Optical proximity effect correction method and system considering grid dependence

Abstract

The invention belongs to the technical field of photoetching, and particularly relates to an optical proximity effect correction method and system considering grid dependence. Through the first correction rule base in the OPC standard configuration base, position iteration correction is carried out on the first to-be-corrected mask pattern in the to-be-corrected layout file, preliminary OPC of the first to-be-corrected mask pattern is achieved, and the OPC efficiency of the to-be-corrected mask pattern is improved under the condition that the GD error influence is considered subsequently; through a second correction rule base obtained through optimization of the first correction mask pattern, moving a second to-be-corrected mask pattern for multiple times according to the target mask pattern moving mode, and calculating light intensity distribution of the second to-be-corrected mask pattern after each time of movement, therefore, the mask movement amount of the second to-be-corrected mask pattern can be obtained by using the average light intensity distribution of the second to-be-corrected mask pattern, and the influence of GD on the OPC process of the second to-be-corrected mask pattern can be effectively reduced.

Description

Technical Field

[0001] This application belongs to the field of photolithography technology, and more specifically, relates to a method and system for correcting optical proximity effect considering grid dependence. Background Technology

[0002] Optical proximity correction (OPC) is a crucial technology supporting the continuous miniaturization of photolithography nodes. It plays an extremely important role in ensuring that the silicon wafer achieves ideal imaging quality and thus guarantees yield. The current approach is to use a photoresist effect simulation model to simulate the imaging of the mask pattern, calculate the imaging pattern contour of the mask pattern on the photoresist, and then calculate the mask pattern corresponding to the required imaging pattern contour through multiple iterations. Finally, the optimal imaging pattern contour is exposed on the silicon wafer using the chemical reaction of the photoresist.

[0003] As the miniaturization precision of photolithography technology increases, the size of the simulated patterns to be lithographically applied to the photoresist is further reduced, and the density of the simulated patterns is also continuously increasing. However, factors such as grid dependency (GD) are beginning to significantly impact the imaging simulation process of mask patterns. For example, when the computational grid size of the photoresist effect simulation model is less than 14nm (the diffraction limit of the mask pattern), the computational grid size of the coordinate grid corresponding to the mask pattern affects the mapping size between the mask pattern and the simulated imaging pattern. Therefore, GD errors amplify the fluctuation range of the mapping size of the mask pattern at different locations, thus affecting the accuracy of the optical proximity effect correction of the mask pattern. Summary of the Invention

[0004] To address the aforementioned deficiencies in existing technologies, this application provides an optical proximity effect correction method and system that considers grid dependence, aiming to reduce the impact of GD error on the OPC correction results of mask patterns and improve the simulation imaging accuracy of mask patterns on photoresist.

[0005] In a first aspect, this application provides a method for correcting optical proximity effects that considers grid dependence, including: S1. Obtain the first correction rule library in the OPC standard configuration library, and based on the first correction rule library, perform position iterative correction on the first mask graphic to be corrected in the layout file to be corrected until the simulation imaging graphic corresponding to the first mask graphic to be corrected reaches the convergence state, and obtain the second mask graphic to be corrected corresponding to the first mask graphic to be corrected. S2. Based on the preset number of target correction iterations and the target mask image movement method, update the parameters of the first correction rule base to obtain the second correction rule base; S3. Based on the second correction rule base, the second mask image to be corrected is moved multiple times according to the movement mode of the target mask image, and the light intensity distribution of the second mask image to be corrected after each movement is calculated. S4. Based on the light intensity distribution of the second mask image to be corrected after each movement, the position of the second mask image to be corrected is corrected. Step S3 is repeated until the simulated imaging image corresponding to the second mask image to be corrected reaches the convergence state.

[0006] The first correction rule base includes a photoresist projection model, an initial correction iteration number, a preset allowable range for contour error, and the movement mode of the target simulation imaging graphic and the initial mask graphic. The photoresist projection model is used to reflect the simulation mapping relationship between the first mask graphic to be corrected and the corresponding simulation imaging graphic. The simulation mapping relationship includes the calculated grid size used to reflect the mapping size between the first mask graphic to be corrected and the simulation imaging graphic.

[0007] Furthermore, the first mask pattern to be corrected in the layout file is iteratively corrected until the simulated imaging pattern corresponding to the first mask pattern to be corrected reaches a convergence state, including: S11. Based on the photoresist projection model, obtain the simulation imaging pattern corresponding to the first mask pattern to be corrected; S12. Obtain the graphic contour error value between the simulated imaging graphic and the target simulated imaging graphic, and correct the first mask graphic to be corrected based on the graphic contour error value and the initial mask graphic movement method. S13. Repeat step S12 until the contour error value of the simulated image is less than the maximum value of the preset contour error allowable range, or the number of iterations in step S12 reaches the initial correction iteration number.

[0008] Furthermore, based on the preset number of target correction iterations and the target mask image movement method, the parameters of the first correction rule base are updated, including: The initial mask pattern movement method in the first correction rule base is replaced with the target mask pattern movement method, and the initial correction iteration number is replaced with the target correction iteration number to obtain the second correction rule base.

[0009] Furthermore, based on the light intensity distribution of the second mask pattern to be corrected after each movement, the position of the second mask pattern to be corrected is corrected, including: S41. Based on the light intensity distribution of the second mask image to be corrected after each movement, obtain the average light intensity distribution of the second mask image to be corrected, and obtain the imaging contour of the simulated imaging image of the second mask image to be corrected based on the average light intensity distribution. S42. Based on the graphic contour error value of the imaging contour between the simulated imaging graphic of the second mask graphic to be corrected and the target simulated imaging graphic, obtain the mask movement amount of the second mask graphic to be corrected, and perform position correction on the second mask graphic to be corrected based on the mask movement amount and the movement mode of the target mask graphic. S43. Repeat step S41 until the contour error value of the simulated image is less than the maximum value of the preset contour error allowable range, or the number of iterations in step S41 reaches the target correction iteration number.

[0010] Furthermore, after the simulated imaging pattern corresponding to the second mask pattern to be corrected reaches the convergence state, it also includes: Obtain the simulated imaging image corresponding to the second mask image to be corrected in each iteration correction process, and calculate the image contour error value between the simulated imaging image and the target simulated imaging image to obtain the set of image contour error values. Based on the preset allowable range of contour error in the second correction rule base, the simulation defect type of the graphic contour error value set is determined. The simulation defect types include GD-dominated, OPC-dominated, and GD and OPC-dominated in tandem. When the simulation defect type is characterized as GD-dominant or GD and OPC co-dominant, the calculation grid size of the photoresist projection model in the second correction rule base is adjusted, and the second mask pattern to be corrected is iteratively corrected based on the second rule base adjusted by the photoresist projection model until the simulation imaging pattern corresponding to the second mask pattern to be corrected reaches the convergence state.

[0011] Furthermore, based on the preset allowable range of contour error in the second correction rule base, the simulation defect type of the graphic contour error value set is determined, including: Obtain the maximum and minimum graphic contour error values ​​in the graphic contour error value set, and determine the simulation defect type of the graphic contour error value set based on the positional relationship between the maximum and minimum graphic contour error values ​​and the preset allowable contour error range. When both the maximum and minimum graphic contour error values ​​exceed the preset allowable range of contour error, the simulation defect type is characterized as GD-dominant. When neither the maximum nor the minimum graphic contour error value exceeds the preset allowable range of contour error, the simulation defect type is characterized as GD and OPC being jointly dominated. When either the maximum or minimum graphic contour error value exceeds the preset allowable contour error range, the simulation defect type is characterized as OPC-dominated.

[0012] Secondly, this application also provides an optical proximity effect correction system that considers grid dependence, for implementing any of the methods in the first aspect, including: The first correction module is used to perform position iterative correction on the first mask graphic to be corrected in the layout file to be corrected based on the first correction rule base, until the simulation imaging graphic corresponding to the first mask graphic to be corrected reaches the convergence state, and obtain the second mask graphic to be corrected corresponding to the first mask graphic to be corrected. The rule base update module is used to update the parameters of the first correction rule base based on the preset number of target correction iterations and the target mask graphic movement method to obtain the second correction rule base. The light intensity distribution acquisition module is used to move the second mask image to be corrected multiple times according to the movement mode of the target mask image based on the second correction rule base, and calculate the light intensity distribution of the second mask image to be corrected after each movement. The second correction module is used to perform position iterative correction on the second mask image to be corrected based on the light intensity distribution after each movement, until the simulated imaging image corresponding to the second mask image to be corrected reaches the convergence state.

[0013] Thirdly, this application also provides an electronic device, characterized in that it comprises: At least one memory for storing computer programs; At least one processor is configured to execute a program stored in the memory, such that, when the program is executed, the processor performs the method described in the first aspect or any possible implementation thereof.

[0014] Fourthly, this application also provides a computer-readable storage medium storing a computer program that, when run on a processor, causes the processor to perform the method described in the first aspect or any possible implementation thereof.

[0015] In summary, the technical solutions conceived by this invention have the following beneficial effects compared with the prior art: 1. By using the first correction rule library in the OPC standard configuration library, the position of the first mask graphic to be corrected in the layout file to be corrected is iteratively corrected, so as to realize the initial OPC of the first mask graphic to be corrected and improve the OPC efficiency of the mask graphic to be corrected when considering the influence of GD error. 2. By using the second correction rule library obtained by optimizing the first correction mask pattern, the second mask pattern to be corrected is moved multiple times according to the movement mode of the target mask pattern, and the light intensity distribution of the second mask pattern to be corrected after each movement is calculated. Then, the average light intensity distribution of the second mask pattern to be corrected can be used to obtain the mask movement amount of the second mask pattern to be corrected, which can effectively reduce the influence of GD on the OPC process of the second mask pattern to be corrected. 3. By obtaining the graphic contour error value between the simulated imaging graphic and the target simulated imaging graphic in each iteration of the second mask graphic to be corrected, a set of graphic contour error values ​​is constructed. Then, when the simulation defect type of the graphic contour error value set is GD-dominated or GD and OPC co-dominated, the calculation grid size of the photoresist projection model in the second correction rule base is adjusted, thereby reducing the influence of GD on the OPC correction result of the second mask graphic to be corrected and improving the simulation imaging accuracy of the mask graphic on the photoresist. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in this application or related technologies, the accompanying drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic flowchart of an optical proximity effect correction method provided in an embodiment of this application.

[0018] Figure 2 This is a schematic diagram of the correction process for the second mask pattern to be corrected provided in the embodiments of this application.

[0019] Figure 3 This is a schematic diagram of the optical proximity effect correction system provided in the embodiments of this application.

[0020] Figure 4 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0021] The technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings.

[0022] In the following description, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance. The following description provides multiple embodiments of this application, which can be substituted or combined with each other. Therefore, this application can also be considered to include all possible combinations of the same and / or different embodiments described. Thus, if one embodiment includes features A, B, and C, and another embodiment includes features B and D, then this application should also be considered to include embodiments containing one or more other possible combinations of A, B, C, and D, even if such embodiments are not explicitly described in the following text.

[0023] The following description provides examples and does not limit the scope, applicability, or examples set forth in the claims. Changes may be made to the function and arrangement of the described elements without departing from the scope of this application. Various processes or components may be appropriately omitted, substituted, or added to the examples. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Furthermore, features described with respect to some examples may be combined into other examples.

[0024] Figure 1 This is a flowchart illustrating the optical proximity effect correction method considering grid dependence provided in the embodiments of this application, as shown below. Figure 1 As shown, the method includes at least the following steps: S1. Obtain the first correction rule library in the OPC standard configuration library, and based on the first correction rule library, perform position iterative correction on the first mask graphic to be corrected in the layout file to be corrected until the simulation imaging graphic corresponding to the first mask graphic to be corrected reaches the convergence state, and obtain the second mask graphic to be corrected corresponding to the first mask graphic to be corrected.

[0025] In this embodiment, the execution entity of the optical proximity effect correction method considering grid dependence is the central controller of the lithography apparatus. The first correction rule base includes a photoresist projection model, initial correction iteration count, preset allowable contour error range, and the movement mode of the target simulated imaging pattern and the initial mask pattern. The photoresist projection model reflects the simulation mapping relationship between the first mask pattern to be corrected and the corresponding simulated imaging pattern. The simulation mapping relationship includes the calculated grid size reflecting the mapping dimension between the first mask pattern to be corrected and the simulated imaging pattern. The OPC standard configuration library is a database used to store layout files to be corrected. It can store various OPC correction rule bases and various mask patterns used for lithography. The data in the OPC correction rule base can also be modified in real time to meet different lithography task requirements.

[0026] In one possible implementation, the first mask pattern to be corrected in the layout file to be corrected is iteratively corrected until the simulated imaging pattern corresponding to the first mask pattern to be corrected reaches a convergence state, including: S11. Based on the photoresist projection model, obtain the simulation imaging pattern corresponding to the first mask pattern to be corrected; S12. Obtain the graphic contour error value between the simulated imaging graphic and the target simulated imaging graphic, and correct the first mask graphic to be corrected based on the graphic contour error value and the initial mask graphic movement method. S13. Repeat step S12 until the contour error value of the simulated image is less than the maximum value of the preset contour error allowable range, or the number of iterations in step S12 reaches the initial correction iteration number.

[0027] In this embodiment of the application, the process of using the first correction rule base to perform position iteration correction on the first mask pattern to be corrected is a conventional OPC process. The purpose is to perform preliminary correction on the first mask pattern to be corrected. Since the computational amount of a single correction in the subsequent OPC process that considers the influence of GD is large, the above operation can save a lot of computing power for the subsequent correction process.

[0028] S2. Based on the preset number of target correction iterations and the target mask graphic movement method, update the parameters of the first correction rule base to obtain the second correction rule base.

[0029] In one possible implementation, the first correction rule base is updated with parameters based on a preset number of target correction iterations and a target mask image movement method, including: The initial mask pattern movement method in the first correction rule base is replaced with the target mask pattern movement method, and the initial correction iteration number is replaced with the target correction iteration number to obtain the second correction rule base.

[0030] In this embodiment of the application, the purpose of setting the second correction rule base is to incorporate the edge contour fluctuation of the mask pattern to be corrected caused by GD in the photoresist projection model as an influencing factor into the OPC process, and the target mask pattern movement method includes a preset step size and a preset position direction in the mask coordinate plane, thereby preparing for subsequent steps.

[0031] S3. Based on the second correction rule base, the second mask image to be corrected is moved multiple times according to the movement mode of the target mask image, and the light intensity distribution of the second mask image to be corrected after each movement is calculated. In the embodiments of this application, such as Figure 2 As shown in the figure, the gray area represents the imaging outline of the target simulated imaging pattern, while the red outline represents the imaging outline of the simulated imaging pattern corresponding to the second mask pattern to be corrected. The evaluation grid points in the figure are used to calculate the positional deviation between the target simulated imaging pattern and the simulated imaging pattern. The evaluation grid points are calculation grid points. The size of each calculation grid point is used to reflect the mapping size between the mask pattern and the simulated imaging pattern. That is, the smaller the size, the smaller the simulated imaging area projected by the mask pattern.

[0032] The target mask pattern movement method includes a preset step size and a preset position direction in the mask coordinate plane. For example, in this embodiment, fourteen movement coordinates (0,0), (1,1)...(13,13) are set. Then, the second mask pattern to be corrected is moved along the movement direction and movement distance of adjacent points, and the light intensity distribution of the second mask pattern to be corrected after each movement is calculated. The light intensity distribution formula is as follows:

[0033]

[0034] in, TCC It is a cross-transfer function. S It is the distribution function of the light source on the second mask pattern to be corrected. H This represents the modulation function of the lens. M It is the spectral function of the mask. (f,g) Represents the normalized coordinates of the mask coordinate plane. (x,y) Represents the coordinates of the simulated imaging plane.

[0035] S4. Based on the light intensity distribution of the second mask image to be corrected after each movement, the position of the second mask image to be corrected is corrected. Step S3 is repeated until the simulated imaging image corresponding to the second mask image to be corrected reaches the convergence state.

[0036] In one possible implementation, the position of the second mask pattern to be corrected is corrected based on the light intensity distribution after each movement, including: S41. Based on the light intensity distribution of the second mask image to be corrected after each movement, obtain the average light intensity distribution of the second mask image to be corrected, and obtain the imaging contour of the simulated imaging image of the second mask image to be corrected based on the average light intensity distribution. S42. Based on the graphic contour error value of the imaging contour between the simulated imaging graphic of the second mask graphic to be corrected and the target simulated imaging graphic, obtain the mask movement amount of the second mask graphic to be corrected, and perform position correction on the second mask graphic to be corrected based on the mask movement amount and the movement mode of the target mask graphic. S43. Repeat step S41 until the contour error value of the simulated image is less than the maximum value of the preset contour error allowable range, or the number of iterations in step S41 reaches the target correction iteration number.

[0037] In this embodiment of the application, since GD will cause certain positional fluctuations in some contour areas of the simulated imaging pattern, by using the average light intensity distribution after each movement as the average light intensity distribution of the second mask pattern to be corrected, the impact of these fluctuations on the imaging accuracy of the simulated imaging pattern can be effectively reduced, thereby improving the correction accuracy of the second mask pattern to be corrected.

[0038] In one possible implementation, after the simulated imaging pattern corresponding to the second mask pattern to be corrected reaches a convergence state, the method further includes: Obtain the simulated imaging image corresponding to the second mask image to be corrected in each iteration correction process, and calculate the image contour error value between the simulated imaging image and the target simulated imaging image to obtain the set of image contour error values. Based on the preset allowable range of contour error in the second correction rule base, the simulation defect type of the graphic contour error value set is determined. The simulation defect types include GD-dominated, OPC-dominated, and GD and OPC-dominated in tandem. When the simulation defect type is characterized as GD-dominant or GD and OPC co-dominant, the calculation grid size of the photoresist projection model in the second correction rule base is adjusted, and the second mask pattern to be corrected is iteratively corrected based on the second rule base adjusted by the photoresist projection model until the simulation imaging pattern corresponding to the second mask pattern to be corrected reaches the convergence state.

[0039] Among them, based on the preset allowable range of contour error in the second correction rule base, the simulation defect type of the graphic contour error value set is determined, including: Obtain the maximum and minimum graphic contour error values ​​in the graphic contour error value set, and determine the simulation defect type of the graphic contour error value set based on the positional relationship between the maximum and minimum graphic contour error values ​​and the preset allowable contour error range. When both the maximum and minimum graphic contour error values ​​exceed the preset allowable range of contour error, the simulation defect type is characterized as GD-dominant. When neither the maximum nor the minimum graphic contour error value exceeds the preset allowable range of contour error, the simulation defect type is characterized as GD and OPC being jointly dominated. When either the maximum or minimum graphic contour error value exceeds the preset allowable contour error range, the simulation defect type is characterized as OPC-dominated.

[0040] In this embodiment, to verify the effectiveness of the improved OPC result considering GD influence, it is necessary to evaluate the simulated imaging pattern corresponding to the second mask pattern to be corrected throughout the entire correction process, so as to further improve the simulation imaging accuracy of the mask pattern on the photoresist. The pattern contour error value reflects the deviation between the simulated imaging pattern corresponding to the second mask pattern to be corrected and the target simulated imaging pattern, which is the theoretical unbiased model used to configure it on the photoresist. When both the maximum and minimum pattern contour error values ​​exceed the preset allowable contour error range, no matter how the OPC is modified, it is difficult to make the entire simulated imaging pattern fall within the allowable range. This situation is a GD-dominated error, which can only be solved by reducing the calculation grid size of the photoresist projection model, that is, reducing the mapping size between the second mask pattern to be corrected and the simulated imaging pattern to refine the range of the OPC processing area.

[0041] Figure 3 A schematic diagram of the structure of the optical proximity effect correction system considering grid dependence provided in the embodiments of this application is shown below. Figure 3As shown, the system includes at least: The first correction module is used to perform position iterative correction on the first mask graphic to be corrected in the layout file to be corrected based on the first correction rule base, until the simulation imaging graphic corresponding to the first mask graphic to be corrected reaches the convergence state, and obtain the second mask graphic to be corrected corresponding to the first mask graphic to be corrected. The rule base update module is used to update the parameters of the first correction rule base based on the preset number of target correction iterations and the target mask graphic movement method to obtain the second correction rule base. The light intensity distribution acquisition module is used to move the second mask image to be corrected multiple times according to the movement mode of the target mask image based on the second correction rule base, and calculate the light intensity distribution of the second mask image to be corrected after each movement. The second correction module is used to perform position iterative correction on the second mask image to be corrected based on the light intensity distribution after each movement, until the simulated imaging image corresponding to the second mask image to be corrected reaches the convergence state.

[0042] like Figure 4 As shown, Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device may include: a processor 401, a communications interface 402, a memory 403, and a communication bus 404. The processor 401, communications interface 402, and memory 403 communicate with each other via the communication bus 404. The processor 401 can call software instructions in the memory 403 to execute the methods described in the above embodiments.

[0043] Furthermore, the logical instructions in the aforementioned memory 403 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application.

[0044] Based on the methods in the above embodiments, this application provides a computer-readable storage medium storing a computer program that, when run on a processor, causes the processor to execute the methods in the above embodiments.

[0045] Based on the methods in the above embodiments, this application provides a computer program product that, when run on a processor, causes the processor to execute the methods in the above embodiments.

[0046] It is understood that the processor in the embodiments of this application can be a CPU (Central Processing Unit), or other general-purpose processors, DSPs (Digital Signal Processors), ASICs (Application Specific Integrated Circuits), FPGAs (Field Programmable Gate Arrays), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. A general-purpose processor can be a microprocessor or any conventional processor.

[0047] The method steps in this application embodiment can be implemented in hardware or by a processor executing software instructions. The software instructions can consist of corresponding software modules, which can be stored in random access memory (RAM), flash memory, ROM (Read-only Memory), PROM (Programmable ROM), EPROM (Erasable PROM), EEPROM (Electrically Erasable EPROM), registers, hard disks, portable hard disks, CD-ROMs, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor, enabling the processor to read information from and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can reside in an ASIC.

[0048] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the flow or function according to the embodiments of this application is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in or transmitted through a computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line DSL) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., SSD (Solid State Disk)).

[0049] It is understood that the various numerical designations used in the embodiments of this application are merely for the convenience of description and are not intended to limit the scope of the embodiments of this application.

[0050] Those skilled in the art will readily understand that the above are merely preferred embodiments of this application and are not intended to limit this application. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for correcting optical proximity effects considering grid dependence, characterized in that, include: S1. Obtain the first correction rule library in the OPC standard configuration library, and based on the first correction rule library, perform position iterative correction on the first mask graphic to be corrected in the layout file to be corrected until the simulation imaging graphic corresponding to the first mask graphic to be corrected reaches the convergence state, and obtain the second mask graphic to be corrected corresponding to the first mask graphic to be corrected. S2. Based on the preset number of target correction iterations and the target mask image movement method, update the parameters of the first correction rule base to obtain the second correction rule base; S3. Based on the second correction rule base, the second mask image to be corrected is moved multiple times according to the movement mode of the target mask image, and the light intensity distribution of the second mask image to be corrected after each movement is calculated. S4. Based on the light intensity distribution of the second mask image to be corrected after each movement, the position of the second mask image to be corrected is corrected, and step S3 is repeated until the simulated imaging image corresponding to the second mask image to be corrected reaches the convergence state.

2. The optical proximity effect correction method according to claim 1, characterized in that, The first correction rule base includes a photoresist projection model, an initial correction iteration number, a preset allowable range for contour error, and a movement method between the target simulated imaging graphic and the initial mask graphic. The photoresist projection model is used to reflect the simulation mapping relationship between the first mask graphic to be corrected and the corresponding simulated imaging graphic. The simulation mapping relationship includes a calculated grid size used to reflect the mapping size between the first mask graphic to be corrected and the simulated imaging graphic.

3. The optical proximity effect correction method according to claim 2, characterized in that, The iterative correction of the first mask pattern to be corrected in the layout file to be corrected until the simulated imaging pattern corresponding to the first mask pattern to be corrected reaches a convergence state includes: S11. Based on the photoresist projection model, obtain the simulation imaging pattern corresponding to the first mask pattern to be corrected; S12. Obtain the graphic contour error value between the simulated imaging graphic and the target simulated imaging graphic, and correct the first mask graphic to be corrected based on the graphic contour error value and the initial mask graphic movement method. S13. Repeat step S12 until the graphic contour error value corresponding to the simulated imaging graphic is less than the maximum value of the preset contour error allowable range, or the number of iterations in step S12 reaches the initial correction iteration number.

4. The optical proximity effect correction method according to claim 3, characterized in that, The step of updating the parameters of the first correction rule base based on the preset number of target correction iterations and the target mask image movement method includes: The initial mask pattern movement method in the first correction rule base is replaced with the target mask pattern movement method, and the initial correction iteration number is replaced with the target correction iteration number to obtain the second correction rule base.

5. The optical proximity effect correction method according to claim 4, characterized in that, Based on the light intensity distribution of the second mask pattern to be corrected after each movement, the position of the second mask pattern to be corrected is corrected, including: S41. Based on the light intensity distribution of the second mask image to be corrected after each movement, obtain the average light intensity distribution of the second mask image to be corrected, and obtain the imaging contour of the simulated imaging image of the second mask image to be corrected based on the average light intensity distribution. S42. Based on the graphic contour error value of the imaging contour between the simulated imaging graphic of the second mask graphic to be corrected and the target simulated imaging graphic, obtain the mask movement amount of the second mask graphic to be corrected, and perform position correction on the second mask graphic to be corrected based on the mask movement amount and the movement mode of the target mask graphic. S43. Repeat step S41 until the graphic contour error value corresponding to the simulated imaging graphic is less than the maximum value of the preset contour error allowable range, or the number of iterations in step S41 reaches the target correction iteration number.

6. The optical proximity effect correction method according to claim 5, characterized in that, After the simulated imaging pattern corresponding to the second mask pattern to be corrected reaches the convergence state, the process further includes: Obtain the simulated imaging image corresponding to the second mask image to be corrected in each iteration correction process, and calculate the image contour error value between the simulated imaging image and the target simulated imaging image to obtain the image contour error value set. Based on the preset allowable range of contour error in the second correction rule base, the simulation defect type of the graphic contour error value set is determined, and the simulation defect type includes GD-dominated, OPC-dominated, and GD and OPC-co-dominated. When the simulation defect type is characterized as GD-dominant or GD and OPC co-dominant, the calculation grid size of the photoresist projection model in the second correction rule base is adjusted, and the second rule base adjusted based on the photoresist projection model is used to iteratively correct the second mask pattern to be corrected until the simulation imaging pattern corresponding to the second mask pattern to be corrected reaches the convergence state.

7. The optical proximity effect correction method according to claim 6, characterized in that, The step of determining the simulation defect type of the graphic contour error value set based on the preset contour error allowable range in the second correction rule base includes: Obtain the maximum and minimum graphic contour error values ​​in the set of graphic contour error values, and determine the simulation defect type of the set of graphic contour error values ​​based on the positional relationship between the maximum and minimum graphic contour error values ​​and the preset allowable contour error range. When both the maximum and minimum graphic contour error values ​​exceed the preset allowable contour error range, the simulation defect type is characterized as GD-dominated. When neither the maximum nor the minimum graphic contour error value exceeds the preset allowable contour error range, the simulation defect type is characterized as being dominated by GD and OPC in tandem. When either the maximum or minimum graphic contour error value exceeds the preset allowable contour error range, the simulation defect type is characterized as OPC-dominated.

8. A grid-dependent optical proximity effect correction system for implementing the method as described in any one of claims 1-7, characterized in that, include: The first correction module is used to perform position iterative correction on the first mask graphic to be corrected in the layout file to be corrected based on the first correction rule base, until the simulation imaging graphic corresponding to the first mask graphic to be corrected reaches the convergence state, and obtain the second mask graphic to be corrected corresponding to the first mask graphic to be corrected. The rule base update module is used to update the parameters of the first correction rule base based on the preset number of target correction iterations and the target mask image movement method to obtain the second correction rule base. The light intensity distribution acquisition module is used to move the second mask image to be corrected multiple times according to the movement mode of the target mask image based on the second correction rule base, and calculate the light intensity distribution of the second mask image to be corrected after each movement. The second correction module is used to perform position iterative correction on the second mask image to be corrected based on the light intensity distribution after each movement, until the simulated imaging image corresponding to the second mask image to be corrected reaches the convergence state.

9. An electronic device, characterized in that, include: At least one memory for storing computer programs; At least one processor is configured to execute a program stored in the memory, wherein when the program stored in the memory is executed, the processor is configured to perform the method as described in any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, the computer-readable storage medium storing instructions that, when executed on a computer or processor, cause the computer or processor to perform the method as described in any one of claims 1-7.

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