Optical proximity correction method, device and equipment of mask graph, and storage medium

Abstract

The application relates to the technical field of semiconductor processing processes, and discloses a mask pattern optical proximity correction method, device, equipment and storage medium, the mask pattern optical proximity correction method comprises the following steps: performing topography prediction on a polishing surface of a wafer to be processed to obtain polishing surface topography information; correcting a focal plane parameter in a simulation optical model according to the polishing surface topography information; and performing optical proximity correction on an initial mask pattern by using the corrected simulation optical model to obtain a corrected mask pattern. In the application, the polishing surface topography information of the wafer to be processed is predicted first, and the focal plane parameter in the simulation optical model is corrected based on the polishing surface topography information, so that the accuracy and reliability of optical proximity correction of the initial mask pattern based on the simulation optical model are ensured, and the processing precision of semiconductor photolithography based on the mask pattern is improved.

Description

Methods, apparatus, equipment and storage media for optical proximity correction of mask images Technical Field

[0001] This invention relates to the field of semiconductor processing technology, and in particular to an optical proximity correction method, apparatus, device, and computer-readable storage medium for a mask pattern. Background Technology

[0002] In the manufacturing of large-scale integrated circuits, chip design patterns are transferred onto wafers using photolithography. As integrated circuit manufacturing processes evolve, the linewidth of the patterns on the wafer gradually shrinks. When the linewidth is significantly smaller than the wavelength of the exposure light source used in the photolithography process, the diffraction effect of photolithography imaging causes a significant deviation between the exposed structural pattern on the wafer and the mask pattern on the photomask. In practical applications, the mask pattern cannot directly replicate the chip design pattern; instead, optical proximity correction based on the diffraction effect is required to ensure that the final exposed structural pattern matches the chip design pattern.

[0003] In semiconductor manufacturing processes, the deposition and exposure of structural layers on wafers are often performed concurrently. The structural layer is deposited first, then polished, and finally exposed. Furthermore, to ensure the pattern formed by exposure matches the design layout, the exposure process is simulated, and optical proximity correction is performed on the mask. However, in simulated exposure, the deposited and polished structural layer is assumed to have a flat surface. In actual manufacturing, the polished surface is not necessarily flat, leading to a discrepancy between the simulated and actual exposure processes. This results in poor reliability of the corrected mask, ultimately affecting the precision of the exposure process on semiconductor wafers. Summary of the Invention

[0004] The purpose of this invention is to provide a method, apparatus, device, and computer-readable storage medium for optical proximity correction of mask patterns, which can improve the accuracy of optical proximity correction of mask plates to a certain extent, improve the reliability of the corrected mask pattern, and ultimately improve the precision of semiconductor exposure processing.

[0005] To solve the above-mentioned technical problems, the present invention provides an optical proximity correction method for a mask image, comprising:

[0006] The morphology of the polished surface of the wafer to be processed is predicted to obtain the morphology information of the polished surface;

[0007] The focal plane parameters in the simulated optical model are corrected based on the polished surface morphology information.

[0008] Using the modified simulated optical model, optical proximity correction is performed on the initial mask pattern to obtain the corrected mask image.

[0009] In one optional embodiment of this application, morphology prediction is performed on the polished surface of the wafer to be processed to obtain polished surface morphology information, including:

[0010] Based on the single-simulation exposure area that the simulated optical model can simulate in a single operation during optical proximity correction of the initial mask pattern, the polished surface of the wafer to be processed is divided into regions to determine local areas.

[0011] The morphology prediction is performed on each local region on the polished surface of the wafer to be processed to obtain the polished surface morphology information corresponding to each local region;

[0012] Based on the polished surface morphology information, determine the average height of the polished surface corresponding to each local area;

[0013] Accordingly, the focal plane parameters in the simulated optical model are corrected based on the polished surface morphology information, including...

[0014] The average height of the polished surface in the local area is used as the focal plane compensation amount in the simulation optical model of the corresponding single simulation exposure area to compensate and correct the focal plane parameters.

[0015] In an optional embodiment of this application, morphology prediction is performed on each local region on the polished surface of the wafer to be processed to obtain polished surface morphology information corresponding to each local region, including:

[0016] The height of each local region on the polished surface of the wafer to be processed is predicted to obtain the average maximum height and average minimum height corresponding to each local region;

[0017] Accordingly, based on the polished surface morphology information, the average height of the polished surface corresponding to each local region is determined, including:

[0018] The average height of the polished surface of each local region is obtained by weighted averaging of the average maximum height and the average minimum height.

[0019] In an optional embodiment of this application, after obtaining the average maximum height and average minimum height corresponding to each local region based on the polished surface morphology information, the method further includes:

[0020] The height difference is obtained by performing a difference calculation between the average maximum height and the average minimum height within the same local area.

[0021] Determine whether there are any local regions in each of the local regions whose corresponding height difference is greater than a set difference threshold;

[0022] If so, the local region where the corresponding height difference is greater than the set difference threshold is segmented to obtain a newly segmented local region;

[0023] The average maximum height and average minimum height of the newly divided local regions are re-predicted until the area of ​​the newly divided local regions is less than a set area threshold and / or the height difference of all the local regions is not greater than the set difference threshold; then, the average height of the polished surface of each local region is weighted and averaged to obtain the average height of the local region.

[0024] In an optional embodiment of this application, morphology prediction is performed on each local region on the polished surface of the wafer to be processed to obtain polished surface morphology information corresponding to each local region, including:

[0025] Based on the material parameters and polishing process parameters corresponding to the polished surface structure layer of the wafer to be processed, the morphology of each local region is predicted using a prediction model obtained in advance through neural network learning and training, thereby obtaining the morphology information of the polished surface.

[0026] In an optional embodiment of this application, morphology prediction is performed on each local region on the polished surface of the wafer to be processed to obtain polished surface morphology information corresponding to each local region, including:

[0027] Determine whether the polished surface structure layer on the wafer to be tested is a single material structure layer;

[0028] If so, the polishing process parameters, material parameters, and size parameters of the wafer to be processed are input into the first prediction model to obtain the polished surface morphology information corresponding to the local area;

[0029] If not, then obtain the pattern information of each local area according to the design layout corresponding to the polished surface structure layer; input the pattern information, polishing process parameters, material parameters and the size parameters of the wafer to be processed into the second prediction model to obtain the polished surface morphology information corresponding to the local area;

[0030] Both the first prediction model and the second prediction model are obtained in advance through neural network model training.

[0031] An optical proximity correction device for a mask image, comprising:

[0032] The morphology prediction module is used to predict the morphology of the polished surface of the wafer to be processed and obtain the morphology information of the polished surface.

[0033] The parameter correction module is used to correct the focal plane parameters in the simulated optical model based on the polished surface morphology information.

[0034] The simulation correction module is used to perform optical proximity correction on the initial mask pattern using the corrected simulation optical model to obtain the corrected mask image.

[0035] In an optional embodiment of this application, the topography prediction module is used to divide the polished surface of the wafer to be processed into regions based on the single-simulation exposure area that the simulated optical model can simulate in a single operation during optical proximity correction of the initial mask pattern, and to determine local regions; to perform topography prediction on each of the local regions on the polished surface of the wafer to be processed, and to obtain polished surface topography information corresponding to each local region; and to determine the average height of the polished surface corresponding to each local region based on the polished surface topography information.

[0036] Accordingly, the parameter correction module is specifically used to compensate and correct the focal plane parameters by using the average height of the polished surface in the local area as the focal plane compensation amount in the simulation optical model of the corresponding single simulation exposure area.

[0037] An optical proximity correction device for a mask image includes:

[0038] Memory, used to store computer programs;

[0039] A processor for executing the computer program to implement the steps of the optical proximity correction method for the mask image as described in any of the preceding claims.

[0040] A computer-readable storage medium storing a computer program that is executed to implement the steps of the optical proximity correction method for a mask image as described in any of the preceding claims.

[0041] The present invention provides an optical proximity correction method, apparatus, device, and computer-readable storage medium for a mask pattern. The optical proximity correction method for the mask pattern includes predicting the morphology of the polished surface of the wafer to be processed to obtain polished surface morphology information; correcting the focal plane parameters in a simulation optical model based on the polished surface morphology information; and using the corrected simulation optical model to perform optical proximity correction on the initial mask pattern to obtain a corrected mask pattern.

[0042] In this application, considering the potential for surface undulations in the structural layer after deposition and polishing on the wafer surface, the morphology of the polished surface on the wafer is first predicted during the optical proximity correction process of the mask pattern. Based on the morphology information of the polished surface obtained from the prediction, the focal plane parameters in the simulation optical model are corrected. This allows the corrected simulation optical model to more accurately simulate the exposure process of the structural layer on the wafer, thereby ensuring the accuracy and reliability of the optical proximity correction of the initial mask pattern based on this simulation process. This is beneficial for improving the processing accuracy of photolithography based on the mask pattern. Attached Figure Description

[0043] 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.

[0044] Figure 1 is a schematic diagram of a cross-sectional structure of the exposure process of a semiconductor wafer;

[0045] Figure 2 is a schematic flowchart of the optical proximity correction method for the mask image provided in the embodiment of this application;

[0046] Figure 3 is a structural block diagram of the optical proximity correction device for the mask pattern provided in the embodiment of this application. Detailed Implementation

[0047] The core of this invention is to provide an optical proximity correction method, apparatus, device, and computer-readable storage medium for a mask pattern, which predicts the surface morphology of the polished structural layer, thereby correcting the simulation optical model, ensuring the accuracy and reliability of the optical proximity correction of the mask pattern, and thus improving the processing accuracy of mask exposure based on the mask pattern.

[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] Figure 1 shows a cross-sectional structural flow diagram of the exposure process for a semiconductor wafer. In the flow diagram shown in Figure 1, the exposure process for this semiconductor wafer is roughly as follows:

[0050] (a) A first structural layer 2 is deposited on substrate 1;

[0051] (b) Polish the upper surface of the first structural layer 2;

[0052] (c) A first mask 3 and a first photoresist 4 are placed on the surface of the first structural layer 2 after polishing, and the first exposure is performed to form the first exposure pattern;

[0053] (d) Deposit the second structural layer 5 on the first exposure pattern;

[0054] (e) Polishing the deposited second structural layer 5 to form a polished second structural layer 5;

[0055] (f) A second mask 6 and a second photoresist 7 are set on the surface of the second structural layer 5 after polishing, and a second exposure is performed to form a second exposure pattern.

[0056] In the embodiment shown in Figure 1, two polishing processes were performed, followed by an exposure process after each polishing process. Theoretically, the surface of the structure layer after polishing is a smooth surface. However, due to limitations in the polishing process, as shown in the magnified schematic diagram of the local structure corresponding to the two polishing processes in Figure 1, a slight magnification of the polished surface reveals obvious undulations. During the optical proximity correction process for the mask pattern, it is necessary to simulate the mask exposure process, that is, to simulate the actual mask exposure process of the wafer. If the simulated exposure pattern is completely consistent with the design layout under the masking action of the mask, it indicates that the mask is accurate. Conversely, if the simulated exposure pattern is inconsistent with the design layout, the mask pattern needs to be corrected and adjusted; this process is also called optical proximity correction. During the simulated exposure process, it is assumed that the photosensitive surface on the wafer is a planar surface as shown by the dotted line in the magnified partial view of the polished surface in Figure 1; however, the actual polished surface may deviate from this planar surface. In other words, the simulated exposure photosensitive surface does not match the actual exposure photosensitive surface. The exposure process is relatively sensitive to the shape of the exposed surface. Therefore, treating the polished exposure surface as a flat surface for mask pattern correction inevitably introduces relatively large errors, thereby reducing the processing accuracy of semiconductor exposure.

[0057] Based on this, as shown in Figure 2, which is a flowchart of the optical proximity correction method for the mask image provided in the embodiment of this application.

[0058] In one specific embodiment of this application, the optical proximity correction method for the mask image may include:

[0059] S11: Predict the morphology of the polished surface of the wafer to be processed and obtain the morphology information of the polished surface.

[0060] As shown in the embodiment in Figure 1 above, the upper surface structure of the wafer to be processed was polished before both the first and second exposures, as shown in Figure 1. In this embodiment, the morphology prediction of the polished surface of the wafer to be processed is performed, which is to predict the surface shape after polishing, similar to that shown in Figure 1 before the first and second exposures. Furthermore, this prediction process can be based on a prediction model obtained through pre-trained neural network learning. For example, a large amount of polished surface morphology information data, along with the material parameters and polishing process of the corresponding polished surface structural layer, can be collected in advance as data samples for neural network learning training to ultimately obtain a prediction model, which can then be used for polished surface morphology prediction.

[0061] S12: Correct the focal plane parameters in the simulated optical model based on the polished surface morphology information.

[0062] It should be noted that the simulated optical model in this embodiment is also the optical model that simulates the exposure light source when simulating the exposure process; wherein, the focal plane parameter refers to the position parameter of the photosensitive surface that senses the exposure light.

[0063] It is understood that the predicted polished surface morphology information in this embodiment mainly needs to determine the height offset of the polished surface from the default photosensitive focal plane; the magnitude of this height offset also determines the amount of compensation for the focal plane parameters.

[0064] For example, when the position shown by the dashed line in the magnified view of the polished surface in Figure 1 is taken as the photosensitive focal plane, the corresponding focal plane parameter is 0. Based on the predicted polished surface morphology information, the height deviation of the photosensitive surface from the default photosensitive focal plane can be determined. At this time, the focal plane parameter can be modified to this height offset.

[0065] S13: Using the modified simulated optical model, optical proximity correction is performed on the initial mask pattern to obtain the corrected mask image.

[0066] After correcting the focal plane parameters in the simulated optical model, the exposure process can be simulated based on the corrected model to achieve optical proximity correction of the mask image, ultimately obtaining an accurate and reliable mask image. It is understood that the optical proximity correction process performed in this step is the same as or similar to current conventional optical proximity correction methods, and will not be described in detail in this application.

[0067] Based on the above discussion, this application further considers that when the surface of the structural layer to be exposed is a polished surface, this polished surface is not an absolutely flat surface. This leads to inaccurate simulation of the actual exposure process during optical proximity correction, ultimately resulting in inaccurate mask pattern correction. By predicting and determining the morphology information of the polished surface and correcting the simulation optical model based on this morphology information, the accuracy and reliability of the simulation optical model are ensured. This improves the accuracy and reliability of optical proximity correction of the mask pattern based on the simulation optical model, which is beneficial to ensuring the processing accuracy of exposure processing using the mask pattern.

[0068] In summary, this application takes into account the potential for surface undulations in the structural layer after deposition and polishing on the wafer surface. During the optical proximity correction of the mask pattern, the morphology of the polished surface on the wafer is first predicted. Based on the predicted morphology information, the focal plane parameters in the simulation optical model are corrected. This allows the corrected simulation optical model to more accurately simulate the exposure process of the structural layer on the wafer, ensuring the accuracy and reliability of the exposure pattern obtained based on the simulation optical model. This, in turn, ensures the accuracy and reliability of the initial mask pattern for optical proximity correction based on the exposure pattern, thus improving the processing accuracy of mask exposure based on the mask pattern.

[0069] Based on the above embodiments, in another optional embodiment of this application, the optical proximity correction process of the mask image may include:

[0070] S21: Based on the single-time simulated exposure area that the simulated optical model can simulate in a single time during the optical proximity correction of the initial mask pattern, the polishing surface of the wafer to be processed is divided into regions to determine the local area.

[0071] S22: Perform morphology prediction on each local area of ​​the polished surface of the wafer to be processed to obtain the morphology information of the polished surface corresponding to each local area;

[0072] S23: Determine the average height of the polished surface corresponding to each local area based on the polished surface morphology information;

[0073] S24: The average height of the polished surface in the local area is used as the focal plane compensation amount in the simulation optical model of the corresponding single simulation exposure area to compensate and correct the focal plane parameters.

[0074] S25: Using the modified simulated optical model, optical proximity correction is performed on the initial mask pattern to obtain the corrected mask image.

[0075] Understandably, during the simulation of the exposure process of the wafer to be processed, due to the accuracy requirements of the exposure simulation process and the resource limitations of the simulation computer, the entire surface of the wafer to be processed is not simulated at once. Instead, the exposure process is simulated in batches for different regions on the surface of the wafer to be processed. Based on this, when predicting the morphology of the polished surface of the wafer to be processed, the surface of the wafer to be processed can be divided into regions to form local regions. The size of each local region should not exceed the maximum area that can be simulated in a single simulation. Then, the prediction model is used to predict the polished surface morphology information corresponding to each local region separately, which can improve the accuracy of the polished surface morphology information corresponding to that local region to a certain extent. Of course, it is understandable that when using the prediction model to predict the polished surface morphology information of local regions at different locations, the position of the local region on the wafer to be processed can also be used as one of the factors to be considered in the prediction.

[0076] Furthermore, as mentioned above, since the morphology prediction of the polished surface in this application is mainly to determine the relative offset height between the actual exposure photosensitive surface and the default photosensitive focal plane, the prediction of the polished surface morphology information of each local area in this embodiment is ultimately to obtain the height information of the polished surface relative to the default photosensitive focal plane.

[0077] It is understandable that in the subsequent exposure simulation process, the exposure process of a local area is simulated simultaneously at one time, that is, the same simulation optical model is used. Since the same simulation optical model has only one focal plane parameter, it is sufficient to determine an average height of the polished surface for each local area as the deviation height of the polished surface from the default photosensitive focal plane of the entire local area.

[0078] Furthermore, as mentioned earlier, the division of local regions is based on the size of the exposure area that can be simulated in a single exposure by the simulated optical model. Each local region is obviously no larger than the size of the exposure area that can be simulated in a single exposure by the simulated optical model. The size of the exposure area that can be simulated in a single exposure by the simulated optical model is generally around 20000nm×20000nm due to limitations in computer resources. Within such a small local region, the height fluctuation of the polished surface is generally not too large. Therefore, the average height can be used to characterize the height of the polished surface in this local region, thereby correcting the focal plane parameters in the simulated optical model.

[0079] Optionally, the polished surface morphology information of each local region can be predicted, which may specifically include:

[0080] The height of each local area on the polished surface of the wafer to be processed is predicted, and the average maximum height and average minimum height of each local area are calculated.

[0081] Accordingly, based on the polished surface morphology information, the average height of the polished surface corresponding to each local area is determined, which may include:

[0082] The average height of the polished surface in each local area is obtained by weighting and averaging the average maximum and average minimum heights.

[0083] It is understandable that when predicting the surface profile of the wafer to be processed, it is obviously unnecessary to accurately predict the height information of every point on the polished surface. Therefore, in this embodiment, the most representative average maximum height and average minimum height are predicted for each local area, and the average height of the two height data is weighted and averaged to obtain the average height of the polished surface of the local area. The weighting coefficients in the weighted average can be determined based on statistical principles obtained from human experience, and no specific restrictions are imposed on this in this embodiment.

[0084] Based on this, in another optional embodiment of this example, after obtaining the average maximum height and average minimum height corresponding to each local region, and before calculating the average height of the polished surface, the following may be included:

[0085] The height difference is obtained by calculating the difference between the average maximum height and the average minimum height within the same local area.

[0086] Determine if there are any local regions where the corresponding height difference is greater than a set difference threshold;

[0087] If so, the local region with the corresponding height difference greater than the set difference threshold will be segmented to obtain a new local region after segmentation;

[0088] For the newly divided local regions, re-predict the average maximum height and average minimum height until the area of ​​the local region is less than the set area threshold and / or the height difference between all local regions is not greater than the set difference threshold; then perform a weighted average of the average maximum height and average minimum height of each local region to obtain the average height of the polished surface of the local region.

[0089] This embodiment further considers that if the height undulation of the polished surface in the same local area is relatively large, the reliability of the average height of the polished surface in that local area will be relatively low. Therefore, this embodiment further performs a difference calculation between the average maximum height and the average minimum height in the same local area. Obviously, if the height difference in the local area is small, it means that the height undulation of the polished surface between different positions in the local area is not large, and the average height of a single polished surface in the local area can be used to represent the overall height position of the polished surface. Conversely, if the variance of the height difference in the local area is large, it means that the height undulation of the polished surface in the local area is large, and the local area can be further divided into smaller local areas. There are various specific division methods, such as average division, that is, dividing the rectangular local area in half; or, for example, dividing the area covered by the same material structural layer (for example, the polished surface in the second exposure of Figure 1 contains two different material structural layers) in the local area into the same new local area, and dividing the area covered by structural layers of different materials into different new local areas. In summary, the goal is to ensure that the height difference within the same local area does not exceed a set threshold, or that the area of ​​the local area is already too small, in which case no further subdivision is necessary.

[0090] It is understood that, in this embodiment, during the exposure simulation process, the exposure process should be simulated separately for each of the newly divided local regions. Therefore, the average height of the polished surface in each local region in this embodiment can more accurately represent the height position of the polished surface within that local region, and the exposure simulation process implemented by the simulation optical model corrected based on this average polished surface height is also more accurate and reliable.

[0091] Based on any of the above embodiments, the morphology prediction of the polished surface on the wafer to be processed in this application can be achieved based on a prediction model obtained by training a neural network; on this basis, the process of morphology prediction can further include:

[0092] S111: Determine whether the polished surface structure layer on the wafer to be processed is a single material structure layer; if yes, proceed to S112; if no, proceed to S113.

[0093] S112: Input the polishing process parameters, material parameters and the size parameters of the wafer to be processed into the first prediction model to obtain the polishing surface morphology information corresponding to the local area;

[0094] S113: Obtain the pattern information of each local area based on the design layout corresponding to the polished surface structure layer; input the pattern information, polishing process parameters, material parameters and the size parameters of the wafer to be processed into the second prediction model to obtain the polished surface morphology information corresponding to the local area;

[0095] Both the first and second prediction models were obtained in advance through neural network model training.

[0096] As shown in Figure 1, during the two exposure processes, the first exposure is performed on the same material structural layer, while the second exposure is performed on two different material structural layers. In actual grinding and polishing, the polished surface shape differs between structural layers of different materials and those of the same material. Therefore, in this embodiment, the surface shapes of the polished surfaces of the two different types of structural layers can be pre-trained to determine two different types of prediction models: a first prediction model and a second prediction model. Thus, during actual morphology prediction, different prediction models can be used according to the actual structural layer type, ensuring the accuracy and reliability of the predicted morphology information.

[0097] Furthermore, the first prediction model in this embodiment is mainly for the polished surface prediction model corresponding to a structural layer with only a single material (e.g., the first structural layer 2 corresponding to the first exposure in Figure 1), similar to the first exposure shown in Figure 1. In this case, the factors affecting the morphology of the polished surface include polishing process parameters, material parameters, and the size parameters of the wafer to be processed. Of course, if it is also necessary to consider the morphology of different local areas, the positional parameters of different local areas can also be used as one of the prediction input parameters. The polishing process parameters in this embodiment can refer to the area of ​​the polishing pad relative to the wafer to be processed, the magnitude of the pressure applied by the polishing pad to the polishing slurry, the rotational speed of the polishing pad and the wafer to be processed respectively, etc., during the grinding and polishing process; while the material parameters mainly include parameters related to the material structure and the rate at which the polishing slurry chemically reacts and corrodes the material.

[0098] The second prediction model in this embodiment is mainly for the polished surface prediction model corresponding to the exposure of structural layers with two or more materials, similar to the second exposure shown in Figure 1 (e.g., the structural layer formed by the first structural layer 2 and the second structural layer 5 in the second exposure in Figure 1). In this case, the factors affecting the polished surface morphology include not only the material parameters, polishing process parameters, and size parameters of the wafer to be processed for each structural layer, but also the positional parameters of each local region. Furthermore, it is necessary to further determine the design layout corresponding to the exposure process that formed the current polished surface structural layer before this exposure (e.g., the design layout corresponding to the first exposure in Figure 1). If the current polished surface structural layer is formed through multiple exposures and depositions, it is necessary to combine multiple design layouts to jointly determine the pattern information of each local region of the current polished surface. Based on this pattern information and the aforementioned parameters, the second prediction model is input for prediction.

[0099] Based on the above discussion, regardless of the number of types of parameters required for the prediction model in this embodiment, in practical applications, corresponding parameter samples and corresponding polished surface samples can be collected based on the required input parameters to train the corresponding neural network model, and finally a prediction model that can accurately predict the morphology of each local area can be obtained.

[0100] The optical proximity correction device for a mask pattern provided in the embodiments of the present invention will be described below. The optical proximity correction device for a mask pattern described below can be referred to in correspondence with the optical proximity correction method for a mask pattern described above.

[0101] Figure 3 is a structural block diagram of the optical proximity correction device for the mask image provided in an embodiment of the present invention. The optical proximity correction device for the mask image in Figure 3 may include:

[0102] The morphology prediction module 100 is used to predict the morphology of the polished surface of the wafer to be processed and obtain the morphology information of the polished surface.

[0103] The parameter correction module 200 is used to correct the focal plane parameters in the simulated optical model based on the polished surface morphology information.

[0104] The simulation correction module 300 is used to perform optical proximity correction on the initial mask pattern using the corrected simulation optical model to obtain the corrected mask image.

[0105] In an optional embodiment of this application, the topography prediction module 100 is used to divide the polished surface of the wafer to be processed into regions based on the single simulated exposure area that can be simulated by the simulated optical model in the optical proximity correction of the initial mask pattern, and to determine local regions; to perform topography prediction on each local region on the polished surface of the wafer to be processed, and to obtain polished surface topography information corresponding to each local region; and to determine the average height of the polished surface corresponding to each local region based on the polished surface topography information.

[0106] Accordingly, the parameter correction module 200 is specifically used to compensate and correct the focal plane parameters by using the average height of the polished surface in the local area as the focal plane compensation amount in the simulation optical model of the corresponding single simulation exposure area.

[0107] In one optional embodiment of this application, the topography prediction module 100 is specifically used to predict the height of each local area on the polished surface of the wafer to be processed, and obtain the average maximum height and average minimum height corresponding to each local area; and to perform a weighted average of the average maximum height and average minimum height of each local area to obtain the average height of the polished surface of the local area.

[0108] In an optional embodiment of this application, the topography prediction module 100 is further configured to perform a difference calculation between the average maximum height and the average minimum height within the same local area to obtain a height difference; determine whether there is a local area in each local area whose corresponding height difference is greater than a set difference threshold; if so, segment the local area whose corresponding height difference is greater than the set difference threshold to obtain a newly segmented local area; re-predict the average maximum height and average minimum height of the newly segmented local area until the area of ​​the newly segmented local area is less than a set area threshold and / or the height difference corresponding to all local areas is not greater than the set difference threshold; and then perform a weighted average of the average maximum height and average minimum height of each local area to obtain the average height of the polished surface of the local area.

[0109] In one optional embodiment of this application, the morphology prediction module 100 is specifically used to predict the morphology of each local area based on the material parameters and polishing process parameters corresponding to the polished surface structure layer of the wafer to be processed, using a prediction model pre-trained through neural network learning, and obtain polished surface morphology information.

[0110] In one optional embodiment of this application, the morphology prediction module 100 is specifically used to determine whether the polished surface structure layer on the wafer to be processed is a single material structure layer; if so, the polishing process parameters, material parameters, and size parameters of the wafer to be processed are input into the first prediction model to obtain the polished surface morphology information corresponding to the local area; if not, the pattern information of each local area is obtained according to the design layout corresponding to the polished surface structure layer; the pattern information, polishing process parameters, material parameters, and size parameters of the wafer to be processed are input into the second prediction model to obtain the polished surface morphology information corresponding to the local area; wherein, both the first prediction model and the second prediction model are obtained in advance through neural network model training.

[0111] The optical proximity correction device for the mask image in this embodiment is used to implement the aforementioned optical proximity correction method for the mask image. Therefore, the specific implementation of the optical proximity correction device for the mask image can be found in the embodiment section of the optical proximity correction method for the mask image above. The specific implementation can be referred to the description of the corresponding embodiments, and will not be repeated here.

[0112] This application also provides an embodiment of an optical proximity correction device for a mask image, which may include:

[0113] Memory, used to store computer programs;

[0114] A processor for executing the computer program to implement the steps of the optical proximity correction method for the mask image as described in any of the preceding claims.

[0115] The steps of the optical proximity correction method for the mask image executed by the processor may include:

[0116] The morphology of the polished surface of the wafer to be processed is predicted to obtain the morphology information of the polished surface; the focal plane parameters in the simulation optical model are corrected according to the morphology information of the polished surface; and the initial mask pattern is optically proximity corrected using the corrected simulation optical model to obtain the corrected mask image.

[0117] This application also provides a computer-readable storage medium storing a computer program that is executed to implement the steps of the optical proximity correction method for a mask image as described in any of the preceding claims.

[0118] The computer-readable storage medium may include 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.

[0119] 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.

[0120] 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 optical proximity correction of a mask image, characterized in that, include: The morphology of the polished surface of the wafer to be processed is predicted to obtain the morphology information of the polished surface; The focal plane parameters in the simulation optical model are corrected based on the polished surface morphology information; the corrected simulation optical model is then used to perform optical proximity correction on the initial mask pattern to obtain the corrected mask image. The method of predicting the morphology of the polished surface of the wafer to be processed to obtain polished surface morphology information includes: dividing the polished surface of the wafer to be processed into regions based on the single-simulation exposure area that the simulation optical model can simulate in a single operation during optical proximity correction of the initial mask pattern, and determining local regions; performing morphology prediction on each of the local regions on the polished surface of the wafer to be processed to obtain polished surface morphology information corresponding to each local region; determining the average height of the polished surface corresponding to each local region based on the polished surface morphology information; and correspondingly, correcting the focal plane parameters in the simulation optical model based on the polished surface morphology information, including: using the average height of the polished surface in the local region as the corresponding... The focal plane compensation amount in the simulation optical model of the single-exposure area is used to compensate and correct the focal plane parameters; morphology prediction is performed on each local region on the polished surface of the wafer to be processed to obtain polished surface morphology information corresponding to each local region, including: height prediction is performed on each local region on the polished surface of the wafer to be processed to obtain the average maximum height and average minimum height corresponding to each local region; accordingly, based on the polished surface morphology information, the average height of the polished surface corresponding to each local region is determined, including: weighted averaging of the average maximum height and average minimum height of each local region to obtain the average height of the polished surface of the local region.

2. The optical proximity correction method for a mask image as described in claim 1, characterized in that, After obtaining the average maximum height and average minimum height corresponding to each local region, the method further includes: performing a difference operation on the average maximum height and average minimum height within the same local region to obtain a height difference; determining whether there is a local region in each local region whose corresponding height difference is greater than a set difference threshold; if so, segmenting the local region whose corresponding height difference is greater than the set difference threshold to obtain a newly segmented local region; re-predicting the average maximum height and average minimum height for the newly segmented local region until the area of ​​the newly segmented local region is less than a set area threshold and / or the height difference corresponding to all local regions is not greater than the set difference threshold; and then performing a weighted average of the average maximum height and average minimum height of each local region to obtain the average height of the polished surface of the local region.

3. The optical proximity correction method for a mask image as described in claim 1 or 2, characterized in that, The morphology prediction of each local region on the polished surface of the wafer to be processed is performed to obtain the polished surface morphology information corresponding to each local region. This includes: based on the material parameters and polishing process parameters corresponding to the polished surface structure layer of the wafer to be processed, using a prediction model pre-trained through neural network learning, the morphology prediction of each local region is performed to obtain the polished surface morphology information.

4. The optical proximity correction method for mask images as described in claim 3, characterized in that, The morphology prediction is performed on each local region on the polished surface of the wafer to be processed to obtain the polished surface morphology information corresponding to each local region. This includes: determining whether the polished surface structure layer on the wafer to be processed is a single material structure layer; if so, the polishing process parameters, material parameters, and the size parameters of the wafer to be processed are input into a first prediction model to obtain the polished surface morphology information corresponding to the local region; if not, the pattern information of each local region is obtained according to the design layout corresponding to the polished surface structure layer; the pattern information, polishing process parameters, material parameters, and the size parameters of the wafer to be processed are input into a second prediction model to obtain the polished surface morphology information corresponding to the local region; wherein, both the first prediction model and the second prediction model are obtained in advance through neural network model training.

5. An optical proximity correction device for a mask pattern, characterized in that, include: The morphology prediction module is used to predict the morphology of the polished surface of the wafer to be processed and obtain the morphology information of the polished surface. The parameter correction module is used to correct the focal plane parameters in the simulated optical model based on the polished surface morphology information. The simulation correction module is used to perform optical proximity correction on the initial mask pattern using the corrected simulation optical model to obtain a corrected mask image. The morphology prediction module is used to divide the polished surface of the wafer to be processed into regions based on the single-time simulated exposure area that the simulation optical model can simulate in the initial mask pattern optical proximity correction, and to determine local regions. Morphology prediction is performed on each of the local regions on the polished surface of the wafer to be processed to obtain polished surface morphology information corresponding to each local region. Based on the polished surface morphology information, the average height of the polished surface corresponding to each local region is determined. Correspondingly, the parameter correction module is specifically used to use the average height of the polished surface of the local region as the focal plane compensation amount in the simulation optical model of the corresponding single-time simulated exposure area to compensate and correct the focal plane parameters. The morphology prediction module is specifically used to predict the height of each local region on the polished surface of the wafer to be processed to obtain the average maximum height and average minimum height corresponding to each local region. A weighted average of the average maximum height and average minimum height of each local region is calculated to obtain the average height of the polished surface of the local region.

6. An optical proximity correction device for a mask pattern, characterized in that, include: Memory, used to store computer programs; A processor for executing the computer program to implement the steps of the optical proximity correction method for a mask image as described in any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that is executed to implement the steps of the optical proximity correction method for a mask image as described in any one of claims 1 to 4.

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