Optical proximity effect correction method and device, storage medium and electronic equipment

Abstract

The invention discloses an optical proximity effect correction method and device, a storage medium and electronic equipment, and the method comprises the steps: obtaining a to-be-corrected mask layout; discretizing the mask boundary of the mask layout to be corrected to obtain a plurality of first boundary sections; calculating a Jacobian matrix of each first boundary section based on a Hopkinson optical transfer matrix; inputting the jacobian matrix into an offset prediction model, and predicting the offset of each first boundary section; and adjusting the position corresponding to the first boundary section according to the offset, and generating a corrected mask layout. According to the scheme, the calculation complexity of OPC can be reduced.

Description

Technical Field

[0001] Embodiments of the present application relate to the field of lithography technology, and in particular to an optical proximity effect correction method, device, storage medium and electronic device. Background Art

[0002] With the progress of integrated circuit manufacturing technology, the chip feature size is continuously reduced, and the challenges faced by the lithography system are intensifying. Due to the low-pass filtering characteristics of the lithography system, the transfer of the mask pattern on the silicon wafer is severely distorted, affecting the yield of chip manufacturing.

[0003] Optical Proximity Correction (OPC) is a method of compensating for the distortion caused by the diffraction of the optical system and process nonlinearity by modifying the mask layout. However, as the feature size decreases, traditional OPC faces problems of high computational complexity and poor convergence. Summary of the Invention

[0004] Embodiments of the present application provide an optical proximity effect correction method, device, storage medium and electronic device, which can reduce the computational complexity of OPC.

[0005] In a first aspect, embodiments of the present application provide an optical proximity effect correction method, including: Obtain a mask layout to be corrected; Discretize the mask boundary of the mask layout to be corrected to obtain a number of first boundary segments; Based on the Hopkins optical transfer matrix, calculate the Jacobian matrix of each first boundary segment; Input the Jacobian matrix into an offset prediction model to predict the offset of each first boundary segment; Adjust the position of the corresponding first boundary segment according to the offset to generate a corrected mask layout.

[0006] In the optical proximity effect correction method provided by the embodiments of the present application, the step of adjusting the position of the corresponding first boundary segment according to the offset to generate a corrected mask layout includes: Based on the offset, update the position of the corresponding first boundary segment by the Newton iteration method until the convergence condition is reached; When the convergence condition is reached, generate a corrected mask layout.

[0007] In the optical proximity effect correction method provided by the embodiments of the present application, the step of updating the position of the corresponding first boundary segment by the Newton iteration method based on the offset until the convergence condition is reached includes: Update the position of the corresponding first boundary segment according to the offset; Update the transmission spectrum of the mask layout to be corrected based on the updated first boundary segment; Calculate the current exposure error according to the Hopkins optical transfer matrix and the updated transmission spectrum; Based on the current exposure error, update the position corresponding to the first boundary segment through the Newton iteration method until the convergence condition is reached.

[0008] In the optical proximity effect correction method provided by the embodiments of the present application, the step of updating the position corresponding to the first boundary segment through the Newton iteration method based on the current exposure error until the convergence condition is reached includes: When the current exposure error is greater than the threshold, return to execute the step of calculating the Jacobian matrix of each first boundary segment based on the Hopkins optical transfer matrix; When the current exposure error is less than or equal to the threshold, it is determined that the convergence condition is reached.

[0009] In the optical proximity effect correction method provided by the embodiments of the present application, it further includes: Construct a Hopkins optical transfer matrix; Construct an offset prediction model.

[0010] In the optical proximity effect correction method provided by the embodiments of the present application, the constructing of the offset prediction model includes: Obtain a test mask layout; Discretize the mask boundary of the test mask layout to obtain a number of second boundary segments; Based on the Hopkins optical transfer matrix, calculate the Jacobian matrix and Hessian matrix of each second boundary segment; Calculate the true offset of each second boundary segment based on the Hessian matrix; Use the true offset as the training label and the Jacobian matrix as the input data to train a preset Unet network model to generate an offset prediction model.

[0011] In the optical proximity effect correction method provided by the embodiments of the present application, the constructing of the Hopkins optical transfer matrix includes: Obtain the optical parameters of the lithography system; According to the optical parameters, establish an optical imaging system using the Hopkins imaging model; Calculate the Hopkins optical transfer matrix based on the optical imaging system.

[0012] In a second aspect, an optical proximity effect correction device provided by an embodiment of the present application includes: An acquisition unit for acquiring a mask layout to be corrected; Discrete unit, used to discretize the mask boundary of the mask layout to be corrected, obtaining a number of first boundary segments; Calculation unit, used to calculate the Jacobian matrix of each of the first boundary segments based on the Hopkins optical transfer matrix; Prediction unit, used to input the Jacobian matrix into an offset prediction model to predict the offset of each of the first boundary segments; Correction unit, used to adjust the position of the corresponding first boundary segment according to the offset to generate a corrected mask layout.

[0013] In a third aspect, the present application provides a storage medium storing a number of instructions suitable for being loaded by a processor to execute the optical proximity effect correction method described in any one of the above.

[0014] In a fourth aspect, the present application provides an electronic device including a memory, a processor, and a computer program stored on the memory and executable on the processor. Wherein, when the processor executes the computer program, the optical proximity effect correction method described in any one of the above is implemented.

[0015] In summary, the optical proximity effect correction method provided by the embodiments of the present application includes obtaining a mask layout to be corrected; discretizing the mask boundary of the mask layout to be corrected to obtain a number of first boundary segments; calculating the Jacobian matrix of each of the first boundary segments based on the Hopkins optical transfer matrix; inputting the Jacobian matrix into an offset prediction model to predict the offset of each of the first boundary segments; adjusting the position of the corresponding first boundary segment according to the offset to generate a corrected mask layout. This solution combines a physical model (Hopkins optical transfer matrix) and a neural network model (offset prediction model), reducing the computational complexity of OPC while ensuring the optical imaging accuracy. Description of the Drawings

[0016] To more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative efforts.

[0017] Figure 1 is a schematic diagram of the application scenario of the optical proximity effect correction method provided by the embodiments of the present application.

[0018] Figure 2 is a schematic flowchart of the optical proximity effect correction method provided by the embodiments of the present application.

[0019] Figure 3It is a schematic structural diagram of the offset prediction model provided by an embodiment of the present application.

[0020] Figure 4 It is a schematic structural diagram of the optical proximity effect correction device provided by an embodiment of the present application.

[0021] Figure 5 It is a schematic structural diagram of the electronic device provided by an embodiment of the present application. Detailed implementation manners

[0022] Here, the exemplary embodiments will be described in detail, and the examples are shown in the drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementation manners described in the following exemplary embodiments do not represent all implementation manners consistent with the present application. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0023] It should be noted that in this document, the term "including", "comprising" or any other variant thereof is intended to cover a non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements but also includes other elements not explicitly listed, or further includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of another identical element in the process, method, article or device including the element. In addition, components, features, and elements with the same name in different embodiments of the present application may have the same meaning or different meanings, and their specific meanings need to be determined based on their explanations in the specific embodiments or further in combination with the context of the specific embodiments.

[0024] It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0025] In the subsequent description, the use of suffixes such as "module", "component" or "unit" for representing elements is only for the convenience of the description of the present application, and it has no specific meaning in itself. Therefore, "module", "component" or "unit" can be used interchangeably.

[0026] In the description of the present application, it should be noted that the orientation or positional relationship indicated by the terms "upper", "lower", "left", "right", "inner", "outer", etc. is based on the orientation or positional relationship shown in the drawings. It is only for the convenience of describing the present application and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation to the present application. In addition, terms such as "first" and "second" are only used for descriptive purposes and should not be construed as indicating or implying relative importance.

[0027] OPC is a method of compensating for the distortion caused by the diffraction of the optical system and the process nonlinearity by modifying the mask layout. However, as the feature size decreases, traditional OPC faces problems of high computational complexity and poor convergence.

[0028] Based on this, the embodiments of the present application provide an optical proximity effect correction method, device, storage medium, and electronic device. Specifically, the optical proximity effect correction device can be integrated in an electronic device, and the electronic device can be a server or a terminal device, etc.; among them, the terminal can include a mobile phone, a wearable smart device, a tablet computer, a laptop computer, and a personal computer (PC), etc.; the server can be a single server or a server cluster composed of multiple servers, and can be a physical server or a virtual server.

[0029] For example, as Figure 1 shown, the electronic device can obtain the mask layout to be corrected; discretize the mask boundary of the mask layout to be corrected to obtain a number of first boundary segments; calculate the Jacobian matrix of each first boundary segment based on the Hopkins optical transfer matrix; input the Jacobian matrix into the offset prediction model to predict the offset of each first boundary segment; adjust the position of the corresponding first boundary segment according to the offset to generate the corrected mask layout.

[0030] The technical solutions shown in the present application will be described in detail below through specific embodiments. It should be noted that the description order of the following embodiments does not limit the priority order of the embodiments.

[0031] Please refer to Figure 2 , Figure 2 which is a schematic flow chart of the optical proximity effect correction method provided by the embodiments of the present application. The specific process of the optical proximity effect correction method can be as follows: 101. Obtain the mask layout to be corrected.

[0032] layout Figure 1Generally created by chip design software (such as Cadence, Mentor Graphics, Synopsys, etc.). In the semiconductor manufacturing industry, to ensure the standardization and compatibility of design data, specific file format standards, such as GDS (Graphic Data System) or OASIS (Open Artwork System Interchange Standard), are usually adopted to save these layout diagrams.

[0033] In this embodiment, the mask layout to be corrected refers to the mask layout where the current exposure error is greater than the threshold.

[0034] In some embodiments, the mask layout to be processed can be obtained first, and then Fourier transform is performed on the mask layout to be processed to obtain its transmission spectrum, that is, the spectral domain distribution of the mask transmission coefficient. Then, according to the Hopkins optical transfer matrix and this transmission spectrum, the current exposure intensity of the mask layout to be processed is calculated. Finally, the current exposure intensity is compared with the target exposure intensity to obtain the current exposure error. When the current exposure error is greater than the threshold, it can be confirmed that the mask layout to be processed is the mask layout to be corrected and needs to perform OPC. When the current exposure error is less than or equal to the threshold, it can be confirmed that the mask layout to be processed does not need to perform OPC.

[0035] It should be noted that the Hopkins optical transfer matrix is constructed in advance, and the specific construction process will be described in detail in subsequent embodiments and will not be elaborated here one by one.

[0036] The target exposure intensity can be set according to the actual situation, and the embodiments of the present application do not limit it.

[0037] 102. Discretize the mask boundary of the mask layout to be corrected to obtain a number of first boundary segments.

[0038] In some embodiments, the mask boundary of the mask layout to be corrected can be divided into a grid according to a preset pixel, so as to obtain a number of discretized first boundary segments.

[0039] 103. Calculate the Jacobian matrix of each first boundary segment based on the Hopkins optical transfer matrix.

[0040] It can be understood that the Jacobian matrix can reflect the local influence of the position change of the corresponding boundary segment on the light intensity distribution.

[0041] The Hopkins optical transfer matrix is constructed in advance. The specific construction process can be to obtain the optical parameters of the lithography system; based on the optical parameters, establish an optical imaging system using the Hopkins imaging model; and calculate the Hopkins optical transfer matrix based on the optical imaging system.

[0042] Among them, the optical parameters can include the exposure wavelength, numerical aperture (NA), light source distribution, and polarization state.

[0043] Specifically, the optical parameters of the lithography system can be obtained first. Then, based on these optical parameters, establish a pupil function to define the transmission characteristics of the lens system for different spatial frequencies, and calculate the light source cross-correlation function to describe the correlation degree between different spectra. Finally, through the convolution relationship combined with the mask transmission spectrum, establish a complete optical imaging system to predict the exposure intensity of the mask layout to be corrected on the silicon wafer.

[0044] In some embodiments, the exposure intensity can be expressed as: (1).

[0045] In Equation (1), is the exposure intensity; is the imaging position; is the optical cross-transfer function; is the spatial sampling frequency; is the transmission spectrum of the mask.

[0046] Among them, . In this equation, is the light source cross-correlation function, is the pupil function.

[0047] For the optical imaging system, After expansion, it can be expressed as: (2).

[0048] In Equation (2), is the imaging kernel (Hopkins optical transfer matrix) of the optical imaging system, is the weight corresponding to the th kernel. is the total number of equivalent convolution kernels.

[0049] At this time, the current exposure intensity of the mask to be corrected can be expressed as: (3).

[0050] It can be understood that Equations (1)-(3) are the mathematical expressions of the construction process of the Hopkins optical transfer matrix.

[0051] OPC is to correct the offset of each boundary segment so that the cost function (exposure error) is minimized: (4) where I(x, y, M) is the current exposure intensity of the mask layout to be corrected, and T(x, y) is the target exposure intensity.

[0052] The matrix form of several boundary segments of the mask layout M(f, g) to be corrected can be expressed as follows: (5).

[0053] In equation (5), represents the two-dimensional Fourier transform of the matrix element.

[0054] The Newton iteration method can be expressed as: (6).

[0055] In equation (6), represents the correlation matrix of all boundary segments; is the number of iterations; is the Jacobian matrix, is the Hessian matrix, and the superscript represents matrix inversion.

[0056] Among them, (7).

[0057] (8).

[0058] In equations (7) and (8), represents the position of the spatial pixel point , , ([[]] represents the pixel point position numbers in the x and y directions, represents the number of pixel points in the x direction); represents the spatial edge position, ( respectively represent the spatial numbers corresponding to the edge).

[0059] It can be understood that substituting equations (7) and (8) into equation (6) can realize the iterative update of the boundary segment position and achieve the OPC of the mask layout to be corrected.

[0060] 104. Input the Jacobian matrix into the offset prediction model to predict the offset of each first boundary segment.

[0061] It can be understood that the traditional Newton method needs to calculate the inverse matrix of the Hessian matrix. However, the Hessian matrix is a second-order partial derivative, and the calculation complexity is relatively high, which limits the application of the Newton method.

[0062] Based on this, in the embodiment of the present application, the Jacobian matrix with a relatively small computational complexity is used as the input, and the true offset corresponding to the Hessian matrix is used as the training label to train the preset Unet network model, so as to obtain an offset prediction model that can predict the true offset corresponding to the Hessian matrix.

[0063] Specifically, the construction process of the offset prediction model can be as follows: obtain a test mask layout; discretize the mask boundary of the test mask layout to obtain a number of second boundary segments; calculate the Jacobian matrix and Hessian matrix of each second boundary segment based on the Hopkins optical transfer matrix; calculate the true offset of each second boundary segment based on the Hessian matrix; use the true offset as the training label and the Jacobian matrix input data to train the preset Unet network model to generate an offset prediction model.

[0064] Wherein, the size of the second boundary segment is the same as that of the first boundary segment.

[0065] Wherein, the preset Unet network model can be as Figure 3 shown, and is divided into three downsampling layers in total, which are implemented by a Convolutional Neural Network (CNN); three upsampling layers (implemented by CNN), and each layer is corrected by a fully connected network including a sigmod activation function. The sigmod activation function is: .

[0066] It can be understood that after the training is completed, the Jacobian matrix of each first boundary segment is input into the offset prediction model, and the offset of each first boundary segment can be predicted.

[0067] 105. Adjust the position of the corresponding first boundary segment according to the offset to generate a corrected mask layout.

[0068] Specifically, based on the offset, the position of the corresponding first boundary segment can be updated by the Newton iteration method until the convergence condition is reached; when the convergence condition is reached, a corrected mask layout is generated.

[0069] Wherein, the convergence condition refers to that the cost function is less than or equal to the threshold; or the number of iterations reaches the maximum number of iterations.

[0070] Wherein, the step of "updating the position of the corresponding first boundary segment by the Newton iteration method based on the offset until the convergence condition is reached" can specifically be: Update the position of the corresponding first boundary segment according to the offset; Based on the updated first boundary segment, update the transmission spectrum of the mask layout to be corrected; Calculate the current exposure error according to the Hopkins optical transfer matrix and the updated transmission spectrum; Based on the current exposure error, update the position of the corresponding first boundary segment by the Newton iteration method until the convergence condition is reached.

[0071] Among them, the specific calculation process of the current exposure error can refer to step 101 and will not be elaborated here one by one.

[0072] It can be understood that when the current exposure error is greater than the threshold, return to execute the step of calculating the Jacobian matrix of each first boundary segment based on the Hopkins optical transfer matrix; when the current exposure error is less than or equal to the threshold, it is determined that the convergence condition is reached.

[0073] In summary, the optical proximity effect correction method provided by the embodiments of the present application includes obtaining a mask layout to be corrected; discretizing the mask boundary of the mask layout to be corrected to obtain a number of first boundary segments; calculating the Jacobian matrix of each first boundary segment based on the Hopkins optical transfer matrix; inputting the Jacobian matrix into an offset prediction model to predict the offset of each first boundary segment; adjusting the position of the corresponding first boundary segment according to the offset to generate a corrected mask layout. Traditional OPC relies on the Newton iteration method to calculate the Hessian matrix, and its complexity grows exponentially with the number of boundary segments. This solution directly predicts the offset corresponding to the Hessian matrix through an offset prediction model, which can reduce the computational complexity. That is, this solution combines a physical model (Hopkins optical transfer matrix) and a neural network model (offset prediction model) to break through the computational bottleneck of traditional OPC and reduce the computational complexity of OPC while ensuring the optical imaging accuracy.

[0074] To facilitate better implementation of the optical proximity effect correction method provided by the embodiments of the present application, the embodiments of the present application also provide an optical proximity effect correction device. The meanings of the terms are the same as those in the above optical proximity effect correction method, and the specific implementation details can refer to the description in the method embodiments.

[0075] Please refer to Figure 4 , Figure 4 which is a schematic structural diagram of the optical proximity effect correction device provided by the embodiments of the present application. The optical proximity effect correction device may include an acquisition unit 201, a discretization unit 202, a calculation unit 203, a prediction unit 204, and a correction unit 205. Among them, The acquisition unit 201 is used to acquire a mask layout to be corrected; The discretization unit 202 is used to discretize the mask boundary of the mask layout to be corrected to obtain a number of first boundary segments; The calculation unit 203 is used to calculate the Jacobian matrix of each first boundary segment based on the Hopkins optical transfer matrix; A prediction unit 204, configured to input the Jacobian matrix into an offset prediction model to predict the offset of each first boundary segment; A correction unit 201, configured to adjust the position of the corresponding first boundary segment according to the offset to generate a corrected mask layout.

[0076] For the specific implementation manners of the above units, reference may be made to the embodiments of the above optical proximity effect correction method, which will not be elaborated herein one by one.

[0077] In summary, the optical proximity effect correction device provided by the embodiment of the present application can obtain the mask layout to be corrected through the acquisition unit 201; the discretization unit 202 discretizes the mask boundary of the mask layout to be corrected to obtain a plurality of first boundary segments; the calculation unit 203 calculates the Jacobian matrix of each first boundary segment based on the Hopkins optical transfer matrix; the prediction unit 204 inputs the Jacobian matrix into the offset prediction model to predict the offset of each first boundary segment; the correction unit 201 adjusts the position of the corresponding first boundary segment according to the offset to generate a corrected mask layout. This solution combines a physical model (Hopkins optical transfer matrix) and a neural network model (offset prediction model), while ensuring the optical imaging accuracy, breaks through the calculation bottleneck of traditional OPC, and reduces the calculation complexity of OPC.

[0078] The embodiment of the present application further provides an electronic device, which may integrate the optical proximity effect correction device of the embodiment of the present application. As Figure 5 shown, it shows a schematic structural diagram of the electronic device involved in the embodiment of the present application. Specifically: The electronic device may include components such as a processor 301 with one or more processing cores and a memory 302 with one or more computer-readable storage media. Those skilled in the art can understand that Figure 5 the structural diagram of the electronic device shown in does not constitute a limitation on the electronic device, and it may include more or fewer components than shown, or combine certain components, or have different component arrangements. Among them: The processor 301 is the control center of the electronic device, connecting various parts of the entire electronic device through various interfaces and lines. By running or executing software programs and / or the present application stored in the memory 302, and calling the data stored in the memory 302, it executes various functions of the electronic device and processes data, thereby monitoring the electronic device as a whole. Optionally, the processor 301 may include one or more processing cores; preferably, the processor 301 may integrate an application processor and a modulation and demodulation processor. Among them, the application processor mainly processes operation storage media, user interfaces, and application programs, etc., and the modulation and demodulation processor mainly processes wireless communication. It can be understood that the above modulation and demodulation processor may not be integrated into the processor 301.

[0079] The memory 302 can be used to store software programs and this application. The processor 301 executes various functional applications and data processing by running the software programs and this application stored in the memory 302. The memory 302 mainly includes a program storage area and a data storage area. Among them, the program storage area can store operating storage media, application programs required for at least one function, etc.; the data storage area can store data created according to the use of the electronic device, etc. In addition, the memory 302 can include high-speed random access memory, and can also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid-state storage devices. Correspondingly, the memory 302 can also include a memory controller to provide the processor 301 with access to the memory 302.

[0080] Although not shown, the electronic device can also include a display unit, an input unit, a power supply, etc., which will not be elaborated here. Specifically in this embodiment, the processor 301 in the electronic device will load the executable files corresponding to the processes of one or more application programs into the memory 302 according to the following instructions, and the processor 301 will run the application programs stored in the memory 302 to implement various functions as follows: Obtain the mask layout to be corrected; Discretize the mask boundary of the mask layout to be corrected to obtain a number of first boundary segments; Based on the Hopkins optical transfer matrix, calculate the Jacobian matrix of each first boundary segment; Input the Jacobian matrix into the offset prediction model to predict the offset of each first boundary segment; Adjust the position of the corresponding first boundary segment according to the offset to generate the corrected mask layout.

[0081] Those of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructions, or by controlling related hardware through instructions. The instructions can be stored in a computer-readable storage medium and loaded and executed by the processor.

[0082] For this reason, the embodiment of this application provides a storage medium, which stores multiple instructions that can be loaded by the processor to execute the steps in any method provided by the embodiment of this application. For example, the instructions can execute the following steps: Obtain the mask layout to be corrected; Discretize the mask boundary of the mask layout to be corrected to obtain a number of first boundary segments; Based on the Hopkins optical transfer matrix, calculate the Jacobian matrix of each first boundary segment; Input the Jacobian matrix into the offset prediction model to predict the offset of each first boundary segment; Adjust the position of the corresponding first boundary segment according to the offset to generate a corrected mask layout.

[0083] For the specific implementation of each of the above operations, reference may be made to the previous embodiments, which will not be elaborated here.

[0084] Among them, the storage medium may include: Read Only Memory (ROM), Random Access Memory (RAM), magnetic disk or optical disc, etc.

[0085] Since the instructions stored in the storage medium can execute the steps in any method provided in the embodiments of the present application, the beneficial effects achievable by any method provided in the embodiments of the present application can be realized. For details, refer to the previous embodiments, which will not be elaborated here.

[0086] The optical proximity effect correction method, device, storage medium and electronic device provided in the present application have been introduced in detail above. Specific examples are used in this article to elaborate on the principle and implementation manner of the present application. The description of the above embodiments is only used to help understand the core idea of the present application; at the same time, for those skilled in the art, according to the idea of the present application, there will be changes in the specific implementation manner and application scope. In summary, the content of this specification should not be construed as a limitation to the present application.

Claims

1. An optical proximity effect correction method, characterized in that, Including: Obtain the mask layout to be corrected; Discretize the mask boundary of the mask layout to be corrected to obtain a number of first boundary segments; Based on the Hopkins optical transfer matrix, calculate the Jacobian matrix of each first boundary segment; Input the Jacobian matrix into an offset prediction model to predict the offset of each first boundary segment; Adjust the position of the corresponding first boundary segment according to the offset to generate a corrected mask layout.

2. The optical proximity effect correction method according to claim 1, characterized in that The adjusting the position of the corresponding first boundary segment according to the offset to generate a corrected mask layout includes: Based on the offset, update the position of the corresponding first boundary segment by Newton's iterative method until the convergence condition is reached; When the convergence condition is reached, generate a corrected mask layout.

3. The optical proximity effect correction method according to claim 2, wherein, The updating the position of the corresponding first boundary segment by Newton's iterative method based on the offset until the convergence condition is reached includes: Update the position of the corresponding first boundary segment according to the offset; Based on the updated first boundary segment, update the transmission spectrum of the mask layout to be corrected; Calculate the current exposure error according to the Hopkins optical transfer matrix and the updated transmission spectrum; Based on the current exposure error, update the position of the corresponding first boundary segment by Newton's iterative method until the convergence condition is reached.

4. The optical proximity effect correction method according to claim 3, characterized in that The updating the position of the corresponding first boundary segment by Newton's iterative method based on the current exposure error until the convergence condition is reached includes: When the current exposure error is greater than the threshold, return to execute the step of calculating the Jacobian matrix of each first boundary segment based on the Hopkins optical transfer matrix; When the current exposure error is less than or equal to the threshold, determine that the convergence condition is reached.

5. The optical proximity effect correction method according to claim 1, characterized in that Also including: Construct a Hopkins optical transfer matrix; Construct an offset prediction model.

6. The optical proximity effect correction method according to claim 5, characterized in that The constructing the offset prediction model includes: Obtain a test mask layout; Discretize the mask boundary of the test mask layout to obtain a number of second boundary segments; Based on the Hopkins optical transfer matrix, calculate the Jacobian matrix and Hessian matrix of each second boundary segment; Calculate the true offset of each second boundary segment based on the Hessian matrix; Use the true offset as the training label and the Jacobian matrix as the input data to train a preset Unet network model to generate an offset prediction model.

7. The optical proximity effect correction method according to claim 5, wherein The constructing the Hopkins optical transfer matrix includes: Obtain the optical parameters of the lithography system; According to the optical parameters, establish an optical imaging system using the Hopkins imaging model; Calculate the Hopkins optical transfer matrix based on the optical imaging system.

8. An optical proximity effect correction device, characterized in that Including: An acquisition unit for obtaining the mask layout to be corrected; A discretization unit for discretizing the mask boundary of the mask layout to be corrected to obtain a number of first boundary segments; A calculation unit for calculating the Jacobian matrix of each first boundary segment based on the Hopkins optical transfer matrix; A prediction unit for inputting the Jacobian matrix into an offset prediction model to predict the offset of each first boundary segment; A correction unit, configured to adjust the position corresponding to the first boundary segment according to the offset, and generate a corrected mask layout.

9. A storage medium, characterized in that, The storage medium stores multiple instructions, and the instructions are adapted to be loaded by a processor to execute the optical proximity effect correction method according to any one of claims 1-7.

10. An electronic device, characterized in that, It includes a memory, a processor, and a computer program stored on the memory and executable on the processor. Wherein, when the processor executes the computer program, it implements the optical proximity effect correction method according to any one of claims 1-7.

Images