Auxiliary pattern determination method, device and equipment for mask layout and storage medium

Abstract

The application discloses a mask pattern auxiliary pattern determination method, device and equipment and a storage medium. The mask pattern auxiliary pattern determination method comprises the following steps: obtaining a pixel-level mask matrix determined according to inverse lithography technology optimization and an initial binary mask matrix; dividing an auxiliary pattern layout area in the initial binary mask matrix according to the pixel value of each pixel unit in the pixel-level mask matrix and MRC rule constraint; generating a plurality of different auxiliary patterns in the auxiliary pattern layout area, obtaining a plurality of candidate binary mask matrices corresponding to each auxiliary pattern; performing exposure simulation on each candidate binary mask matrix, obtaining a candidate binary mask matrix corresponding to an exposure image with the minimum deviation from a target exposure image, and obtaining auxiliary pattern information in the mask pattern. In the application, the imaging advantage of the inverse lithography technology is retained, and the operation amount and operation difficulty of auxiliary pattern layout operation are reduced.

Description

Technical Field

[0001] This invention relates to the field of computational lithography and mask patterning technology, and in particular to an auxiliary pattern determination method, apparatus, device, and computer-readable storage medium for mask patterns. Background Technology

[0002] Photolithography is a crucial process technology for manufacturing semiconductor chips, and its precision directly determines the chip's performance, cost, and integration density. A photomask is an essential tool for photolithographic exposure, and the accuracy and reliability of the photomask pattern directly determine the precision of the photolithography.

[0003] Traditional optical proximity correction (OPC) technology compensates for deformation caused by diffraction by making minor geometric adjustments to the edges of the main mask pattern, such as indentation, convexity, and the addition of serifs. It has been widely adopted in mature manufacturing processes. However, for high-density, complex, and irregularly shaped target patterns, the mask pattern determined by OPC technology is often limited in accuracy, making it difficult to meet the high-precision imaging requirements of advanced manufacturing processes.

[0004] Inverse Lithography (ILT) technology uses the ideal imaging result of the wafer surface as the optimization endpoint to iteratively solve for a pixel-level continuous grayscale distribution mask. Under the constraints of a given optical system, it can approximate the theoretically optimal imaging effect, significantly reducing edge placement errors and exhibiting far superior adaptability to complex layouts compared to traditional OPC technology. However, current technology can only fabricate binary masks with both transparent and opaque states, making it impossible to industrialize the continuous grayscale mask directly output by ILT. If a simple global threshold binarization is applied to the continuous grayscale mask, a large amount of diffraction compensation details will be lost, significantly diminishing the imaging optimization advantages of ILT. Therefore, a solution is adopted that adds a sub-resolution assist feature (SRAF) around the main image. By introducing additional diffraction components through the assist feature, the light field distribution is modulated, improving the imaging quality of the main image. This transforms the optimal grayscale solution determined by ILT into a manufacturable binary mask with an assist feature, thus balancing the optimal imaging advantages of ILT with mask manufacturability.

[0005] However, the current methods for determining sub-resolution auxiliary graphics in the mask pattern mostly involve generating them randomly or through batch exhaustive search, and then filtering them one by one based on lithography simulation. This method of determining sub-resolution auxiliary graphics has the problems of extremely high computational cost, difficulty in algorithm implementation, and insufficient accuracy in the final arrangement of sub-resolution auxiliary graphics. Summary of the Invention

[0006] The purpose of this invention is to provide a method, apparatus, device, and computer-readable storage medium for determining auxiliary patterns in a mask layout. This method can accurately and reliably achieve the layout setting of auxiliary patterns using reverse photolithography, reduce the computational overhead of determining the layout setting of auxiliary patterns in the mask layout, and ensure the accuracy and reliability of the layout of auxiliary patterns.

[0007] To solve the above-mentioned technical problems, the present invention provides an auxiliary pattern determination method for a mask layout, comprising:

[0008] Obtain the pixel-level mask matrix optimized according to the reverse lithography technique, and construct an initial binary mask matrix with the same size as the pixel-level mask matrix;

[0009] Based on the pixel values ​​of each pixel unit in the pixel-level mask matrix and the MRC rule constraints, an auxiliary graphic layout area is divided in the initial binary mask matrix;

[0010] According to the MRC rule constraints, multiple sets of different auxiliary graphics are generated in the auxiliary graphics layout area of ​​the initial binarized mask matrix, and multiple sets of candidate binarized mask matrices corresponding to each set of auxiliary graphics are obtained.

[0011] Exposure simulation is performed on each of the candidate binarized mask matrices, and the obtained exposed image is compared with the target exposed image to obtain the candidate binarized mask matrix corresponding to the exposed image with the smallest deviation from the target exposed image, thereby obtaining auxiliary graphic information in the mask layout.

[0012] Optionally, constructing an initial binarized mask matrix with the same size as the pixel-level mask matrix includes:

[0013] Construct a zero matrix with the same size as the pixel-level mask matrix;

[0014] Based on the target layout of the mask layout, the corresponding main graphic region is divided in the all-zero matrix;

[0015] The pixel units in the main graphic region are marked as 1 to obtain the initial binary mask matrix.

[0016] Optionally, based on the pixel values ​​of each pixel unit in the pixel-level mask matrix and the MRC rule constraints, an auxiliary graphic layout region is divided in the initial binarized mask matrix, including:

[0017] According to the MRC rule constraints, an initial layable region is divided in the initial binary mask matrix, consisting of pixel units whose minimum distance from the main graphic region is not less than a set spacing threshold.

[0018] Based on the pixel values ​​of each pixel unit in the pixel-level mask matrix, the pixel units of the initial layable region are filtered to obtain an auxiliary graphic layable region composed of pixel units whose corresponding pixel values ​​are greater than a set pixel threshold.

[0019] Optionally, auxiliary graphics are laid out in different layout methods within the layoutable area of ​​the initial binarized mask matrix to generate multiple sets of candidate binarized mask matrices, including:

[0020] In the auxiliary graphic layout area, multiple connected sub-regions are identified, and the average height and average width of each connected sub-region are calculated.

[0021] With the center of the connected sub-region as the center point, the corresponding average height and average width are the rectangle height and rectangle width, respectively, forming the initial rectangular auxiliary shape corresponding to each connected sub-region;

[0022] Constraints and adjustment conditions according to the MRC rules The initial rectangular auxiliary graphics are scaled and their spacing adjusted to obtain multiple sets of candidate auxiliary graphics with different layouts; among them, , The width and height dimensions of the candidate auxiliary graphic. These are the minimum width dimension and the maximum width dimension, respectively. These are the minimum height dimension and the maximum height dimension, respectively.

[0023] Based on each of the candidate auxiliary graphics, the initial binarization mask matrix is ​​used to generate multiple sets of candidate binarization mask matrices.

[0024] Optionally, exposure simulation is performed on each of the candidate binarized mask matrices, including:

[0025] Perform a two-dimensional Fourier transform on the candidate binarized mask matrix to obtain the mask frequency domain spectrum and the corresponding mask frequency domain spectrum complex conjugate;

[0026] Based on the mask frequency domain spectrum and the complex conjugate of the mask frequency domain spectrum, a photolithographic imaging model is adopted. Exposure simulation calculations are performed to obtain the exposure image; among them, For the pixel unit in the exposed image Exposure intensity, It is a two-dimensional inverse Fourier transform function. These are the mask frequency domain spectrum and the complex conjugate of the mask frequency domain spectrum, respectively. For spatial sampling frequency, , As the imaging kernel of the optical system, for The complex conjugate function, For the first The weight coefficients corresponding to each kernel This represents the total number of equivalent convolution kernels.

[0027] Optionally, the obtained exposed image is compared with the target exposed image to obtain the candidate binarized mask matrix corresponding to the exposed image with the smallest deviation from the target exposed image, thereby obtaining auxiliary graphic information in the mask layout, including:

[0028] Each group of exposed images is compared with the target exposed image to perform an imaging error cost function operation to obtain the imaging error cost function value corresponding to each exposed image.

[0029] The imaging error cost function values ​​are sorted in ascending order, and the candidate binarization mask matrix corresponding to the exposure image with the first n sorted imaging error cost function values ​​is selected.

[0030] Based on the selected candidate binarized mask matrix, multiple sets of auxiliary graphic information are obtained.

[0031] Optionally, the imaging error cost function is calculated by performing an imaging error cost function operation on each group of the exposed images and the target exposed image respectively, to obtain the imaging error cost function value corresponding to each of the exposed images, including:

[0032] Using the exposure image corresponding to the pixel-level mask matrix as the target exposure image, according to the MSE cost function Each of the exposed images is then calculated to obtain the imaging error cost function value; where, The value of the imaging error cost function is... These are the total width and total height dimensions of the candidate binary mask matrix, respectively. For the pixel unit in the exposed image Exposure intensity; For the pixel unit in the target exposed image The intensity of the exposed light.

[0033] An auxiliary pattern determining device for a mask layout, comprising:

[0034] A matrix construction module is used to obtain a pixel-level mask matrix optimized according to the reverse lithography technique, and to construct an initial binary mask matrix with the same size as the pixel-level mask matrix.

[0035] The region division module is used to divide the auxiliary graphic layout area in the initial binary mask matrix according to the pixel value of each pixel unit in the pixel-level mask matrix and the MRC rule constraints;

[0036] The graphic layout module is used to generate multiple sets of different auxiliary graphics in the auxiliary graphic layout area of ​​the initial binary mask matrix according to the MRC rule constraints, and to obtain multiple sets of candidate binary mask matrices corresponding to each set of auxiliary graphics.

[0037] The simulation filtering module is used to perform exposure simulation on each of the candidate binary mask matrices, compare the obtained exposure image with the target exposure image, obtain the candidate binary mask matrix corresponding to the exposure image with the smallest deviation from the target exposure image, and obtain auxiliary graphic information in the mask layout.

[0038] An auxiliary pattern determination device for a mask layout, comprising:

[0039] Memory, used to store computer programs;

[0040] A processor for executing the computer program to implement the steps of the auxiliary graphic determination method for the mask layout as described in any of the preceding claims.

[0041] A computer-readable storage medium storing a computer program that is executed by a processor to implement the steps of the auxiliary graphic determination method for a mask layout as described in any of the preceding claims.

[0042] This invention provides a method, apparatus, device, and computer-readable storage medium for determining auxiliary patterns in a mask layout. The method includes: obtaining a pixel-level mask matrix optimized using reverse lithography; constructing an initial binarized mask matrix with the same size as the pixel-level mask matrix; dividing the initial binarized mask matrix into a region where auxiliary patterns can be laid out, based on the pixel values ​​of each pixel unit in the pixel-level mask matrix and MRC rule constraints; laying out auxiliary patterns in the region of the initial binarized mask matrix according to different layout methods to generate multiple sets of candidate binarized mask matrices; performing exposure simulation on each candidate binarized mask matrix to obtain an exposed image; and obtaining auxiliary pattern information in the mask layout based on the candidate binarized mask matrix corresponding to the exposed image with the smallest deviation from the target exposed image.

[0043] This application uses the pixel-level mask matrix determined by optimization based on the reverse lithography technique as a basis, and combines it with MRC rule constraints to accurately and reliably divide the auxiliary graphic layout area in the initial binary mask matrix. Furthermore, it realizes various auxiliary graphic layouts in the auxiliary graphic layout area, and selects the auxiliary graphic based on the minimum deviation of the target exposure image through exposure simulation of the candidate binary mask matrix with different auxiliary graphics. This avoids blindly exhaustively arranging auxiliary graphics. On the basis of meeting the mask plate making process constraints, it completes the solution of auxiliary graphics that retains the imaging advantages of the reverse lithography technique and can be industrialized, reducing the computational load and difficulty of auxiliary graphic layout calculation. Attached Figure Description

[0044] To more clearly illustrate the technical solutions of the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0045] Figure 1 A flowchart illustrating the auxiliary graphic determination method for the mask layout provided in the embodiments of this application;

[0046] Figure 2 A structural block diagram of the auxiliary pattern determination device for the mask layout provided in the embodiments of this application. Detailed Implementation

[0047] The core of this invention is to provide a method, apparatus, device, and computer-readable storage medium for determining auxiliary patterns of a mask layout, which completes the solution of auxiliary patterns that retains the imaging advantages of reverse lithography technology and can be industrialized, while reducing the computational load and difficulty of auxiliary pattern layout calculations.

[0048] To enable those skilled in the art to better understand the present invention, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. Obviously, the described embodiments are merely some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0049] like Figure 1 As shown, Figure 1 This is a flowchart illustrating the auxiliary graphic determination method for the mask layout provided in the embodiments of this application.

[0050] In one specific embodiment of this application, the auxiliary pattern determination method for the mask layout may include:

[0051] S1: Obtain the pixel-level mask matrix determined by the reverse lithography technique, and construct an initial binary mask matrix with the same size as the pixel-level mask matrix.

[0052] It is understood that the pixel-level mask matrix in this embodiment is a pixel-level mask matrix with continuous grayscale pixel values ​​determined through optimization iteration using reverse lithography technology. The initial binarized mask matrix is ​​a binarized matrix constructed based on the pixel-level mask matrix. Specifically, it means that the size of the initial binarized mask matrix is ​​the same as the size of the pixel-level mask matrix. That is, the initial binarized mask matrix and the pixel-level mask matrix have the same size. Therefore, there should be a one-to-one correspondence between each pixel unit in the initial binarized mask matrix and each pixel unit in the pixel-level mask matrix.

[0053] Furthermore, the initial binary mask matrix is ​​a binary matrix in which each pixel unit corresponding to the main graphic region is marked as 1, and the remaining pixel units are marked as 0. The main graphic region can be determined by dividing the target layout of the mask pattern in the initial binary mask matrix, or it can be determined by combining the pixel values ​​of each pixel unit in the pixel-level mask matrix with the pattern formed by the target layout. This application does not specifically limit this.

[0054] In this embodiment, the initial binarized mask matrix is ​​also the equivalent mask matrix corresponding to the main graphic in the mask layout, which serves as the carrier matrix for subsequent layout auxiliary graphics (sub-resolution auxiliary graphics).

[0055] In one alternative embodiment, the process of constructing the initial binary mask matrix can be as follows.

[0056] S11: Construct an all-zero matrix with the same size as the pixel-level mask matrix.

[0057] S12: Based on the target layout of the mask layout, divide the corresponding main graphic region in the all-zero matrix.

[0058] S13: Mark the pixel units in the main graphic area as 1 to obtain the initial binary mask matrix.

[0059] In practical applications, the position of each pixel unit in the all-zero matrix on the target layout can be determined by combining the pattern of the target layout with the position of each pixel unit in the all-zero matrix. The main graphic area covered by the main graphic in the all-zero matrix can be determined by marking each pixel unit in the main graphic area as 1, thus obtaining the initial binary mask matrix.

[0060] S2: Based on the pixel values ​​of each pixel unit in the pixel-level mask matrix and the MRC rule constraints, divide the auxiliary graphic layout area in the initial binary mask matrix.

[0061] As mentioned above, the initial binarized mask matrix serves as the carrier matrix for setting auxiliary graphics. However, it is clear that not every pixel unit in the initial binarized mask matrix can be used to place auxiliary graphics. For example, the placement of auxiliary graphics should obviously avoid the main graphic area, meaning that the areas not in the main graphic area and the areas where auxiliary graphics are placed should not overlap. Furthermore, considering the actual manufacturing process limitations of the mask, the spacing between the auxiliary graphics and the main graphic should not be too small, i.e., it should follow the MRC rule constraint (Mask Rule Check, minimum rule constraint) to ensure that the placed auxiliary graphics can be industrially implemented.

[0062] Therefore, in one alternative embodiment, the process of dividing the auxiliary graphic layoutable region in the initial binary mask matrix can be as follows.

[0063] S21: According to the MRC rule constraints, divide the initial layoutable area in the initial binary mask matrix into pixel units whose minimum distance from the main graphic area is not less than the set spacing threshold.

[0064] S22: Based on the pixel values ​​of each pixel unit in the pixel-level mask matrix, filter the pixel units of the initial layable area to obtain the auxiliary graphic layable area composed of pixel units whose corresponding pixel values ​​are greater than the set pixel threshold.

[0065] MRC rule constraints refer to the geometric dimensional constraints that a mask must follow due to the mask manufacturing process, including constraints such as minimum graphic size, minimum graphic spacing, minimum graphic area, and corner spacing. The setting of the spacing threshold in S21 of this embodiment is also based on the minimum graphic spacing in the MRC rule constraints, and the setting of the spacing threshold should be greater than or equal to the minimum graphic spacing in the MRC rule constraints.

[0066] Based on this, during the process of dividing the initial layable area, each pixel unit marked as 0 in the initial binary mask matrix can be subjected to Euclidean distance calculation with each pixel unit marked as 1 (i.e., the pixel unit in the main graphic area). If the Euclidean distance between the pixel unit marked as 0 and all pixel units marked as 1 is greater than the set spacing threshold, then the pixel unit marked as 0 can be divided into the pixel unit in the initial layable area.

[0067] Of course, in practical applications, we can first identify the edge pixel units of the main graphic area in the initial binary mask matrix. During the process of dividing the initial layable area, we can perform Euclidean distance calculations on each pixel unit marked as 0 and each edge pixel unit in turn. Pixel units that have an Euclidean distance greater than the set spacing threshold and are marked as 0 can be divided into pixel units in the initial layable area.

[0068] In step S21 of this embodiment, according to the MRC rule constraint, the main graphic region in the initial binarized mask matrix is ​​expanded outward by a set spacing threshold size. The region outside the expanded region can be used as the initial layoutable region, thereby initially ensuring that the auxiliary graphics set in the subsequent layout must satisfy the MRC rule with the main graphic.

[0069] Based on this, it is further considered that in the pixel-level mask matrix, the pixel units with relatively small pixel values ​​outside the target main graphic area have low light transmittance and are not suitable for setting auxiliary graphics. Therefore, in the initial binary mask matrix that carries the auxiliary graphics, the pixel units at the same position should also not be suitable for placing auxiliary graphics.

[0070] Based on this, this embodiment further filters each pixel unit in the initial layable region. Specifically, it can be determined by whether the pixel value of the pixel unit corresponding to the same position in the pixel-level mask matrix is ​​greater than a set pixel threshold. For example, if the pixel value of the pixel unit corresponding to the same position in the pixel-level mask matrix of a pixel unit in the initial layable region is greater than the set pixel threshold, then this pixel unit in the initial layable region can be assigned to the auxiliary graphic layable region. If the pixel value is not greater than the set pixel threshold, then the pixel unit is removed from the initial layable region. In this embodiment, the set pixel threshold can be set to 0.3, 0.4, or 0.5, and should at least not be greater than 0.5.

[0071] In this embodiment, by using MRC rule constraints and the dual filtering of pixel unit grayscale values ​​in the pixel-level mask matrix, the region in the initial binary mask matrix that can be reasonably arranged and set with auxiliary graphics is more accurately selected and divided. This effectively and reasonably reduces the layout range of auxiliary graphics, which greatly reduces the number of auxiliary graphics layouts while ensuring the reliability of subsequent auxiliary graphics layout settings.

[0072] S3: Based on the MRC rule constraints, generate multiple sets of different auxiliary graphics in the layout area of ​​the auxiliary graphics of the initial binary mask matrix, and obtain multiple sets of candidate binary mask matrices corresponding to each set of auxiliary graphics.

[0073] After dividing the auxiliary graphic layout area in the initial binary mask matrix, the auxiliary graphic can also have a variety of different layouts in the layout area. Thus, under the condition of the area range restriction of the layout area, multiple sets of auxiliary graphics with different layouts can be randomly generated.

[0074] Alternatively, the actual layout process for generating auxiliary graphics can be as follows.

[0075] S31: Identify multiple connected sub-regions in the layoutable area of ​​the auxiliary graphics, and calculate the average height and average width of each connected sub-region.

[0076] S32: Using the center of the connected sub-region as the center point, the corresponding average height and average width are the height and width of the rectangle, respectively, forming the initial rectangular auxiliary shape corresponding to each connected sub-region.

[0077] S33: Constrain and adjust constraints according to MRC rules The initial rectangular auxiliary graphics are scaled and their spacing adjusted to obtain multiple sets of candidate auxiliary graphics with different layouts; among them, , For the width and height dimensions of the candidate auxiliary graphics, These are the minimum width dimension and the maximum width dimension, respectively. These are the minimum height dimension and the maximum height dimension, respectively.

[0078] S34: Generate multiple sets of candidate binary mask matrices from the initial binary mask matrix based on each candidate auxiliary graphic.

[0079] In this embodiment, a connected sub-region composed of multiple pixel units is formed within the layoutable area of ​​the auxiliary graphic. This forms an initial rectangular auxiliary graphic with the center of the connected sub-region as its center point, and the average height and width of the connected sub-region as its rectangle height and width, respectively. Setting the initial rectangular auxiliary graphic as a rectangle in this embodiment makes the shape of the auxiliary graphic units more regular and reduces the difficulty of manufacturing the auxiliary graphic. Using the average height and width of the connected sub-region as the height and width dimensions of the initial rectangular auxiliary graphic avoids the initial rectangular auxiliary graphic from deviating significantly from the coverage area of ​​the connected sub-region due to extremely large or small dimensions in a few rows or columns, thus ensuring the reliability of the initial rectangular auxiliary graphic.

[0080] The above is the initial rectangular auxiliary graphic generated based on the connected sub-regions of the layoutable area of ​​the auxiliary graphic. However, in practical applications, as many different layout schemes of the auxiliary graphic as possible should be given in order to select the optimal layout scheme of the auxiliary graphic.

[0081] Based on this, various layouts of the auxiliary graphic can be achieved by adjusting and transforming the initial rectangular auxiliary graphic. Simultaneously, to ensure the layout of the auxiliary graphic is suitable for production manufacturing, it can be constrained according to MRC rules and adjustment constraints. Specific adjustment constraints can be... .

[0082] In this embodiment, the minimum height and minimum width dimensions are determined based on the minimum graphic size in the MRC rule constraints. During the adjustment process of the initial rectangular auxiliary graphic's height, width, and spacing according to the adjustment constraints and MRC rule constraints, if the initial rectangular auxiliary graphic satisfies that its width is greater than the minimum width and its height is greater than the minimum height, and if its height is greater than the maximum height, then its height can be reduced to equal the maximum height. Similarly, if its width is greater than the maximum width, then the width of the candidate auxiliary graphic can be reduced to the maximum width.

[0083] Furthermore, if the height of the initial rectangular auxiliary graphic is less than the minimum height, it can be directly discarded. If the spacing between the initial rectangular auxiliary graphic and its neighboring counterparts is greater than the minimum spacing requirement of the MRC rule, the height of the initial rectangular auxiliary graphic can be appropriately increased to obtain a candidate auxiliary graphic that satisfies both the adjustment constraint and the MRC rule. If the spacing between the initial rectangular auxiliary graphic and its neighboring counterparts is limited by the minimum spacing requirement, preventing the adjustment of the initial rectangular auxiliary graphic's height, it can be discarded. In practical applications, if the height of the initial rectangular auxiliary graphic is small and the spacing between it and its neighboring counterparts is sufficiently large, it can be processed in two different ways: discarding or increasing its height, resulting in two different auxiliary graphic layout schemes. Using the height of the initial rectangular auxiliary graphic as an example, the same principle applies to the width of the initial rectangular auxiliary graphic; it can be compared to the minimum width and adjusted in a similar manner. This will not be repeated here.

[0084] Furthermore, if the distance (including the corner distance) between two adjacent initial rectangular auxiliary figures is less than the minimum distance size constrained by the MRC rule, the relative position between the initial rectangular auxiliary figures or the size of one of the initial rectangular auxiliary figures can be adjusted.

[0085] Provided that the width and height dimensions of two adjacent initial auxiliary graphics meet the above adjustment constraints, different spacing dimensions between the two initial rectangular auxiliary graphics can also be adjusted (which should always be greater than the minimum spacing dimension in the MRC rule constraints) to generate different layout schemes for the auxiliary graphics.

[0086] Based on the above discussion, the process of adjusting the initial rectangular auxiliary graphics can be as follows: First, check if the spacing between different initial rectangular auxiliary graphics meets the minimum spacing requirement of the MRC rule. If it does, the two initial rectangular auxiliary graphics can be retained as candidate auxiliary graphics. Otherwise, without violating the minimum width and minimum height constraints of a single initial rectangular auxiliary graphic, reduce the size of the two initial rectangular auxiliary graphics equally. If reducing the size of one initial rectangular auxiliary graphic would violate the minimum width and / or minimum height, adjust the size of the other initial rectangular auxiliary graphic to meet the minimum spacing constraint of the two initial rectangular auxiliary graphics. If neither initial rectangular auxiliary graphic can be reduced, one is randomly discarded. This process continues until all generated candidate auxiliary graphics simultaneously meet their own size constraints and mutual spacing constraints. Finally, multiple sets of candidate auxiliary graphics with different layouts are generated. The pixel units covered by each set of candidate auxiliary graphics are marked as 1, which generates the corresponding candidate binary mask matrix from the initial binary mask matrix. Multiple sets of candidate auxiliary graphics can generate N sets of initial binary mask matrices.

[0087] In this embodiment, the pixel values ​​of the pixel-level mask matrix are used as the basis to screen the layout area of ​​auxiliary graphics, and the connected sub-regions are aggregated to generate an initial rectangular auxiliary graphic. Then, through adaptive size correction and iterative adjustment of the spacing between auxiliary graphics, the generated auxiliary graphics meet the mask manufacturing constraints of MRC rules in terms of both the size of the single graphic and the spacing between the graphics, ensuring that the layout can be made into a plate. In addition, multiple sets of differentiated and compliant candidate auxiliary graphic layouts are generated in batches to provide sufficient candidate samples for subsequent imaging simulation to select the optimal solution.

[0088] S4: Perform exposure simulation on each candidate binarized mask matrix, compare the obtained exposed image with the target exposed image, obtain the candidate binarized mask matrix corresponding to the exposed image with the smallest deviation from the target exposed image, and obtain auxiliary graphic information in the mask pattern.

[0089] Exposure simulation of each candidate binarized mask matrix is ​​used to screen and verify the layout of auxiliary graphics in the candidate binarized mask matrix.

[0090] Alternatively, this simulated exposure process can be as follows.

[0091] S41: Perform a two-dimensional Fourier transform on the candidate binarized mask matrix to obtain the mask frequency domain spectrum and the corresponding complex conjugate of the mask frequency domain spectrum.

[0092] S42: Based on the mask frequency domain spectrum and the complex conjugate of the mask frequency domain spectrum, a photolithographic imaging model is adopted. Exposure simulation calculations are performed to obtain the exposure image; among them, For the pixel unit in the exposed image Exposure intensity, It is a two-dimensional inverse Fourier transform function. These are the mask frequency domain spectrum and the complex conjugate of the mask frequency domain spectrum, respectively. For spatial sampling frequency, , As the imaging kernel of the optical system, for The complex conjugate function, For the first The weight coefficients corresponding to each kernel This represents the total number of equivalent convolution kernels.

[0093] The lithography imaging model in this embodiment fully includes the entire process of optical cross-transfer function, mask spectrum interference superposition, and inverse Fourier transform back to the spatial domain. It strictly matches the optical transfer characteristics of lithography diffraction. The simulated exposure intensity distribution can truly reflect the modulation effect of different binarized mask matrices on the imaging of the main pattern. The simulation results have high credibility, ensuring the rationality of subsequent scheme selection.

[0094] Furthermore, in this embodiment, the candidate binary mask matrix in the spatial domain is subjected to a two-dimensional Fourier transform to obtain the mask spectrum and its conjugate, which is consistent with the essence of photolithography diffraction (the mask pattern is decomposed into diffraction components of different spatial frequencies participating in interference superposition). This can accurately characterize all diffraction frequency components of the mask. The cross transfer function is decomposed into a weighted summation of multiple imaging kernels, thereby allowing all kernels and weight coefficients to be solved in advance. When simulating each group of candidate binary mask matrices in batches, there is no need to repeatedly solve complex double integrals. The calculation is completed by fast Fourier convolution, which greatly reduces the total time spent traversing and simulating multiple groups of candidate binary mask matrices, improves the algorithm iteration efficiency, and facilitates engineering implementation.

[0095] Based on the above discussion, after performing exposure simulation on each candidate binarized mask matrix, each exposed image and the target exposed image can be compared. The specific process is as follows:

[0096] S43: Perform imaging error cost function calculations on each group of exposed images and the target exposed image respectively to obtain the imaging error cost function value corresponding to each exposed image.

[0097] S44: Sort the imaging error cost function values ​​in ascending order, and select the candidate binarization mask matrix corresponding to the exposure image with the first n sorted imaging error cost function values.

[0098] S45: Output multiple sets of auxiliary graphic information based on the selected candidate binary mask matrix.

[0099] In this embodiment, the overall deviation between the exposed image and the target exposed image corresponding to each candidate binarized mask matrix is ​​calculated pixel by pixel using a cost function. This transforms the imaging quality of the auxiliary graphic layout in different candidate binarized mask matrices into quantifiable values, enabling an intuitive evaluation of the imaging effect of the auxiliary graphics in the binarized mask matrix. Furthermore, all imaging error cost function values ​​are sorted in ascending order, and the top n candidate binarized mask matrices with the smallest errors are selected. This means that the layout of the auxiliary graphics in the multiple candidate binarized mask matrices with the best imaging effect is selected. This approach not only yields the auxiliary graphic layout with the best imaging performance for mask preparation but also retains multiple alternative schemes, facilitating flexible selection based on layout constraints and process requirements, thereby improving the adaptability and flexibility of the auxiliary graphic layout.

[0100] Optionally, the process of calculating the corresponding imaging error cost function value for the exposed image may include:

[0101] The target exposure image is the exposure image corresponding to the pixel-level mask matrix, and the MSE cost function is used. Calculate the imaging error cost function value for each exposed image; where, The value of the imaging error cost function. These represent the total width and total height dimensions of the candidate binary mask matrix, respectively. For the pixel unit in the exposed image Exposure intensity; For the target exposure of the pixel unit in the image The intensity of the exposed light.

[0102] In this embodiment, the pixel-level mask matrix itself is obtained through iterative optimization based on reverse lithography, with the goal of making the exposed image as close as possible to the design target image. Therefore, the exposed image of the pixel-level mask matrix itself represents the optimal imaging result that the optical system can achieve. Thus, the target exposed image obtained by exposure simulation using the pixel-level mask matrix can be used as a benchmark for evaluating the exposed images of each candidate binarized mask matrix.

[0103] Of course, in practical applications, the target exposure image can also be generated directly based on the designed target pattern to calculate the imaging error cost function value, without affecting the implementation of the technical solution in this application.

[0104] Based on the above discussion, this embodiment determines multiple sets of candidate binary mask matrices by comparing and filtering between each exposed image and the target exposed image. The layout information of the auxiliary graphics in each candidate binary mask matrix is ​​also the information of multiple sets of auxiliary graphics in the final output mask layout. In practical applications, the layout information of the auxiliary graphics may not be output, and the selected candidate binary mask matrices may be directly used as the mask layout.

[0105] In summary, this application uses the pixel-level mask matrix determined by the optimization based on the back-light lithography technology as a basis, and combines it with MRC rule constraints to accurately and reliably divide the auxiliary graphic layout area in the initial binary mask matrix. Furthermore, it implements various auxiliary graphic layouts within this layout area. By analyzing candidate binary mask matrices with different auxiliary graphics, and then using exposure simulation to select the optimal auxiliary graphic based on the minimum deviation of the target exposure image, it avoids blindly exhaustively arranging auxiliary graphics. While meeting the constraints of the mask fabrication process, it solves for auxiliary graphics that retain the imaging advantages of back-light lithography technology and can be industrially implemented, reducing the computational load and difficulty of auxiliary graphic layout calculations.

[0106] The auxiliary pattern determination device for mask layout provided in the embodiments of the present invention will be described below. The auxiliary pattern determination device for mask layout described below can be referred to in correspondence with the auxiliary pattern determination method for mask layout described above.

[0107] Figure 2 A structural block diagram of the auxiliary pattern determination device for the mask layout provided in the embodiments of this application is shown below. Figure 2 The auxiliary pattern determining device for the mask layout may include:

[0108] The matrix construction module 100 is used to obtain the pixel-level mask matrix determined by optimization based on the reverse lithography technique, and to construct an initial binary mask matrix with the same size as the pixel-level mask matrix.

[0109] The region division module 200 is used to divide the auxiliary graphic layout area in the initial binary mask matrix according to the pixel value of each pixel unit in the pixel-level mask matrix and the MRC rule constraints.

[0110] The graphic layout module 300 is used to generate multiple sets of different auxiliary graphics in the auxiliary graphic layout area of ​​the initial binary mask matrix according to the MRC rule constraints, and obtain multiple sets of candidate binary mask matrices corresponding to each set of auxiliary graphics.

[0111] The simulation filtering module 400 is used to perform exposure simulation on each candidate binarized mask matrix, compare the obtained exposure image with the target exposure image, obtain the candidate binarized mask matrix corresponding to the exposure image with the smallest deviation from the target exposure image, and obtain auxiliary graphic information in the mask pattern.

[0112] In an optional embodiment, the matrix construction module 100 is specifically used to construct an all-zero matrix with the same size as the pixel-level mask matrix; according to the target layout of the mask layout, to divide the corresponding main graphic region in the all-zero matrix; and to mark the pixel units in the main graphic region as 1 to obtain an initial binary mask matrix.

[0113] In an optional embodiment, the region division module 200 is specifically used to divide an initial layable region composed of pixel units whose minimum distance from the main graphic region is not less than a set spacing threshold in the initial binary mask matrix according to the MRC rule constraints; and to filter each pixel unit in the initial layable region according to the pixel value of each pixel unit in the pixel-level mask matrix to obtain an auxiliary graphic layable region composed of pixel units whose corresponding pixel value is greater than the set pixel threshold.

[0114] In one optional embodiment, the graphic layout module 300 is specifically configured to identify multiple connected sub-regions in the auxiliary graphic layoutable area, calculate the average height and average width of each connected sub-region, take the center of the connected sub-region as the center point, and form an initial rectangular auxiliary graphic corresponding to each connected sub-region with the corresponding average height and average width as the rectangle height and rectangle width, respectively; and constrain and adjust the constraints according to the MRC rules. The initial rectangular auxiliary graphics are scaled and their spacing adjusted to obtain multiple sets of candidate auxiliary graphics with different layouts; among them, , The width and height dimensions of the candidate auxiliary graphic. These are the minimum width dimension and the maximum width dimension, respectively. These are the minimum height dimension and the maximum height dimension, respectively; based on each of the candidate auxiliary graphics, the initial binarized mask matrix is ​​used to generate multiple sets of candidate binarized mask matrices.

[0115] In one optional embodiment, the simulation screening module 400 is specifically used to perform a two-dimensional Fourier transform on the candidate binarized mask matrix to obtain the mask frequency domain spectrum and the corresponding mask frequency domain spectrum complex conjugate; based on the mask frequency domain spectrum and the mask frequency domain spectrum complex conjugate, a photolithography imaging model is used. Exposure simulation calculations are performed to obtain the exposure image; among them, For the pixel unit in the exposed image Exposure intensity, It is a two-dimensional inverse Fourier transform function. These are the mask frequency domain spectrum and the complex conjugate of the mask frequency domain spectrum, respectively. For spatial sampling frequency, , As the imaging kernel of the optical system, for The complex conjugate function, For the first The weight coefficients corresponding to each kernel This represents the total number of equivalent convolution kernels.

[0116] In an optional embodiment, the simulation screening module 400 is specifically used to perform imaging error cost function calculations on each group of the exposed images and the target exposed image respectively to obtain the imaging error cost function value corresponding to each exposed image; sort the imaging error cost function values ​​in ascending order, and select the candidate binarization mask matrix corresponding to the exposed images whose imaging error cost function values ​​are ranked in the top n; and obtain multiple groups of auxiliary graphic information based on the selected candidate binarization mask matrix.

[0117] In an optional embodiment, the simulation screening module 400 is specifically used to, using the exposure image corresponding to the pixel-level mask matrix as the target exposure image, and according to the MSE cost function... Each of the exposed images is then calculated to obtain the imaging error cost function value; where, The value of the imaging error cost function is... These are the total width and total height dimensions of the candidate binary mask matrix, respectively. For the pixel unit in the exposed image Exposure intensity; For the pixel unit in the target exposed image The intensity of the exposed light.

[0118] The auxiliary pattern determination device for the mask layout in this embodiment is used to implement the aforementioned auxiliary pattern determination method for the mask layout. Therefore, the specific implementation of the auxiliary pattern determination device for the mask layout can be found in the embodiment section of the auxiliary pattern determination method for the mask layout above. The specific implementation can be referred to the description of the corresponding embodiments, and will not be repeated here.

[0119] This application also provides an embodiment of an auxiliary pattern determination device for a mask layout, which may include:

[0120] Memory, used to store computer programs;

[0121] A processor for executing the computer program to implement the steps of the auxiliary graphic determination method for the mask layout as described in any of the preceding claims.

[0122] The auxiliary graphic determination methods for the mask layout executed by this processor include:

[0123] A pixel-level mask matrix optimized based on reverse lithography is obtained, and an initial binary mask matrix with the same size as the pixel-level mask matrix is ​​constructed. Based on the pixel values ​​of each pixel unit in the pixel-level mask matrix and MRC rule constraints, an auxiliary graphic layout area is delineated within the initial binary mask matrix. According to MRC rule constraints, multiple sets of different auxiliary graphics are generated within the auxiliary graphic layout area of ​​the initial binary mask matrix, obtaining multiple candidate binary mask matrices corresponding to each set of auxiliary graphics. Exposure simulation is performed on each candidate binary mask matrix, and the obtained exposed image is compared with the target exposed image. The candidate binary mask matrix corresponding to the exposed image with the smallest deviation from the target exposed image is obtained, thus acquiring the auxiliary graphic information in the mask layout.

[0124] This application also provides an embodiment of a computer-readable storage medium storing a computer program that is executed by a processor to implement the steps of the auxiliary pattern determination method for a mask layout as described in any of the preceding claims.

[0125] The computer-readable storage medium includes random access memory (RAM), memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, register, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0126] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that the elements inherent in a process, method, article, or apparatus that includes a list of elements are included. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element. Additionally, portions of the technical solutions provided in the embodiments of this application that are consistent with the implementation principles of corresponding technical solutions in the prior art have not been described in detail to avoid excessive elaboration.

[0127] This article uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. It should be noted that those skilled in the art can make several improvements and modifications to the present invention without departing from the principles of the present invention, and these improvements and modifications also fall within the protection scope of the present invention.

Claims

1. A method for determining auxiliary graphics of a mask layout, characterized in that, include: Obtain the pixel-level mask matrix optimized according to the reverse lithography technique, and construct an initial binary mask matrix with the same size as the pixel-level mask matrix; Based on the pixel values ​​of each pixel unit in the pixel-level mask matrix and the MRC rule constraints, an auxiliary graphic layout area is divided in the initial binary mask matrix; According to the MRC rule constraints, multiple sets of different auxiliary graphics are generated in the auxiliary graphics layout area of ​​the initial binarized mask matrix, and multiple sets of candidate binarized mask matrices corresponding to each set of auxiliary graphics are obtained. Exposure simulation is performed on each of the candidate binarized mask matrices, and the obtained exposed image is compared with the target exposed image to obtain the candidate binarized mask matrix corresponding to the exposed image with the smallest deviation from the target exposed image, thereby obtaining auxiliary graphic information in the mask layout. Constructing an initial binary mask matrix with the same size as the pixel-level mask matrix includes: Construct a zero matrix with the same size as the pixel-level mask matrix; Based on the target layout of the mask layout, the corresponding main graphic region is divided in the all-zero matrix; The pixel units in the main graphic region are marked as 1 to obtain the initial binary mask matrix; The obtained exposed image is compared with the target exposed image to obtain the candidate binarized mask matrix corresponding to the exposed image with the smallest deviation from the target exposed image. Auxiliary graphic information in the mask layout is then obtained, including: Each group of exposed images is compared with the target exposed image to perform an imaging error cost function operation to obtain the imaging error cost function value corresponding to each exposed image. The imaging error cost function values ​​are sorted in ascending order, and the candidate binarization mask matrix corresponding to the exposure image with the first n sorted imaging error cost function values ​​is selected. Based on the selected candidate binarized mask matrix, multiple sets of auxiliary graphic information are obtained.

2. The method for determining auxiliary patterns of a mask layout as described in claim 1, characterized in that, Based on the pixel values ​​of each pixel unit in the pixel-level mask matrix and the MRC rule constraints, auxiliary graphic layout regions are divided in the initial binary mask matrix, including: According to the MRC rule constraints, an initial layable region is divided in the initial binary mask matrix, consisting of pixel units whose minimum distance from the main graphic region is not less than a set spacing threshold. Based on the pixel values ​​of each pixel unit in the pixel-level mask matrix, the pixel units of the initial layable region are filtered to obtain an auxiliary graphic layable region composed of pixel units whose corresponding pixel values ​​are greater than a set pixel threshold.

3. The method for determining auxiliary graphics of a mask layout as described in claim 2, characterized in that, In the initial binary mask matrix, auxiliary graphics are laid out in different layout methods within the available area of ​​the auxiliary graphics, generating multiple sets of candidate binary mask matrices, including: In the auxiliary graphic layout area, multiple connected sub-regions are identified, and the average height and average width of each connected sub-region are calculated. With the center of the connected sub-region as the center point, the corresponding average height and average width are the rectangle height and rectangle width, respectively, forming the initial rectangular auxiliary shape corresponding to each connected sub-region; Constraints and adjustments are made in accordance with the MRC rules. The initial rectangular auxiliary graphics are scaled and their spacing adjusted to obtain multiple sets of candidate auxiliary graphics with different layouts; among them, , The width and height dimensions of the candidate auxiliary graphic. These are the minimum width dimension and the maximum width dimension, respectively. These are the minimum height dimension and the maximum height dimension, respectively. Based on each of the candidate auxiliary graphics, the initial binarization mask matrix is ​​used to generate multiple sets of candidate binarization mask matrices.

4. The method for determining auxiliary patterns of a mask layout as described in claim 1, characterized in that, Exposure simulation is performed on each of the candidate binarized mask matrices, including: Perform a two-dimensional Fourier transform on the candidate binarized mask matrix to obtain the mask frequency domain spectrum and the corresponding mask frequency domain spectrum complex conjugate; Based on the mask frequency domain spectrum and the complex conjugate of the mask frequency domain spectrum, a photolithographic imaging model is adopted. Exposure simulation calculations are performed to obtain the exposure image; among them, For the pixel unit in the exposed image Exposure intensity, It is a two-dimensional inverse Fourier transform function. These are the mask frequency domain spectrum and the complex conjugate of the mask frequency domain spectrum, respectively. For spatial sampling frequency, , As the imaging kernel of the optical system, for The complex conjugate function, For the first The weight coefficients corresponding to each kernel This represents the total number of equivalent convolution kernels.

5. The method for determining auxiliary patterns of a mask layout as described in claim 1, characterized in that, Each group of exposed images is compared with the target exposed image using an imaging error cost function to obtain the imaging error cost function value corresponding to each exposed image, including: Using the exposure image corresponding to the pixel-level mask matrix as the target exposure image, according to the MSE cost function Each of the exposed images is then calculated to obtain the imaging error cost function value; where, The value of the imaging error cost function is... These are the total width and total height dimensions of the candidate binary mask matrix, respectively. For the pixel unit in the exposed image Exposure intensity; For the pixel unit in the target exposed image The intensity of the exposed light.

6. An auxiliary pattern determining device for a mask layout, characterized in that, include: A matrix construction module is used to obtain a pixel-level mask matrix optimized according to the reverse lithography technique, and to construct an initial binary mask matrix with the same size as the pixel-level mask matrix. The region division module is used to divide the auxiliary graphic layout area in the initial binary mask matrix according to the pixel value of each pixel unit in the pixel-level mask matrix and the MRC rule constraints; The graphic layout module is used to generate multiple sets of different auxiliary graphics in the auxiliary graphic layout area of ​​the initial binary mask matrix according to the MRC rule constraints, and to obtain multiple sets of candidate binary mask matrices corresponding to each set of auxiliary graphics. The simulation filtering module is used to perform exposure simulation on each of the candidate binary mask matrices, compare the obtained exposure image with the target exposure image, obtain the candidate binary mask matrix corresponding to the exposure image with the smallest deviation from the target exposure image, and obtain auxiliary graphic information in the mask pattern. The matrix construction module is specifically used to construct an all-zero matrix with the same size as the pixel-level mask matrix; and to divide the corresponding main graphic region in the all-zero matrix according to the target layout of the mask layout. The pixel units in the main graphic region are marked as 1 to obtain the initial binary mask matrix; The simulation screening module is specifically used to perform imaging error cost function calculation on each group of the exposure images and the target exposure image respectively to obtain the imaging error cost function value corresponding to each exposure image; sort the imaging error cost function values ​​in ascending order, and select the candidate binarized mask matrix corresponding to the exposure images with the first n sorted imaging error cost function values; Based on the selected candidate binarized mask matrix, multiple sets of auxiliary graphic information are obtained.

7. An auxiliary pattern determination device for a mask layout, characterized in that, include: Memory, used to store computer programs; A processor for executing the computer program to implement the steps of the auxiliary graphic determination method for a mask layout as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that is executed by a processor to implement the steps of the auxiliary graphic determination method for a mask layout as described in any one of claims 1 to 5.

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