpose hardware-based systems that perform the specified functions or operations. Achieved by a combination of specialized hardware and computer instructions.

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Abstract

本公开提供了一种显示面板的工艺数据的验证方法、设备、存储介质、产品，涉及工艺验证技术领域。显示面板的工艺数据的验证方法包括：基于显示面板的任一工艺过程的设计数据来生成用于执行工艺过程的仿真工艺数据；使用工艺模型来模拟使用仿真工艺数据执行工艺过程；以及使用测量模型来基于模拟结果验证仿真工艺数据是否可用于实际生产，其中工艺模型是基于在显示面板的实际制造过程中产生的实际工艺数据来构建的，测量模型是基于在显示面板的实际制造过程中产生的实际工艺数据和实际测量数据来构建的。

Description

显示面板的工艺数据的验证方法、显示面板的生产方法和电子设备 技术领域
本公开涉及工艺验证技术领域，尤其涉及一种显示面板的工艺数据的验证方法、显示面板的生产方法、电子设备、存储介质和计算机程序产品。
背景技术
通常，显示产品在上市前需要经过严格的标准验证。例如OLED产品的背板制造工艺阶段、蒸镀封装工艺阶段和模组工艺阶段等，均需要进行合理性验证。由于设备的工艺波动问题，需要调整多次才能达成设计所需要的工艺参数。这就会导致验证阶段的时间很长，尤其是新产品验证所需时间就会更长，影响了新产品的研发进度。
发明内容
本公开提供了一种显示面板的工艺数据的验证方法、显示面板的生产方法、电子设备、存储介质和计算机程序产品。
根据一方面，本公开提供了一种显示面板的工艺数据的验证方法，包括：基于显示面板的任一工艺过程的设计数据来生成用于执行工艺过程的仿真工艺数据；使用工艺模型来模拟使用仿真工艺数据执行工艺过程；以及使用测量模型来基于模拟结果验证仿真工艺数据是否可用于实际生产，其中工艺模型是基于在显示面板的实际制造过程中产生的实际工艺数据来构建的，测量模型是基于在显示面板的实际制造过程中产生的实际工艺数据和实际测量数据来构建的。
例如，使用工艺模型来模拟使用仿真工艺数据执行工艺过程包括：使用工艺模型来确定在使用仿真工艺数据执行工艺过程的情况下所能得到的显示面板的特征数据。
例如，使用测量模型来基于模拟结果验证仿真工艺数据是否可用于实际生产包括：使用测量模型在实际工艺数据当中确定与仿真工艺数据之间的相似度高于预设相似度阈值的实际工艺数据作为相似工艺数据；在实际测量数据当中确定使用相似工艺数据实际执行工艺过程所得到的显示面板的特征数据作为实际特征数据；以及响应于实际特征数据与工艺模型输出的特征数据之间的差异小于预设差异阈值，确定仿真工艺数据可用于实际生产。
例如，验证方法还包括：在使用测量模型来基于模拟结果验证仿真工艺数据是否可 用于实际生产之前，使用控制模型对实际工艺数据应用反馈参数算法来计算工艺波动，并将工艺波动施加到工艺模型输出的特征数据。
例如，反馈参数算法包括移动平均算法、加权移动平均算法和指数移动平均算法之一。
例如，移动平均算法包括根据以下公式来计算连续多个周期的工艺参数的平均值：
Figure PCTCN2022116149-appb-000001
其中C 1，C 2，...C n是每个周期的工艺参数的值，n为大于1的整数。
例如，加权移动平均算法包括末日加权算法、线性加权算法、梯形加权算法和平方系数加权算法之一。
例如，末日加权算法包括根据以下公式来计算连续多个周期的工艺参数的加权平均值：
Figure PCTCN2022116149-appb-000002
其中C 1，C 2，...C n是每个周期的工艺参数的值，n为大于1的整数。
例如，线性加权算法包括根据以下公式来计算连续多个周期的工艺参数的加权平均值：
Figure PCTCN2022116149-appb-000003
其中C 1，C 2，...C n是每个周期的工艺参数的值，n为大于1的整数。
例如，梯形加权算法包括根据以下公式来计算连续多个周期的工艺参数的加权平均值：
Figure PCTCN2022116149-appb-000004
其中C 1，C 2，...C n是每个周期的工艺参数的值，n为大于1的整数。
例如，平方系数加权算法包括根据以下公式来计算连续多个周期的工艺参数的加权平均值：
Figure PCTCN2022116149-appb-000005
其中C 1，C 2，...C n是每个周期的工艺参数的值，n为大于1的整数。
例如，指数移动平均算法包括根据以下公式来计算连续多个周期的工艺参数的加权平均值：
Figure PCTCN2022116149-appb-000006
其中C 1，C 2，...C n是每个周期的工艺参数的值，n为大于1的整数，α为加权指数。
例如，显示面板的任一工艺过程包括背板制造工艺。
例如，显示面板的任一工艺过程包括背板制造工艺中用于形成膜层的光刻工艺，设计数据包括掩模板的设计图，基于显示面板的任一工艺过程的设计数据来生成用于执行工艺过程的仿真工艺数据包括以下操作中的至少之一：对掩膜板的设计图的至少部分区域进行仿真，得到测试图；根据接收到的曝光参数设定信息来生成曝光工艺参数；根据接收到的抗蚀剂参数设定信息来生成抗蚀剂工艺参数；以及根据接收到的显影参数设定信息来生成显影工艺参数。
例如，生成曝光工艺参数包括以下各项中的至少之一：数值孔径、波长、相干因子、照明类型、曝光倍率和焦点位置。
例如，生成抗蚀剂工艺参数包括以下各项中的至少之一：光致抗蚀剂的类型、光致抗蚀剂的厚度和显影速率、基底材料和光敏化合物PAC浓度分布。
例如，基于显示面板的任一工艺过程的设计数据来生成用于执行工艺过程的仿真工艺数据还包括以下至少之一：基于曝光工艺参数对测试图进行透镜投影仿真，得到空间像数据；以及基于显影参数来生成显影后的膜层的图形数据。
例如，该验证方法还包括：通过用户交互界面来展示空间像数据和图形数据中的至少之一并接收用户输入，以及根据用户输入来调整曝光工艺参数、抗蚀剂工艺参数和显影工艺参数中的至少之一。
例如，实际测量数据包括在任一工艺过程开始之前测量得到的数据以及在任一工艺过程开始之后测量得到的数据。
例如，该方法还包括：更新实际工艺数据和实际测量数据；以及根据更新的实际工艺数据和实际测量数据来更新工艺模型和测量模型。
例如，该方法还包括：响应于验证了仿真工艺数据通过验证可用于实际生产，将仿真工艺数据应用于显示的实际制造过程。
例如，该验证方法还包括：将经验证可用于实际生产的仿真工艺数据形成为制造工艺文件。
根据另一方面，本公开提供了一种电子设备，包括存储器和处理器，存储器存储有可被处理器执行的指令，指令被处理器执行，以使处理器能够执行根据本公开实施例的方法。
根据另一方面，本公开提供了一种存储有计算机指令的非瞬时计算机可读存储介质， 其中，计算机指令用于使计算机执行根据本公开实施例的方法。
根据另一方面，本公开提供了一种计算机程序产品，包括计算机程序，计算机程序在被处理器执行时实现根据本公开实施例的方法。
根据另一方面，本公开提供了一种显示面板的生产方法，包括物理制造过程和数字处理过程，其中，
在所述物理制造过程中执行显示面板的至少一个工艺过程，得到实际工艺数据和实际测量数据；
在所述数字处理过程中，使用基于所述实际工艺数据和实际测量数据而生成的工艺模型和测量模型来执行根据本公开实施例的验证方法，以验证仿真工艺数据是否可用于实际生产。
例如，在所述物理制造过程中执行显示面板的至少一个工艺过程包括：依次执行前测量操作、准备操作、载入工艺数据操作、工艺加工操作和后测量操作，其中在所述载入工艺数据操作中载入了所述实际工艺数据，所述前测量操作、所述工艺加工操作和所述后侧量操作中的至少之一产生了所述实际测量数据。
例如，该生产方法还包括：响应于经验证所述仿真工艺数据可用于实际生产，将所述仿真数据作为实际工艺数据应用于所述物理制造过程中的载入工艺数据操作。
例如，该生产方法还包括：再次执行物理制造过程，以产生新的实际工艺数据和新的实际测量数据；以及基于新的实际工艺数据和新的实际测量数据来更新所述工艺模型和测量模型。
附图说明
图1是根据本公开一个实施例的显示面板的工艺数据的验证方法的流程图；
图2A是根据本公开另一个实施例的显示面板的工艺数据的验证方法的流程图；
图2B是根据本公开一个实施例的显示面板的生产方法的示意图；
图3是根据本公开一个实施例的光刻工艺数据的验证过程的示意图；
图4是根据本公开一个实施例的生成光刻工艺仿真工艺数据的流程图；
图5A和图5B是根据本公开一个实施例的光刻设计仿真中测试图形生成功能的示意图；
图5C是根据本公开一个实施例的光刻设计仿真中版图布尔运算功能的示意图；
图5D和图5E是根据本公开一个实施例的光刻设计仿真中工艺窗口分析功能的示 意图；
图5F是根据本公开一个实施例的光刻设计仿真中艺叠层反射率分析功能的示意图；
图5G是根据本公开一个实施例的光刻设计仿真中光刻光学成像仿真功能的示意图；以及
图6是根据本公开一个实施例适于实现显示面板的工艺数据的验证方法的电子设备的框图。
具体实施方式
为使本公开实施例的目的、技术方案和优点更加清楚，下面将结合本公开实施例中的附图，对本公开实施例中的技术方案进行清楚、完整的描述。显然，所描述的实施例是本公开的一部分实施例，而不是全部。基于所描述的本公开实施例，本领域普通技术人员在无需创造性劳动的前提下获得的所有其他实施例都属于本公开保护的范围。应注意，贯穿附图，相同的元素由相同或相近的附图标记来表示。在以下描述中，一些具体实施例仅用于描述目的，而不应该理解为对本公开有任何限制，而只是本公开实施例的示例。在可能导致对本公开的理解造成混淆时，将省略常规结构或配置。应注意，图中各部件的形状和尺寸不反映真实大小和比例，而仅示意本公开实施例的内容。
除非另外定义，本公开实施例使用的技术术语或科学术语应当是本领域技术人员所理解的通常意义。本公开实施例中使用的“第一”、“第二”以及类似词语并不表示任何顺序、数量或重要性，而只是用于区分不同的组成部分。
图1是根据本公开一个实施例的显示面板的工艺数据的验证方法的流程图。
如图1所示，工艺数据的验证方法可以包括操作S110至S130。
在操作S110，基于显示面板的任一工艺过程的设计数据来生成用于执行工艺过程的仿真工艺数据。
例如，设计数据可以包括设计文件。设计文件包括与显示面板的该工艺过程的设计相关的信息，例如但不限于制造显示面板的该工艺过程要使用的或生成的一个或多个部件的设计图和设计参数。在一些实施例中，设计数据还可以包括与显示面板设计相关的其他数据，例如与显示面板的制造工艺相关的参数、条件等等。以显示面板的光刻工艺过程为例，设计数据可以包括光刻工艺中涉及的以下数据中的至少之一：掩膜板的设计图、曝光参数设定信息、抗蚀剂参数设定信息和显影参数设定信息。可以通过例如用户交互界面来接收用户输入的各种设计数据，并根据接收到的设计数据来生成相应的工艺 数据作为仿真工艺数据。例如计算机可以对接收到掩膜板的设计图进行选择和切分，得到适合于设计者查看的测试图。在一些实施例中，计算机还可以根据曝光参数设定信息来生成曝光工艺参数，根据抗蚀剂参数设定信息来生成抗蚀剂工艺参数，根据彰显参数设定信息来生成彰显工艺参数。在一些实施例中，计算机还可以根据接收到的各种设计数据，通过模型推演或计算来生成各种仿真结果图，以供设计者查看。设计者可以根据仿真结果图，通过交互界面对设计数据进行调整。计算机可以根据设计者调整后的设计数据来重新生成仿真工艺数据。通过反复的调整，可以最终获得更符合实际需求的仿真工艺数据。这个过程也称作产品设计仿真过程。
产品设计仿真过程可以借助于仿真设计软件来实现。例如，仿真软件可以根据工艺要求，选择光刻胶。仿真软件可以根据所需形成的光刻图像，模拟设计掩膜版图像。仿真软件还可以模拟光刻胶在受到光辐照(曝光)后发生的光化学反应。光刻胶中受到光辐照的部分和未受到光辐照的部分的内部结构会发生不同的化学变化，使得光刻胶中受到光辐照的部分和未受到光辐照的部分在显影液中的溶解速度相差非常大。仿真软件可以模拟光刻胶的此种特性，结合掩膜板的图案，得到在光刻胶上形成的与掩膜版相应的图像。此外，仿真软件可以模拟曝光过程利用高精度对准光刻机进行，模拟不同的曝光时间、不同的曝光光源、不同类型的光刻胶、光刻胶的不同粘度和厚度等。例如，仿真软件在模拟光刻工艺过程所使用的工艺数据可以输出作为光刻工艺过程对应的仿真工艺数据。例如，掩膜版图形、曝光时间、曝光光源、光刻胶类型、光刻胶的粘度和厚度等。
在操作120，使用工艺模型来模拟使用仿真工艺数据来执行工艺过程，
在操作130，使用测量模型来基于模拟结果来验证仿真工艺数据是否可用于实际生产。
工艺模型是基于在显示面板的实际制造过程中产生的实际工艺数据来构建的，测量模型是基于在显示面板的实际制造过程中产生的实际工艺数据和实际测量数据来构建的。
例如，实际工艺数据和实际测量数据可以是显示面板的实际制造过程中产生的历史数据。由于受实际生产工艺中设备工艺波动的影响，实际工艺数据和实际测量数据也是波动的。因此，根据实际工艺数据建立的工艺模型以及根据实际工艺模型和实际测量数据建立的测量模型可以表征实际生产工艺中设备工艺波动情况。根据工艺模型和测量模型对仿真工艺数据进行虚拟验证仿真，可以得到贴近实际生产情况的工艺数据。
例如，实际测量数据包括在任一工艺过程开始之前测量得到的数据以及在任一工艺过程开始之后测量得到的数据。在任一工艺过程开始之前测量得到的数据可以包括工艺设备当前的静态数据和制备显示面板的原料数据等等。在任一工艺过程开始之后测量得到的数据可以包括工艺设备当前的工作运行数据和样品数据等等。
本公开实施例的验证方法适用于显示面板制造工艺中的任一工艺过程，可以基于设计数据生成用于执行工艺过程的仿真工艺数据并基于用实际数据构建的工艺模型和测量模型对仿真工艺数据的可行性进行虚拟验证，从而将显示面板的设计仿真的数据和虚拟验证仿真的数据互联互通，实现完整的工艺数字孪生。相比于传统技术中的人工验证，缩短了显示面板的设计和验证时间。
图2A是根据本公开另一个实施例的显示面板的工艺数据的验证方法的流程图。如图2A所示，工艺数据的验证方法可以包括操作S210至S260。
在操作S210，基于显示面板的任一工艺过程的设计数据来生成用于执行工艺过程的仿真工艺数据。
例如，可以使用仿真软件来基于显示面板的任一工艺过程的设计数据来生成用于执行工艺过程的仿真工艺数据。例如，用户可以启动仿真软件的界面，并在界面中设置参数，以使得计算机基于显示面板的设计数据和用户设置的参数来生成用于执行显示面板的工艺过程的仿真工艺数据。仿真工艺数据可以包括多种仿真工艺参数，例如但不限于GDS设计图、剂量(Dose)、特征尺寸(CD，Critical Dimension)、机械设计图、电路设计图、结构设计图、曝光波长、光谱比重、光源类型、孔径值、光刻胶胶厚、显影液浓度、软烤温度、预烤温度和时间等。作为示例，计算机可以基于显示面板的设计图生成测试图，并根据用户设置的参数生成诸如曝光波长、孔径值、光刻胶厚度、显影液浓度之类的各种仿真工艺参数。用户输入的参数可以表征用户对显示面板规格的需求。在一些实施例中，还可以根据测试图和/或生成的各种工艺参数来生成仿真结果图，以供用户查看。用户可以根据仿真结果图来调整输入，计算机可以根据调整后的用户输入的来相应调整所生成的各种工艺参数。用户还可以在仿真软件的界面上可以对仿真过程进行调试。仿真软件的仿真过程可以是模拟工艺过程的多种环境参数、设备参数、材料参数、化学反应和物理反应等，通过求解器以数值计算的方式进行仿真计算。
例如，显示面板的设计数据可以包括显示面板的任一工艺过程的设计数据。显示面 板的工艺过程包括背板制造工艺、蒸镀封装工艺和模组工艺等等。显示面板的设计数据可以包括GDS设计图、电路设计图，结构设计图、机械设计图、剂量、特征尺寸等等。在不同的工艺阶段，可以采用不同的仿真软件。对于每一种工艺过程，仿真软件都会生成相应的仿真工艺参数。每个工艺过程对应的仿真工艺参数的类型可能是相同的，也可能是不同的。例如，对于背板制造工艺中的光刻工艺过程，输入至仿真软件的设计数据可以包括GDS设计图、特征尺寸和推荐剂量等。
上述过程可以称作显示面板设计仿真过程。在通过上述显示面板设计仿真生成了仿真工艺数据之后，可以基于数学模型，模拟使用仿真工艺数据来执行工艺过程，并基于模拟结果来验证仿真工艺数据是否可用于实际生产，该过程也称作虚拟验证仿真。例如，仿真软件输出的仿真工艺数据可作为虚拟验证仿真过程的输入。将经验证可用于实际生产的的仿真工艺数据可以形成制造工艺文件。制造工艺文件可以以图样、简图、文字内容或表格的形式展示。制造工艺文件包括的工艺数据是可以用于实际生产的工艺数据。制造工艺文件也可以包括工艺规程和工艺卡。工艺规程可以包括工艺过程的操作方法，工艺卡可以包括工艺过程涉及的工艺参数和工艺标准。例如制造工艺文件包括对仿真软件输出的仿真工艺数据进行验证后的满足显示面板需求的仿真工艺数据，包括剂量信息，曝光波长、光谱比重、光源类型、孔径值、光刻胶胶厚、显影液浓度、软烤温度、预烤温度和时间等。
在得到仿真工艺数据后，还需要对仿真工艺数据进行虚拟验证仿真。例如，基于数据模型模拟使用仿真工艺数据来执行工艺过程，并基于模拟结果来验证仿真工艺数据是否可用于实际生产。数学模型可以包括工艺模型和测量模型。在一些实施例中，数学模型还可以包括控制模型。下面将结合以下步骤S220至S240对虚拟验证仿真进行说明。
在操作S220，使用工艺模型来确定在使用仿真工艺数据执行工艺过程的情况下所能得到的显示面板的特征数据。
工艺模型可以是根据实际工艺数据构建的工艺机理模型。工艺模型可以以仿真工艺数据作为输入并且以显示面板的特征数据作为输出，通过建立输入与输出之间的线性或非线性关系来模拟工艺过程的执行。例如，根据工艺机理模型(例如，光刻的物理模型，刻蚀和化学气相沉积的漂移扩散模型)，建立一个准确的数学公式来标识输入输出之间的关系(线性或者非线性)。再通过实验或者量产的工艺参数，对该数学公式进行调优， 以得到工艺模型。从而工艺模型可以基于多种仿真工艺参数与特征数据之间的线性关系或非线性关系生成显示面板的任一工艺过程相应的特征数据。
在操作S230，使用控制模型对实际工艺数据应用反馈参数算法来计算工艺波动，并将工艺波动施加到工艺模型输出的特征数据。
控制模型可以是根据实际工艺数据来构建的波动规律模型。控制模型用于将基于实际工艺数据计算出的工艺波动应用于模拟结果，以产生调整后的模拟结果。控制模型可以模拟要仿真的工艺过程的运行逻辑并实现模型状态的管理(数据筛选，控制逻辑)。控制模型可以选择一个最优化过程控制模型中的反馈参数算法来根据实际制造过程中产生的工艺数据和/或测量数据来计算工艺波动。反馈参数算法可以对工艺波动进行自动校正。运行逻辑可以是由工艺工程师将业务流程抽象出模型。模型状态管理可以包括对每个业务流程需要的工艺数据来源的筛选。业务流程的改变需要调节控制逻辑，例如增加、删除、改变和查询。反馈参数算法可以包括移动平均算法、加权移动平均算法和指数移动平均算法之一。
在操作S240，使用测量模型将实际特征数据与工艺模型输出的特征数据进行差异性比较。
测量模型可以是根据实际测量数据和实际工艺数据来构建的统计学模型。例如可以根据实际测量数据基于机器学习算法(SVM，决策树，随机森林，逻辑回归，贝叶斯等)构建测量模型。测量模型用于通过将针对仿真工艺数据的模拟结果与针对实际工艺数据的实际测量数据相比较，来验证仿真工艺数据是否可用于实际生产。
例如，测量模型可以在实际工艺数据当中确定与仿真工艺数据之间的相似度高于预设相似度阈值的实际工艺数据作为相似工艺数据，在实际测量数据当中确定使用相似工艺数据实际执行工艺过程所得到的显示面板的特征数据作为实际特征数据。然后，测量模型可以将上述实际特征数据与上述由工艺模型产生的并由控制模型施加了工艺波动之后的特征数据进行比较，如果二者之间的差异小于预设差异阈值，确定仿真工艺数据可用于实际生产。
上述实施例中虽然通过与阈值相比较的方式来判定差异的大小是否符合预定的要求，然而本公开的实施例不限于此，还可以根据其他计算方式来确定差异的大小是否符合预定的要求，这里不再赘述。
在操作S250，基于比较结果来判断仿真工艺数据是否通过验证，如果通过验证，则执行操作S260，否则可以返回步骤S210，以便用户调整设计数据或者调整参数设置。
例如，如果操作S230中通过基于仿真工艺参数进行模拟计算得到的特征数据与实际生产过程中采用与仿真工艺参数相似的工艺参数制造得到结构的特征数据匹配，则认为仿真工艺数据通过了验证，否则认为未通过验证。验证结果通过产品需求的制造工艺标准，可认为通过关于显示面板的产品设计仿真得到的仿真工艺数据在真实的物理工艺设备中可以生成出符合预设需求的合格显示面板。如果验证结果不通过，可认为通过关于显示面板的产品设计仿真得到的仿真工艺数据在真实的物理工艺设备中生成显示面板可能不符合预设需求，从而需要对显示面板的设计数据进行修改，以得到满足显示面板需求的制造工艺标准的验证结果。
以光刻工艺为例，假设在操作S210生成了曝光工艺参数A1、抗蚀剂工艺参数A2和彰显工艺参数A3，那么在操作S220基于工艺参数A1、A2和A3来模拟光刻工艺过程，通过计算得到了光刻图案的形状、尺寸等特征数据。在操作S230对操作S220模拟出的特征数据添加工艺波动。然后，在步骤S240可以使用测量模型在实际生产过程中使用的各种各样的工艺参数的数值当中，确定与A1、A2和A3之间的差值分别小于预设阈值的曝光工艺参数、抗蚀剂工艺参数和彰显工艺参数。如果找到了这样的工艺参数，例如曝光工艺参数B1、抗蚀剂工艺参数B2和彰显工艺参数B3，其中A1与B1之间的差值、A2与B2之间的差值以及A3与B3之间的差值均小于预先设定的阈值，那么则将实际工艺数据B1、B2、B3作为仿真工艺数据A1、A2、A3的相似工艺数据。然后，在实际测量数据当中，寻找使用曝光工艺参数B1、抗蚀剂工艺参数B2和彰显工艺参数B3进行实际光刻工艺的情况下测量得到的光刻图案的特征数据，例如光刻图案的形状、尺寸等，作为实际特征数据。然后，在步骤S250将实际特征数据(即测量得到的光刻图案的形状、尺寸等)与步骤S230提供的特征数据(即，工艺模型通过虚拟仿真得到的光刻图案的尺寸、形状等)进行比较，如果二者之间的差异小于预设的阈值，则认为基于仿真工艺参数A1、A2和A3通过虚拟仿真得到的光刻图案与实际生产过程中基于相似的实际工艺参数B1、B2和B3执行光刻工艺所得到的光刻图案是大体上一致的，从而可以认为仿真工艺参数A1、A2和A3在实际制造当中是可行的，即，通过了验证。反之，如果基于仿真工艺参数A1、A2和A3通过虚拟仿真得到的光刻图案与基于工艺 参数B1、B2和B2在实际制造过程中得到的光刻图案之间的差异过大以至于超过了可接受的范围，则认为仿真工艺参数A1、A2和A3应用于实际制造是不可行的，即，未通过验证。
在操作S260，将仿真工艺数据应用于显示面板的实际制造过程。
例如，在显示面板设计经过虚拟验证仿真后，如果能够达到标准，则将设计数据导入真实的物理工艺设备。如果虚拟验证仿真的数据不满足实际物理工艺生产的条件，可以及时修改显示面板的设计数据。通过虚拟验证的方法，将满足实际物理工艺生产的条件仿真工艺数据应用于显示面板的实际制造过程，可以缩短显示面板设计验证时间，加快新显示面板上市速度。
在一些实施例中，操作S230可以是可选的。例如，在一些实施例中，可以省略操作230，以提高处理速度。在省略了操作S230情况下，在操作S240中，测量模型可以将操作S220中工艺模型输出的显示面板的特征数据与实际特征数据进行差异比较，以此来判断仿真工艺参数是否通过验证。
在本公开实施例中，还可以更新实际工艺数据和实际测量数据，并根据更新的实际工艺数据和实际测量数据来更新数学模型，例如更新上述工艺模型、测量模型和控制模型中的至少之一。
例如，可以周期性地或者在完成真实的制造工艺后，再次获取真实的制造工艺产生的实际工艺数据和实际测量数据来加入或替换已有的实际工艺数据和实际测量数据，从而实现实际工艺数据和实际测量数据的更新。可以基于更新后的实际工艺数据和实际测量数据来调整数学模型。虚拟验证仿真过程可以使用更新后的数学模型对显示面板设计仿真过程产生的仿真工艺数据进行验证。
在一些实施例中，还可以根据验证结果对生产参数进行优化。在一些实施例中，还可以根据验证结果进行故障预测维修和不良预测。
图2B是根据本公开一个实施例的显示面板的生产方法的示意图。如图2B所示，显示面板的生产包括数字处理过程260和物理制造过程270。
数字处理过程260也称作数字工艺，是虚拟工艺过程，包括显示面板设计仿真261和虚拟验证仿真262。物理制造过程270也称作物理工艺，是真实的工艺过程。物理制造过程270包括前测量、准备工作、载入工艺数据、工艺加工和后测量过程。物理制造 过程270产生的数据可以包括实际工艺数据和实际测量数据。在物理制造过程270中，前测量过程产生工艺前的实际测量数据，后测量过程产生工艺后的实际测量数据。准备工作过程和工艺加工过程可以产生工艺数据。物理制造过程270产生的实际数据可以用于构建和优化数字处理过程260所需的数学模型。
虚拟验证仿真262过程的构建数学模型可以包括工艺模型2621、控制模型2622和测量模型2623。工艺模型2621可以是根据实际工艺数据构建的，控制模型2622也可以是根据实际工艺数据来构建的，测量模型2623可以是根据实际测量数据和实际工艺数据来构建的。
在本公开实施例中，数字处理过程260中产品设计仿真261过程产生的仿真工艺数据包括多种仿真工艺参数。在虚拟验证仿真262中，可以使用工艺模型2621来确定在使用仿真工艺数据执行工艺过程的情况下所能得到的显示面板的特征数据；使用控制模型2622对实际工艺数据应用反馈参数算法来计算工艺波动并将工艺波动施加到工艺模型2621输出的特征数据，得到调整后的特征数据；以及使用测量模型2623将调整后的特征数据与实际特征数据进行差异性比较，并响应于实际特征数据与工艺模型2621输出的特征数据之间的差异小于预设差异阈值，确定仿真工艺数据通过验证，可用于实际生产。测量模型2623在实际工艺数据当中确定与仿真工艺数据之间的相似度高于预设相似度阈值的实际工艺数据作为相似工艺数据，在实际测量数据当中确定使用相似工艺数据实际执行工艺过程所得到的显示面板的特征数据作为实际特征数据。
例如，对于剂量和特征尺寸，剂量与特征尺寸具有线性关系，遵循y＝kx的约束。其中y为剂量，x为特征尺寸，k可以是一个线性参数，线性参数可以是根据历史经验总结出来。在仿真工艺数据为剂量的情况下，工艺模型2621可以根据线性关系y＝kx，生成相应的特征尺寸。根据不同的工艺和机理，参数k可以是线性，也可以是非线性的。
例如，控制模型2622可以是根据设备的工艺波动形成的波动规律模型。
例如，反馈参数算法包括移动平均算法、加权移动平均算法和指数移动平均算法。可以从移动平均算法、加权移动平均算法和指数移动平均算法中选择其中一种算法作为最优化算法。
例如，移动平均算法包括根据以下公式来计算连续多个周期的工艺参数的平均值：
Figure PCTCN2022116149-appb-000007
其中C 1，C 2，...C n是每个周期的工艺参数的值，n为大于1的整数。
例如，加权移动平均算法包括末日加权算法、线性加权算法、梯形加权算法和平方系数加权算法之一。
例如，末日加权算法包括根据以下公式来计算连续多个周期的工艺参数的加权平均值：
Figure PCTCN2022116149-appb-000008
其中C 1，C 2，...C n是每个周期的工艺参数的值，n为大于1的整数。
例如，线性加权算法包括根据以下公式来计算连续多个周期的工艺参数的加权平均值：
Figure PCTCN2022116149-appb-000009
其中C 1，C 2，...C n是每个周期的工艺参数的值，n为大于1的整数。
例如，梯形加权算法包括根据以下公式来计算连续多个周期的工艺参数的加权平均值：
Figure PCTCN2022116149-appb-000010
其中C 1，C 2，...C n是每个周期的工艺参数的值，n为大于1的整数。
例如，平方系数加权算法包括根据以下公式来计算连续多个周期的工艺参数的加权平均值：
Figure PCTCN2022116149-appb-000011
其中C 1，C 2，...C n是每个周期的工艺参数的值，n为大于1的整数。
例如，指数移动平均算法包括根据以下公式来计算连续多个周期的工艺参数的加权平均值：
Figure PCTCN2022116149-appb-000012
其中C 1，C 2，...C n是每个周期的工艺参数的值，n为大于1的整数，α为加权指数。
例如，测量模型2623可以是由设备的历史的测量数据形成的设备测量的统计模型。
历史的测量数据是实际工艺生成中的真实测量的数据，真实测量的数据根据构建测量模型。通过测量模型2623将控制模型2622生成的调整后特征数据与实际特征数据进行差异性比较，并基于比较结果来判断仿真工艺数据是否通过验证。构建的测量模型2623可以用于虚拟验证仿真中的验证环节，因为虚拟验证环节没有进行实际的生产，所以需要测量模型2623来进行虚拟量测。
例如，在完成背板制造工艺的虚拟验证仿真后，将虚拟验证仿真的输出的仿真工艺参数与历史的实际工艺数据进行匹配，如果是，则认为仿真工艺数据通过了验证，否则认为未通过验证。
基于本公开实施例的显示面板的工艺数据的验证方法，本公开还可以提供一种显示面板的生产方法。
例如，显示面板的生产方法包括物理制造过程(例如上述物理制造过程270)和数字处理过程(例如上述数字处理过程260)。
在物理制造过程中，可以执行显示面板的至少一个工艺过程，得到实际工艺数据和实际测量数据。例如在所述物理制造过程中可以依次执行前测量操作、准备操作、载入工艺数据操作、工艺加工操作和后测量操作，其中在所述载入工艺数据操作中载入了所述实际工艺数据，所述前测量操作、所述工艺加工操作和所述后侧量操作中的至少之一产生了所述实际测量数据。
在数字处理过程中，可以使用基于所述实际工艺数据和实际测量数据而生成的工艺模型和测量模型来执行上述任意实施例的验证方法，以验证仿真工艺数据是否可用于实际生产。在一些实施例中，还可以响应于经验证所述仿真工艺数据可用于实际生产，将所述仿真数据作为实际工艺数据应用于所述物理制造过程中的载入工艺数据操作。
例如，实际测量数据包括中任一工艺过程开始之前测量得到的数据以及在任一工艺过程开始之后测量得到的数据。例如，物理制造过程270的前测量操作得到的测量数据和后测量操作得到的测量数据。
例如，在显示面板的生产方法中，还可以再次执行物理制造过程，以产生新的实际工艺数据和新的实际测量数据；以及基于新的实际工艺数据和新的实际测量数据来更新数学模型。再次执行物理制造过程270的前测量操作、准备操作、载入工艺数据操作、 工艺加工操作和后测量操作后，将此次执行物理制造过程270实际生产的仿真数据作为实际工艺数据应用于数字处理过程260，作为更新的实际工艺数据和实际测量数据，并根据更新的实际工艺数据和实际测量数据来更新数学模型。
通过本公开实施例，数字工艺根据物理工艺提供真实工艺数据构建和调整数据模型，实现数字工艺和物理工艺之间的数据共享和数据交互。在数字工艺中，显示面板设计仿真和虚拟验证仿真的数据互联互通，形成一个完整的工艺数字孪生过程，从而形成一个产品设计-产品设计仿真-虚拟验证仿真的工艺数字孪生闭环，实现虚拟数据和真实数据的互联互通。通过虚拟验证仿真对产品设计仿真的结果进行验证并给出显示面板的设计数据的优化方向，从而及时修改显示面板的设计数据，实现缩短显示面板设计验证时间，加快新显示面板上市速度。
显示面板的任一工艺过程可以包括背板制造工艺。背板制造工艺可以包括涂覆、光刻和刻蚀工艺。涂覆工艺包括溅射过程(Sputter)和等离子体增强化学气相沉积过程(PECVD，Plasma Enhanced Chemical Vapor Deposition)。溅射过程利用物理溅射原理沉积金属膜层。PECVD利用化学气相沉积的方法沉积半导体或非金属膜层。光刻工艺包括导轨过程(Track)和光刻过程(Aligner)，导轨过程在基板上涂覆对光敏感的光刻胶，曝光完成后将被曝光的光刻胶显影掉。光刻过程用紫外光将没有掩膜的光刻胶感光，完成曝光。刻蚀工艺包括干刻蚀(Dry Etch)、湿刻蚀(Wet Etch)、去胶工艺(Strip)和清洗过程(Clearner)。干刻蚀用反应气体干法刻蚀掉非金属或金属膜层，湿刻蚀用化学药液如酸湿法刻蚀掉金属膜层。去胶工艺用化学药液将外曝光的光刻胶剥离掉。清洗过程在沉积前对膜层进行清洗。
图3是根据本公开一个实施例的虚拟验证仿真的示意图。
如图3所示，物理光刻工艺包括多个光刻过程310、320、330。在每个光刻过程结束后，可以执行一次测量操作，以获得实际测量数据。例如在光刻过程310之后执行一次测量操作340，在光刻过程320之后执行测量操作350。可以获取每个光刻过程产生的工艺数据以及每个测量操作产生的测量数据以用于构建虚拟验证仿真中的数学模型。
例如，光刻过程310产生工艺数据PD1，随后测量操作340产生测量数据MD1，接着下一周期的光刻过程320产生工艺数据PD2，随后测量操作350产生测量数据MD2，接着下一周期的光刻过程330产生工艺数据PD3，以此类推。根据光刻过程生成的工艺 数据和针对光刻过程进行测量生成的测量数据可以用于构建虚拟验证仿真360中的测量模型。在一些实施例中，这些工艺数据和测量数据还可以用于数学模型的调整和优化。
图4是根据本公开一个实施例的生成光刻工艺仿真工艺数据的流程图。
显示基板的任一工艺过程包括背板制造工艺中用于形成膜层的光刻工艺，光刻工艺可以包括掩模设计、曝光、抗蚀和显影过程。设计数据包括掩模板的设计图，基于显示面板的设计数据来生成光刻工艺的仿真工艺数据的步骤可以包括操作S410至S440中的至少之一。
在操作S410，对掩膜板的设计图的至少部分区域进行仿真，得到测试图。
例如，在掩模设计过程中，在仿真软件中将掩模板的设计图的导入设计数据，可以在基板上限定后续需要刻蚀的目标图形的位置进行选定和仿真，从而生成测试图。
在操作S420，根据接收到的曝光参数设定信息来生成曝光工艺参数。
例如，在曝光过程中，在仿真软件中生成曝光机设备的曝光工艺参数，生成曝光工艺参数包括以下各项中的至少之一：数值孔径、波长、相干因子、照明类型、曝光倍率和焦点位置等。
在操作S430，根据接收到的抗蚀剂参数设定信息来生成抗蚀剂工艺参数。
例如，在抗蚀过程中，生成抗蚀剂工艺参数包括以下各项中的至少之一：光致抗蚀剂的类型、光致抗蚀剂的厚度和显影速率、基底材料和光敏化合物PAC浓度分布。
在仿真软件中导入光刻胶参数、光刻胶类型，光刻胶胶厚、显影速率、不同衬底膜层(金属或非金属材料)等参数，能够得到光敏化合物浓度分布。
在操作S440，根据接收到的显影参数设定信息来生成显影工艺参数。
在本公开实施例中，生成光刻工艺仿真工艺数据的方法在操作S410至S440的基础上还包括基于曝光工艺参数对测试图进行透镜投影仿真，得到空间像数据；以及基于显影参数来生成显影后的膜层的图形数据。
例如，基于显示面板的设计数据来生成光刻工艺的仿真工艺数据的步骤在操作S410至S440的基础上还可以包括通过用户交互界面来展示空间像数据和图形数据中的至少之一并接收用户输入，以及根据用户输入来调整曝光工艺参数、抗蚀剂工艺参数和显影工艺参数中的至少之一。
例如，在曝光过程中，基于经过透镜投影后的空间像分布，可以导出空间像数据。 在显影过程中，将显影参数导入仿真软件的显影模块，可以输出显影之后的图形。在用户交互界面来展示空间像数据和/或图像数据中，使得用户可以根据展示的空间像数据和/或图像数据，确定空间像数据和/或图像数据是否符合条件。在不符合条件的情况下，输入相关设置，以调整曝光工艺参数、抗蚀剂工艺参数和显影工艺参数中的至少之一。
图5A和图5B是根据本公开一个实施例的光刻设计仿真中测试图形生成功能的示意图。图5C是根据本公开一个实施例的光刻设计仿真中版图布尔运算功能的示意图。图5D和图5E是根据本公开一个实施例的光刻设计仿真中工艺窗口分析功能的示意图。图5F是根据本公开一个实施例的光刻设计仿真中艺叠层反射率分析功能的示意图。图5G是根据本公开一个实施例的光刻设计仿真中光刻光学成像仿真功能的示意图。
如图5A至5C所示，可以对掩膜板的设计图的至少部分区域进行仿真，得到测试图。可以根据设定的规则，生成常规系列的测试图像。也可以根据用户的特定需求，生成特殊测试图形。如图5A所示的交互界面用于展示预先设定的默认规则或者接收由用户根据特殊需要而输入的规则。计算机可以根据规则(例如X方向上的剪裁间距Clip Pitch X和剪裁尺寸Clip Size X和Y方向上的剪裁间距Clip Pitch Y和剪裁尺寸Clip Size Y等等)对掩膜板的设计图的至少部分区域进行位置选定和仿真，得到如图5B所示的测试图。如图5B所示，测试图可以包含特征尺寸cd、版图中图形的数量、图形之间的排列间距space、图形之间的缺口间隔gap和图形之间的中心间隔pitch等信息。如图5C所示，在版图布尔运算功能界面中，可以对测试图(例如图5B所示的测试图)进行分区域和分单元的查看和编辑，还可以对测试图中的图形进行布尔运算和对图形进行膨胀、收缩、翻转和抽取等操作，以及提供在动态范围进行压缩和放大的功能。例如，如图5C所示，原测试图包括3个并列排布的“I”型图形元素和1个“L”图形元素。通过对原测试图的布尔运算，使3个并列排布的“I”型图形元素合并成一个“I”型图形元素。布尔运算还可以包括对多个图形元素进行差集、并集和交集运算。
如图5D至5F所示，在生成测试图之后，可以通过交互界面来接收曝光参数设定信息、抗蚀剂参数设定信息和显影参数设定信息中的至少之一。例如，可以通过如图5D所示的界面来接收用户输入的曝光参数设定信息。计算机可以根据接收到的曝光参数设定信息生成曝光工艺参数，根据接收到的抗蚀剂参数设定信息来生成抗蚀剂工艺参数，根据接收到的显影参数设定信息来生成显影工艺参数。如图5E所示，基于如图5D所 设定的各种参数信息，可以进行工艺窗口分析。例如计算机根据用户给定的曝光剂量(Dose Factor)和离焦量(Defocus Values)，获取仿真图形对应的光刻工艺窗口。例如，计算机根据选择在曝光仿真过程中可以关联分析空间像图像(Aerial image)、光刻胶中像(bulk image)、光敏化合物浓度分布图像(PAC image)。在曝光仿真过程中还可以为工艺窗口分析设置曝光焦点矩阵(曝光剂量和离焦量)、工艺窗口测量方法、特征尺寸规范(CD specification)、侧壁角规范(sidewall angle specification)抗蚀剂规范(resist less specification)、曝光纬度规范(expose latitude specification)、线边缘粗糙度规范(line edge roughness specification)等参数。计算机通过为工艺窗口分析设置的参数进行仿真，以保证能够正确光刻出掩模的测试图的图形。例如光刻工艺窗口的部分仿真结果如图5E所示，以椭圆为工艺窗口测量方法，仿真得到最佳焦点位置、最佳剂量和最佳特征尺寸等。此外也可以改变工艺窗口的形状和限制条件等参数，从而对多种形状的工艺窗口和限制条件进行仿真。如图5F所示，还可以进行工艺叠层反射率分析。例如可以针对单光刻胶膜层，分析光刻胶膜层的反射率(reflectivity)，从而对多种单光刻胶膜层的厚度(thickness)进行仿真。也可以针对光刻胶加抗反层的多层膜结构，分析基底的反射率和多层膜的反射率，从而对光刻胶加抗反层的多层膜结构进行仿真。由此通过光刻工艺窗口仿真和工艺叠层反射率仿真可以得到曝光工艺参数，例如数值孔径、波长、相干因子、照明类型、曝光倍率和焦点位置等，以及抗蚀剂工艺参数，例如光致抗蚀剂的类型、光致抗蚀剂的厚度和显影速率、基底材料和光敏化合物PAC浓度分布。
如图5G所示，在一些实施例中，还可以基于曝光工艺参数对所述测试图进行透镜投影仿真，得到空间像数据。在一些实施例中，还可以基于显影参数来生成显影后的所述膜层的图形数据。例如在光刻光学成像功能界面中，可以对空间像、光刻胶中像和光敏化合物/光酸产生剂(PAC/PAG)浓度进行仿真建模，得到如图5G所示的光学成像仿真结果。例如，针对光源，可以支持对多种光源照明方式、多种光源分布、单波长照明和宽波带照明方式的仿真。针对掩模，可以进行二维薄掩模近似仿真和三维厚掩模分析仿真。针对仿真方法，可以采用基尔霍夫近似仿真和严格耦合波方法仿真。针对透镜，可以进行波像差分析仿真和干式系统及浸没式系统仿真。针对光刻胶，可以通过传输矩阵法，对光刻胶光学效应建模。例如，通过光刻建模使得仿真过程可以基于图5C所示的版图的“L”型图形元素进行光刻仿真，并基于仿真得到曝光工艺参数对测试图进行透 镜投影仿真，得到空间像数据。然后，可以通过用户交互界面来展示所述空间像数据和所述图形数据中的至少之一并接收用户输入。例如通过用户交互界面来展示如图5G所示的空间像数据、光刻胶中像和光敏化合物/光酸产生剂(PAC/PAG)浓度中的至少之一，以供用户参考。然后，用户可以通过交互界面来调整各种参数设定信息，计算机可以根据用户输入来调整所述曝光工艺参数、抗蚀剂工艺参数和显影工艺参数中的至少之一。
图6是根据本公开一个实施例适于实现显示面板的工艺数据的验证方法的电子设备的框图。如图6所示，根据本公开实施例的电子设备600包括处理器601，其可以根据存储在只读存储器(ROM)602中的程序或者从存储部分608加载到随机访问存储器(RAM)603中的程序而执行各种适当的动作和处理。处理器601例如可以包括通用微处理器(例如CPU)、指令集处理器和/或相关芯片组和/或专用微处理器(例如，专用集成电路(ASIC))等等。处理器601还可以包括用于缓存用途的板载存储器。处理器601可以包括用于执行根据本公开实施例的方法流程的不同动作的单一处理单元或者是多个处理单元。
在RAM 603中，存储有电子设备600操作所需的各种程序和数据。处理器601、ROM 602以及RAM 603通过总线604彼此相连。处理器601通过执行ROM 602和/或RAM 603中的程序来执行根据本公开实施例的方法流程的各种操作。需要注意，所述程序也可以存储在除ROM 602和RAM 603以外的一个或多个存储器中。处理器601也可以通过执行存储在所述一个或多个存储器中的程序来执行根据本公开实施例的方法流程的各种操作。
根据本公开的实施例，电子设备600还可以包括输入/输出(I/O)接口605，输入/输出(I/O)接口605也连接至总线604。电子设备600还可以包括连接至I/O接口605的以下部件中的一项或多项：包括键盘、鼠标等的输入部分606；包括诸如阴极射线管(CRT)、液晶显示器(LCD)等以及扬声器等的输出部分607；包括硬盘等的存储部分608；以及包括诸如LAN卡、调制解调器等的网络接口卡的通信部分609。通信部分609经由诸如因特网的网络执行通信处理。驱动器610也根据需要连接至I/O接口605。可拆卸介质611，诸如磁盘、光盘、磁光盘、半导体存储器等等，根据需要安装在驱动器610上，以便于从其上读出的计算机程序根据需要被安装入存储部分608。
本公开还提供了一种非瞬时计算机可读存储介质，该计算机可读存储介质可以是上 述实施例中描述的设备/装置/系统中所包含的；也可以是单独存在，而未装配入该设备/装置/系统中。上述计算机可读存储介质承载有一个或者多个程序，当上述一个或者多个程序被执行时，实现根据本公开实施例的方法。
根据本公开的实施例，计算机可读存储介质可以是非易失性的计算机可读存储介质，例如可以包括但不限于：便携式计算机磁盘、硬盘、随机访问存储器(RAM)、只读存储器(ROM)、可擦式可编程只读存储器(EPROM或闪存)、便携式紧凑磁盘只读存储器(CD-ROM)、光存储器件、磁存储器件、或者上述的任意合适的组合。在本公开中，计算机可读存储介质可以是任何包含或存储程序的有形介质，该程序可以被指令执行系统、装置或者器件使用或者与其结合使用。例如，根据本公开的实施例，计算机可读存储介质可以包括上文描述的ROM 602和/或RAM 603和/或ROM 602和RAM 603以外的一个或多个存储器。
本公开的实施例还包括一种计算机程序产品，其包括计算机程序，该计算机程序包含用于执行流程图所示的方法的程序代码。当计算机程序产品在计算机系统中运行时，该程序代码用于使计算机系统实现本公开实施例所提供的产品的工艺数据的验证方法。
在该计算机程序被处理器601执行时执行本公开实施例的系统/装置中限定的上述功能。根据本公开的实施例，上文描述的系统、装置、模块、单元等可以通过计算机程序模块来实现。
在一种实施例中，该计算机程序可以依托于光存储器件、磁存储器件等有形存储介质。在另一种实施例中，该计算机程序也可以在网络介质上以信号的形式进行传输、分发，并通过通信部分609被下载和安装，和/或从可拆卸介质611被安装。该计算机程序包含的程序代码可以用任何适当的网络介质传输，包括但不限于：无线、有线等等，或者上述的任意合适的组合。
在这样的实施例中，该计算机程序可以通过通信部分609从网络上被下载和安装，和/或从可拆卸介质611被安装。在该计算机程序被处理器601执行时，执行本公开实施例的系统中限定的上述功能。根据本公开的实施例，上文描述的系统、设备、装置、模块、单元等可以通过计算机程序模块来实现。
根据本公开的实施例，可以以一种或多种程序设计语言的任意组合来编写用于执行本公开实施例提供的计算机程序的程序代码，具体地，可以利用高级过程和/或面向对象 的编程语言、和/或汇编/机器语言来实施这些计算程序。程序设计语言包括但不限于诸如Java，C++，python，“C”语言或类似的程序设计语言。程序代码可以完全地在用户计算设备上执行、部分地在用户设备上执行、部分在远程计算设备上执行、或者完全在远程计算设备或服务器上执行。在涉及远程计算设备的情形中，远程计算设备可以通过任意种类的网络，包括局域网(LAN)或广域网(WAN)，连接到用户计算设备，或者，可以连接到外部计算设备(例如利用因特网服务提供商来通过因特网连接)。
附图中的流程图和框图，图示了按照本公开各种实施例的系统、方法和计算机程序产品的可能实现的体系架构、功能和操作。在这点上，流程图或框图中的每个方框可以代表一个模块、程序段、或代码的一部分，上述模块、程序段、或代码的一部分包含一个或多个用于实现规定的逻辑功能的可执行指令。也应当注意，在有些作为替换的实现中，方框中所标注的功能也可以以不同于附图中所标注的顺序发生。例如，两个接连地表示的方框实际上可以基本并行地执行，它们有时也可以按相反的顺序执行，这依所涉及的功能而定。也要注意的是，框图或流程图中的每个方框、以及框图或流程图中的方框的组合，可以用执行规定的功能或操作的专用的基于硬件的系统来实现，或者可以用专用硬件与计算机指令的组合来实现。
本领域技术人员可以理解，本公开的各个实施例和/或权利要求中记载的特征可以进行多种组合或/或结合，即使这样的组合或结合没有明确记载于本公开中。特别地，在不脱离本公开精神和教导的情况下，本公开的各个实施例和/或权利要求中记载的特征可以进行多种组合和/或结合。所有这些组合和/或结合均落入本公开的范围。
以上对本公开的实施例进行了描述。但是，这些实施例仅仅是为了说明的目的，而并非为了限制本公开的范围。尽管在以上分别描述了各实施例，但是这并不意味着各个实施例中的措施不能有利地结合使用。本公开的范围由所附权利要求及其等同物限定。不脱离本公开的范围，本领域技术人员可以做出多种替代和修改，这些替代和修改都应落在本公开的范围之内。

Claims (29)

  1. 一种显示面板的工艺数据的验证方法，包括：
    基于显示面板的任一工艺过程的设计数据来生成用于执行所述工艺过程的仿真工艺数据；
    使用工艺模型来模拟使用所述仿真工艺数据执行所述工艺过程；以及
    使用测量模型来基于模拟结果验证所述仿真工艺数据是否可用于实际生产，
    其中所述工艺模型是基于在显示面板的实际制造过程中产生的实际工艺数据来构建的，所述测量模型是基于在显示面板的实际制造过程中产生的实际工艺数据和实际测量数据来构建的。
  2. 根据权利要求1所述的方法，其中，所述使用工艺模型来模拟使用所述仿真工艺数据执行所述工艺过程包括：
    使用所述工艺模型来确定在使用所述仿真工艺数据执行所述工艺过程的情况下所能得到的显示面板的特征数据。
  3. 根据权利要求1或2所述的方法，其中，所述使用测量模型来基于模拟结果验证所述仿真工艺数据是否可用于实际生产包括：
    使用所述测量模型在所述实际工艺数据当中确定与所述仿真工艺数据之间的相似度高于预设相似度阈值的实际工艺数据作为相似工艺数据；
    在实际测量数据当中确定使用所述相似工艺数据实际执行所述工艺过程所得到的显示面板的特征数据作为实际特征数据；以及
    响应于所述实际特征数据与所述工艺模型输出的特征数据之间的差异小于预设差异阈值，确定所述仿真工艺数据可用于实际生产。
  4. 根据权利要求1至3中任一项所述的方法，还包括：在使用所述测量模型来基于模拟结果验证所述仿真工艺数据是否可用于实际生产之前，使用控制模型对实际工艺数据应用反馈参数算法来计算工艺波动，并将工艺波动施加到所述工艺模型输出的特征数据。
  5. 根据权利要求4所述的方法，其中，所述反馈参数算法包括移动平均算法、加权移动平均算法和指数移动平均算法之一。
  6. 根据权利要求5所述的方法，其中，所述移动平均算法包括根据以下公式来计算连续多个周期的工艺参数的平均值：
    Figure PCTCN2022116149-appb-100001
    其中C 1，C 2，...C n是每个周期的工艺参数的值，n为大于1的整数。
  7. 根据权利要求5所述的方法，其中，所述加权移动平均算法包括末日加权算法、线性加权算法、梯形加权算法和平方系数加权算法之一。
  8. 根据权利要求7所述的方法，其中，所述末日加权算法包括根据以下公式来计算连续多个周期的工艺参数的加权平均值：
    Figure PCTCN2022116149-appb-100002
    其中C 1，C 2，...C n是每个周期的工艺参数的值，n为大于1的整数。
  9. 根据权利要求7所述的方法，其中，所述线性加权算法包括根据以下公式来计算连续多个周期的工艺参数的加权平均值：
    Figure PCTCN2022116149-appb-100003
    其中C 1，C 2，...C n是每个周期的工艺参数的值，n为大于1的整数。
  10. 根据权利要求7所述的方法，其中，所述梯形加权算法包括根据以下公式来计算连续多个周期的工艺参数的加权平均值：
    Figure PCTCN2022116149-appb-100004
    其中C 1，C 2，...C n是每个周期的工艺参数的值，n为大于1的整数。
  11. 根据权利要求7所述的方法，其中，所述平方系数加权算法包括根据以下公式来计算连续多个周期的工艺参数的加权平均值：
    Figure PCTCN2022116149-appb-100005
    其中C 1，C 2，...C n是每个周期的工艺参数的值，n为大于1的整数。
  12. 根据权利要求5所述的方法，其中，所述指数移动平均算法包括根据以下公式来计算连续多个周期的工艺参数的加权平均值：
    Figure PCTCN2022116149-appb-100006
    其中C 1，C 2，...C n是每个周期的工艺参数的值，n为大于1的整数，α为加权指数。
  13. 根据权利要求1至12中任一项所述的方法，其中，所述显示面板的任一工艺过程包括背板制造工艺。
  14. 根据权利要求13所述的方法，其中，所述显示面板的任一工艺过程包括背板制造工艺中用于形成膜层的光刻工艺，所述设计数据包括掩模板的设计图，所述基于显示面板的任一工艺过程的设计数据来生成用于执行所述工艺过程的仿真工艺数据包括以下操作中的至少之一：
    对掩膜板的设计图的至少部分区域进行仿真，得到测试图；
    根据接收到的曝光参数设定信息来生成曝光工艺参数；
    根据接收到的抗蚀剂参数设定信息来生成抗蚀剂工艺参数；以及
    根据接收到的显影参数设定信息来生成显影工艺参数。
  15. 根据权利要求14所述的方法，其中，所述曝光工艺参数包括以下各项中的至少之一：数值孔径、波长、相干因子、照明类型、曝光倍率和焦点位置。
  16. 根据权利要求14所述的方法，其中，所述抗蚀剂工艺参数包括以下各项中的至少之一：光致抗蚀剂的类型、光致抗蚀剂的厚度和显影速率、基底材料和光敏化合物PAC浓度分布。
  17. 根据权利要求14所述的方法，所述基于显示面板的任一工艺过程的设计数据来生成用于执行所述工艺过程的仿真工艺数据还包括以下至少之一：
    基于曝光工艺参数对所述测试图进行透镜投影仿真，得到空间像数据；以及
    基于显影参数来生成显影后的所述膜层的图形数据。
  18. 根据权利要求17所述的方法，还包括：通过用户交互界面来展示所述空间像数据和所述图形数据中的至少之一并接收用户输入，以及根据用户输入来调整所述曝光工艺参数、抗蚀剂工艺参数和显影工艺参数中的至少之一。
  19. 根据权利要求1至18中任一项所述的方法，其中，所述实际测量数据包括在所述任一工艺过程开始之前测量得到的数据以及在所述任一工艺过程开始之后测量得到的数据。
  20. 根据权利要求1至19中任一项所述的方法，还包括：更新实际工艺数据和实际测量数据；以及根据更新的实际工艺数据和实际测量数据来更新所述工艺模型和测量模型。
  21. 根据权利要求1至22中任一项所述的方法，还包括：响应于验证了所述仿真工艺数据可用于实际生产，将所述仿真工艺数据应用于所述显示面板的实际制造过程。
  22. 根据权利要求1至21中任一项所述的方法，还包括：将经验证可用于实际生产的仿真工艺数据形成为制造工艺文件。
  23. 一种电子设备，包括存储器和处理器，所述存储器存储有可被所述处理器执行的指令，所述指令被所述处理器执行，以使所述处理器能够执行权利要求1至22中任一项所述的方法。
  24. 一种存储有计算机指令的非瞬时计算机可读存储介质，其中，所述计算机指令用于使所述计算机执行根据权利要求1至22中任一项所述的方法。
  25. 一种计算机程序产品，包括计算机程序，所述计算机程序在被处理器执行时实现根据权利要求1至22中任一项所述的方法。
  26. 一种显示面板的生产方法，包括物理制造过程和数字处理过程，其中，
    在所述物理制造过程中执行显示面板的至少一个工艺过程，得到实际工艺数据和实际测量数据；
    在所述数字处理过程中，使用基于所述实际工艺数据和实际测量数据而生成的工艺模型和测量模型来执行如权利要求1至22中任一项所述的方法，以验证仿真工艺数据是否可用于实际生产。
  27. 根据权利要求26所述的方法，其中，在所述物理制造过程中执行显示面板的至少一个工艺过程包括：依次执行前测量操作、准备操作、载入工艺数据操作、工艺加工操作和后测量操作，其中在所述载入工艺数据操作中载入了所述实际工艺数据，所述前测量操作、所述工艺加工操作和所述后侧量操作中的至少之一产生了所述实际测量数据。
  28. 根据权利要求26或27所述的方法，还包括：响应于经验证所述仿真工艺数据可用于实际生产，将所述仿真数据作为实际工艺数据应用于所述物理制造过程中的载入工艺数据操作。
  29. 根据权利要求26至28中任一项所述的方法，还包括：再次执行所述物理制造过程，以产生新的实际工艺数据和新的实际测量数据；以及
    基于新的实际工艺数据和新的实际测量数据来更新所述工艺模型和测量模型。
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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5621652A (en) * 1995-03-21 1997-04-15 Vlsi Technology, Inc. System and method for verifying process models in integrated circuit process simulators
JP2010122438A (ja) * 2008-11-19 2010-06-03 Nec Electronics Corp リソグラフィシミュレーションモデルの検証方法、検証プログラム及び検証装置
US20160224701A1 (en) * 2015-02-04 2016-08-04 Samsung Electronics Co., Ltd. Design validation system
CN109491216A (zh) * 2018-12-20 2019-03-19 上海集成电路研发中心有限公司 一种优化光刻工艺参数的方法
CN112685993A (zh) * 2021-03-17 2021-04-20 武汉大学 一种柔性pcb板湿法化学蚀刻工艺仿真方法

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5621652A (en) * 1995-03-21 1997-04-15 Vlsi Technology, Inc. System and method for verifying process models in integrated circuit process simulators
JP2010122438A (ja) * 2008-11-19 2010-06-03 Nec Electronics Corp リソグラフィシミュレーションモデルの検証方法、検証プログラム及び検証装置
US20160224701A1 (en) * 2015-02-04 2016-08-04 Samsung Electronics Co., Ltd. Design validation system
CN109491216A (zh) * 2018-12-20 2019-03-19 上海集成电路研发中心有限公司 一种优化光刻工艺参数的方法
CN112685993A (zh) * 2021-03-17 2021-04-20 武汉大学 一种柔性pcb板湿法化学蚀刻工艺仿真方法

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