Photomask correction methods, apparatus, equipment and media

Abstract

This application relates to the field of semiconductor manufacturing technology, specifically to a photomask correction method, apparatus, device, and medium. The photomask correction method includes: obtaining a test layout with known parameters; training an initial optical proximity effect correction model based on the known parameters until both the cost evaluation function and the root mean square value are minimized, thus obtaining an optical correction model; obtaining photochemical reaction parameters of the test layout, training the optical correction model based on the photochemical reaction parameters until both the cost evaluation function and the root mean square value are minimized, thus obtaining a target layout correction model; inputting the initial layout into the target layout correction model to obtain a corrected layout, and obtaining a target photomask based on the corrected layout, which at least ensures that the photomask pattern after exposure is consistent with the target pattern actually desired by the user.

Description

Technical Field

[0001] This application relates to the field of semiconductor manufacturing technology, and in particular to a photomask correction method, apparatus, device and medium. Background Technology

[0002] The optical proximity effect (OPE) is a critical issue in semiconductor manufacturing, especially in photolithography. As the feature size of integrated circuits continues to shrink (down to the nanometer scale), diffraction and interference phenomena of light cause deviations between the image of the pattern on the photoresist and the actual design pattern. This phenomenon is called the optical proximity effect.

[0003] In semiconductor manufacturing, optical proximity (OPE) can cause pattern distortion. For example, dense lines or contact holes may merge (bridge) or break due to light diffraction, leading to short circuits or open circuits in the device. OPE can also cause changes in critical dimensions of the pattern after exposure, affecting device performance and yield. Summary of the Invention

[0004] Therefore, it is necessary to address the problems mentioned above by providing a method that can avoid the adverse effects of parameter errors such as optical errors and photochemical reactions on the exposed photomask pattern, and at least ensure that the exposed photomask pattern is consistent with the target pattern that the user actually wants to obtain.

[0005] To achieve the above and other objectives, according to various embodiments of this application, one aspect of this application provides a photomask correction method, comprising:

[0006] Obtain a test layout with known parameters, including pattern parameters, photoluminescence parameters, and film parameters, including the number of layers, film material, film thickness, and photoresist parameters.

[0007] The initial optical proximity effect correction model is trained based on known parameters until the cost evaluation function and root mean square value are minimized, thus obtaining the optical correction model.

[0008] The photochemical reaction parameters of the test pattern are obtained, including the reaction rate and diffusion rate in the dense and sparse regions of the pattern, as well as the reaction rate and diffusion rate of photoacids and photobases in the tangential and normal directions.

[0009] The optical correction model is trained based on photochemical reaction parameters until the cost evaluation function and root mean square value are minimized, thus obtaining the target layout correction model.

[0010] The initial layout is input into the target layout correction model to obtain the corrected layout, and the target photomask is obtained based on the corrected layout.

[0011] In the photomask correction method described in the above embodiments, a test pattern with known parameters is first obtained. These parameters include pattern parameters, yellow light parameters, and film layer parameters. The film layer parameters include the number of layers, film material, film thickness, and photoresist parameters. Then, an initial optical proximity effect correction model is trained using the test pattern and its known parameters until both the cost evaluation function and the root mean square value are minimized. This optical correction model is capable of correcting for the optical proximity effect, avoiding adverse effects from optical errors and other optical factors on the pre-exposure pattern. Furthermore, optical factors have a high impact on the final post-exposure pattern error, sometimes exceeding 80%. Therefore, establishing an optical correction model that can at least avoid the optical proximity effect can significantly shorten the model training time. Then, the optical correction model is trained using the photochemical reaction parameters of the test pattern to obtain a target pattern correction model. This target pattern correction model can compensate for errors caused by photochemical reaction parameters, ensuring that the post-exposure photomask pattern matches the user's desired target pattern.

[0012] In some embodiments, the test layout includes multiple periodically distributed sub-patterns; obtaining the optical correction model includes: taking known parameters as input and the target parameters of the multiple sub-patterns in the post-exposure layout as output, training an initial optical proximity effect correction model until the cost evaluation function and the root mean square value are minimized, thus obtaining the optical correction model. This facilitates obtaining a test layout based on a block of known parameters through periodic repetition of that block, thereby reducing the complexity and cost of obtaining a test layout with known parameters and ensuring the accuracy of the known parameters obtained for the test layout.

[0013] In some embodiments, the target parameters of the multiple sub-patterns in the post-exposure layout include: the coordinate information of the center point coordinates of the multiple sub-patterns in the post-exposure layout.

[0014] In some embodiments, the yellow light parameters include illumination system parameters.

[0015] In some embodiments, the graphic parameters include at least one of the following: graphic point coordinates, shape of sub-graphics, spacing, and line width.

[0016] In some embodiments, the multiple sub-patterns include grid patterns or conductive contact patterns.

[0017] In some embodiments, the photochemical reaction parameters further include: a function of the effect of baking on the critical dimensions of the exposed layout.

[0018] In some embodiments, a function describing the effect of the development rate on the critical dimensions of the exposed layout is used.

[0019] One embodiment of this disclosure also discloses a photomask correction device, including a test pattern acquisition module, an optical correction model acquisition module, a photochemical reaction parameter acquisition module, a target pattern correction model acquisition module, and a target photomask acquisition module. The test pattern acquisition module is used to acquire a test pattern with known parameters, including pattern parameters, yellow light parameters, and film parameters. The film parameters include the number of layers, film material, film thickness, and photoresist parameters. The optical correction model acquisition module is used to train an initial optical proximity effect correction model based on the known parameters until the cost evaluation function and the root mean square value are minimized. The optical correction model is obtained through a photochemical reaction parameter acquisition module. This module acquires the photochemical reaction parameters of the test layout, including the reaction rate and diffusion rate in dense and sparse regions of the pattern, as well as the reaction rate and diffusion rate of photoacids and photobases in the tangential and normal directions. The target layout correction model acquisition module trains the optical correction model based on the photochemical reaction parameters until the cost evaluation function and root mean square value are minimized, thus obtaining the target layout correction model. The target photomask acquisition module inputs the initial layout into the target layout correction model to obtain the corrected layout, and then uses the corrected layout to obtain the target photomask.

[0020] In some embodiments, the photochemical reaction parameters further include: a function of the effect of baking on the critical dimensions of the exposed layout.

[0021] In some embodiments, a function describing the effect of the development rate on the critical dimensions of the exposed layout is used.

[0022] In some embodiments, a photomask correction device is provided, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps of any photomask correction method in the embodiments of this application.

[0023] In some embodiments, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps of any photomask correction method in the embodiments of this application.

[0024] In some embodiments, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps of any of the photomask correction methods described above.

[0025] The unexpected technical effects that can be produced by the embodiments of this application include:

[0026] An initial optical proximity effect correction model is trained using the test pattern and its known parameters until both the cost evaluation function and the root mean square value are minimized. This results in an optical correction model capable of correcting for the optical proximity effect, avoiding the adverse effects of optical errors and other optical factors on the pre-exposure pattern. Furthermore, optical factors have a significant impact on the final post-exposure pattern error, sometimes exceeding 80%. Therefore, establishing an optical correction model that can at least avoid the optical proximity effect first shortens the model training time. Then, the optical correction model is trained using the photochemical reaction parameters of the test pattern to obtain a target pattern correction model. This target pattern correction model can compensate for errors caused by photochemical reaction parameters, ensuring that the post-exposure photomask pattern matches the user's desired target pattern. Attached Figure Description

[0027] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0028] Figure 1 This is a schematic flowchart of a photomask correction method provided in one embodiment of this application;

[0029] Figure 2 This is a schematic diagram of the structure of a test layout provided in one embodiment of this application;

[0030] Figure 3 This is a schematic diagram of training an initial optical proximity effect correction model in one embodiment of this application;

[0031] Figure 4 This is a schematic diagram of training an optical correction model in one embodiment of this application;

[0032] Figure 5 This is a schematic diagram of the layout at different stages during the process of modifying a test layout including a grid pattern in one embodiment of this application;

[0033] Figure 6 This is a schematic diagram comparing the correction time required by the photomask correction method in one embodiment of this application to correct a test layout including a grating pattern, with the correction time required by the conventional method to correct a test layout including a grating pattern.

[0034] Figure 7 This is a schematic diagram of the layout at different stages during the process of modifying a test layout including a target contact pattern in one embodiment of this application;

[0035] Figure 8This is a schematic diagram comparing the correction time required by the photomask correction method in one embodiment of this application to correct a test pattern including a target contact pattern, with the correction time required by the conventional method to correct a test pattern including a target contact pattern.

[0036] Figure 9 This is a schematic diagram of a photomask correction device provided in one embodiment of this application.

[0037] Explanation of reference numerals in the attached figures:

[0038] 1000. Photomask correction device; 101. Test pattern acquisition module; 102. Optical correction model acquisition module; 103. Photochemical reaction parameter acquisition module; 104. Target pattern correction model acquisition module; 105. Target photomask acquisition module; 100. Central sub-pattern; 200. Repeating sub-pattern; 20. Target grid pattern; 21. Grid pattern after exposure; 30. Target contact pattern; 31. Contact pattern after exposure. Detailed Implementation

[0039] To facilitate understanding of this application, a more complete description will be provided below with reference to the accompanying drawings. Preferred embodiments of this application are shown in the drawings. However, this application can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of the disclosure of this application.

[0040] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein in the specification of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application.

[0041] When using the terms “including,” “having,” and “comprising” as described herein, another component may be added unless explicitly qualifying terms such as “only,” “consisting of,” etc. are used. Unless otherwise stated, singular terms may include plural forms and should not be construed as having a quantity of one.

[0042] In this application, unless otherwise expressly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0043] Furthermore, the terms “first”, “second”, etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated.

[0044] In the process of manufacturing semiconductor chips, photomasks are used to form patterns on semiconductors using photolithography. To replicate these patterns onto a wafer, an integrated circuit photolithography machine is used to photoetch the projected circuitry. The manufacturing process generally includes: exposure, development, removal of photoresist, and photolithography. The general process of photolithography is as follows: first, a specific pattern structure is obtained on a photomask; then, the pattern on the photomask is replicated onto the silicon wafer using photolithography equipment. However, the process of creating patterns through photolithography introduces some degree of distortion, especially as linewidths decrease, the distortion becomes increasingly severe. Typical examples include corner rounding and line end shortening. These phenomena are caused by the Optical Proximity Effect (OPE), which is caused by the nonlinear filtering of the optical imaging system. The industry has addressed these issues using Optical Proximity Correction (OPC) technology. In OPC, the pattern on the integrated circuit mask is pre-corrected to compensate for the distortion caused by the photolithography process, so that the corrected pattern can obtain the pre-designed pattern structure after photolithography.

[0045] However, photochemical reactions play a crucial role in the photoresist exposure process, and improper control can lead to various pattern defects. Even patterns corrected for optical proximity are still adversely affected by photochemical reaction parameters during exposure and development. For example, insufficient photoacid generation results in residual colloids or blurred pattern edges after development; lateral diffusion of photoacid leads to line edge roughness (LER) or poor linewidth uniformity; aromatic compounds in the photoresist oxidize to carboxylic acids under UV light, altering the pH of the developer; and metallic impurities (such as Na and K) in the photoresist migrate to the silicon wafer surface after exposure. Therefore, purely optical correction models cannot resolve the adverse effects of photochemical reaction parameters on the exposed pattern.

[0046] Therefore, the embodiments of this application aim to provide a photomask correction method, apparatus, device and medium, which can at least avoid the adverse effects of parameter errors such as optical errors and photochemical reactions on the exposed photomask pattern, and ensure that the exposed photomask pattern is consistent with the target pattern that the user actually wants to obtain.

[0047] The photomask correction method, apparatus, device, and medium provided in this application embodiment can be applied to a lithography machine processor. The lithography machine processor communicates with a server via a network, and the server communicates with a server receiver. The lithography machine processor can also communicate directly with the server receiver. The communication connection can be wired or wireless.

[0048] For example, the photomask correction method, apparatus, equipment, and medium are applied to the lithography machine processor. The lithography machine processor can obtain a test layout with known parameters from the server's receiving end. The known parameters include pattern parameters, photoluminescence parameters, and film layer parameters. The film layer parameters include the number of layers, film layer material, film layer thickness, and photoresist parameters. The lithography machine processor trains an initial optical proximity effect correction model based on the known parameters until the cost evaluation function and root mean square value are minimized, thus obtaining the optical correction model. The lithography machine processor can obtain the photochemical reaction parameters of the test layout from the server's receiving end. The photochemical reaction parameters include the reaction rate and diffusion rate in the dense and sparse regions of the pattern, as well as the reaction rate and diffusion rate of photoacids and photobases in the tangential and normal directions. The lithography machine processor trains the optical correction model based on the photochemical reaction parameters until the cost evaluation function and root mean square value are minimized, thus obtaining the target layout correction model. The lithography machine processor inputs the initial layout into the target layout correction model to obtain the corrected layout, which facilitates the subsequent generation of the target photomask based on the corrected layout.

[0049] For example, the photomask correction method, apparatus, equipment, and medium are applied to a server. The server obtains a test layout with known parameters from a server receiver. These known parameters include pattern parameters, optical parameters, and film parameters. The film parameters include the number of layers, film material, film thickness, and photoresist parameters. The server trains an initial optical proximity effect correction model based on the known parameters until the cost evaluation function and root mean square value are minimized, thus obtaining the optical correction model. The server can obtain the photochemical reaction parameters of the test layout from the server receiver. These photochemical reaction parameters include the reaction rate and diffusion rate in dense and sparse regions of the pattern, as well as the reaction rate and diffusion rate of photoacids and photobases in the tangential and normal directions. The server trains the optical correction model based on the photochemical reaction parameters until the cost evaluation function and root mean square value are minimized, thus obtaining the target layout correction model. The server inputs the initial layout into the target layout correction model to obtain the corrected layout, which facilitates the subsequent generation of the target photomask based on the corrected layout.

[0050] like Figure 1 As shown, in some embodiments, a photomask correction method is provided, including the following steps:

[0051] Step S12: Obtain the test layout with known parameters, including pattern parameters, photoluminescence parameters, and film parameters. Film parameters include the number of layers, film material, film thickness, and photoresist parameters.

[0052] Step S14: Train the initial optical proximity effect correction model based on the known parameters until the cost evaluation function and the root mean square value are both minimized, and obtain the optical correction model;

[0053] Step S15: Obtain the photochemical reaction parameters of the test pattern. The photochemical reaction parameters include: the reaction rate and diffusion rate in the dense and sparse regions of the pattern, as well as the reaction rate and diffusion rate of photoacids and photobases in the tangential and normal directions.

[0054] Step S16: Train the optical correction model based on the photochemical reaction parameters until the cost evaluation function and the root mean square value are minimized, and obtain the target layout correction model;

[0055] Step S18: Input the initial layout into the target layout correction model to obtain the corrected layout, and obtain the target photomask based on the corrected layout.

[0056] Specifically, a test pattern with known parameters is first obtained, including pattern parameters, yellow light parameters, and film layer parameters. Film layer parameters include the number of layers, film material, film thickness, and photoresist parameters. Then, an initial optical proximity effect correction model is trained using the test pattern and its known parameters until the cost evaluation function and root mean square value are minimized, resulting in an optical correction model. This model can correct for the optical proximity effect, avoiding the adverse effects of optical errors and other optical factors on the pre-exposure pattern. Furthermore, optical factors have a high impact on the final post-exposure pattern error, sometimes exceeding 80%. Therefore, establishing an optical correction model that can at least avoid the optical proximity effect can significantly shorten the model training time. Then, the optical correction model is trained using the photochemical reaction parameters of the test pattern to obtain a target pattern correction model. This target pattern correction model can compensate for errors caused by photochemical reaction parameters, ensuring that the post-exposure photomask pattern matches the user's desired target pattern.

[0057] like Figure 2 As shown, in some embodiments, a central sub-pattern 100 with known parameters can be used as the center of the test layout. Then, repeating sub-patterns 200 are determined with the central sub-pattern 100 as the center and distributed in a mirror symmetric manner. The pattern parameters, photoluminescence parameters, and film layer parameters of the repeating sub-patterns 200 are known. Thus, through simple mirroring, a test layout with accurately known parameters can be obtained. The known parameters include pattern parameters, photoluminescence parameters, and film layer parameters. The film layer parameters include the number of layers, film layer material, film layer thickness, and photoresist parameters.

[0058] In some embodiments, based on a block unit with known parameters, a test layout is obtained by periodically repeating the block unit, thereby reducing the complexity and cost of obtaining a test layout with known parameters and ensuring the accuracy of the known parameters of the test layout.

[0059] In some embodiments, the test pattern includes multiple test points with known coordinate values, which facilitates the determination of change parameters such as offset, expansion, and shrinkage of the exposed pattern based on the coordinate information of the multiple test points in the exposed pattern.

[0060] For example, please continue to refer to Figure 2 Based on the coordinates (x1, y1) of the first test point and the coordinates (x2, y2) of the second test point in the central sub-figure 100, the line width and center coordinates of the central sub-figure 100 can be calculated. After obtaining the target parameters of multiple sub-figures in the post-exposure layout, including the coordinate information of the center point coordinates of multiple sub-figures in the post-exposure layout, the offset, expansion, and shrinkage of the post-exposure figure can be determined based on the coordinate values ​​in the test layout and the coordinate information in the post-exposure layout. This helps to determine whether the post-exposure photomask pattern matches the target figure that the user actually wants to obtain.

[0061] In some embodiments, the test pattern includes multiple periodically distributed sub-patterns; obtaining the optical correction model includes: taking known parameters as input, taking the target parameters of the multiple sub-patterns in the post-exposure pattern as output, training an initial optical proximity effect correction model until the cost evaluation function and the root mean square value are both minimized, and obtaining the optical correction model.

[0062] In some embodiments, the yellow light parameters include illumination system parameters. For example, yellow safety lamps typically use sodium lamps or LEDs with wavelengths between 550nm and 600nm (avoiding photoresist-sensitive bands, such as the 365nm i-line, 248nm KrF, and 193nm ArF). The illumination intensity needs to be controlled to less than 1 lux to avoid accidental exposure of the photoresist. The light source parameters for lithography machine exposure include light source type, numerical aperture (NA), coherence factor (σ), and dose.

[0063] In some embodiments, photoresist-related parameters include sensitivity wavelength and contrast. Yellow light must be avoided (e.g., positive / negative photoresists are sensitive to UV or EUV, but do not react to light above 550nm). Contrast reflects the exposure response characteristics of the photoresist.

[0064] In some embodiments, the shape of the sub-graphics in the test layout includes at least one of a circle, a polygon, a crescent shape, a sector shape, and a ring.

[0065] In some embodiments, the subpattern in the test layout includes a pad oxide layer, a silicon nitride layer, a silicon oxide layer, an α-carbon layer, an anti-reflection layer, and a photoresist layer sequentially stacked along the direction away from the substrate. The thickness of the pad oxide layer is 20-25 angstroms, for example, it can be 20 angstroms, 22 angstroms, or 25 angstroms; the extinction coefficient of the pad oxide layer can be 1.5711, and its refractive index is approximately 0. The thickness of the silicon nitride layer is 300-400 angstroms, for example, it can be 300 angstroms, 350 angstroms, 380 angstroms, or 400 angstroms; the extinction coefficient of the silicon nitride layer can be 2.62165, and its refractive index is approximately 0.38843. The thickness of the silicon oxide layer is 220-230 angstroms, for example, it can be 220 angstroms, 225 angstroms, or 230 angstroms; the extinction coefficient of the silicon oxide layer can be 1.563, and its refractive index is approximately 0. The thickness of the α-carbon layer is 1900 Å to 2000 Å, for example, the thickness of the α-carbon layer can be 1900 Å, 1950 Å, or 2000 Å, etc.; the extinction coefficient of the α-carbon layer can be 1.5165, and the refractive index is approximately 0.6935. The thickness of the anti-reflective layer is 320 Å to 350 Å, for example, the thickness of the anti-reflective layer can be 320 Å, 330 Å, or 350 Å, etc.; the extinction coefficient of the anti-reflective layer can be 1.88, and the refractive index is approximately 0.46. The thickness of the photoresist layer is 980 Å to 1020 Å, for example, the thickness of the photoresist layer can be 980 Å, 1000 Å, or 1020 Å, etc.; the extinction coefficient of the photoresist layer can be 1.7, and the refractive index is approximately 0.049.

[0066] In some embodiments, the graphic parameters include at least one of the following: graphic point coordinates, shape of sub-graphics, spacing, and line width.

[0067] Please continue to refer to this. Figure 2 In some embodiments, the line width of the central sub-graphic 100 can be calculated based on the coordinates (x1, y1) of the first test point and the coordinates (x2, y2) of the second test point in the central sub-graphic 100.

[0068] Please refer to Figure 3 In some embodiments, in step S12, after obtaining the test layout with known parameters, the known parameters include pattern parameters, yellow light parameters, and film parameters. The film parameters include the number of layers, film material, film thickness, and photoresist parameters. In step S14, an initial optical proximity effect correction model is trained using the test layout and its known parameters until the cost evaluation function and root mean square value are minimized, thus obtaining the optical correction model. Since the pure optical model training converges quickly, and the optical proximity effect can be well corrected using pattern parameters, yellow light parameters, and film parameters, establishing an optical correction model that can at least avoid the optical proximity effect can shorten the model training time.

[0069] Please refer to Figure 4 In some embodiments, in step S15, after obtaining the photochemical reaction parameters of the test layout, the photochemical reaction parameters include: the reaction rate and diffusion rate in the dense and sparse regions of the pattern, as well as the reaction rate and diffusion rate of photoacids and photobases in the tangential and normal directions; in step S16, an optical correction model is trained based on the photochemical reaction parameters until the cost evaluation function and the root mean square value are minimized, thereby obtaining the target layout correction model.

[0070] Please refer to Figure 5 In some embodiments, Figure 5 Figure (1) shows a test layout including multiple target grid patterns 20. The pattern parameters, light parameters and film parameters of the multiple target grid patterns 20 are known. The film parameters include the number of stacks, film material, film thickness and photoresist parameters. Figure 5 Figure (2) shows the pure optically corrected figure obtained after inputting the figure in Figure (1) and its known parameters into the optical correction model for correction. Figure 5 Figure (3) shows the corrected layout obtained after inputting the graphic and its known parameters from Figure (2) into the target layout correction model for correction. Figure 5 Figure (4) shows the exposed grid pattern 21 on the target photomask obtained based on the modified layout in Figure (3). By comparing the target grid pattern 20 and the exposed grid pattern 21 in Figure (4), it is found that graphic defects such as broken stripes or bridging are effectively avoided, and the key dimensions of the target grid pattern 20 and the exposed grid pattern 21 are basically consistent, which meets the expected requirements.

[0071] Please refer to Figure 6 , Figure 6 The green line illustrates the distribution of correction time for each of the following test layouts (DB1, DB2, DB3, DB4, and DB5), which include a grid pattern (1G). Each layout was corrected using the target layout correction model in this embodiment until the contour error was less than or equal to 0.1 nm. The known parameters of the first test layout (DB1), second test layout (DB2), third test layout (DB3), fourth test layout (DB4), and fifth test layout (DB5) are different. Figure 6 The red line illustrates the distribution of correction time for the first test pattern DB1, the second test pattern DB2, the third test pattern DB3, the fourth test pattern DB4, and the fifth test pattern DB5, which include a grid pattern (1G), respectively, using conventional photomask pattern correction methods to correct the contour error to less than or equal to 0.1nm. By comparing the green and red lines, it can be found that the photomask correction method in this embodiment reduces the pattern correction time by 17% while ensuring that the pattern correction accuracy is not reduced.

[0072] Please refer to Figure 7 In some embodiments, Figure 7 Figure (1) shows a test layout including multiple target contact patterns 30. The pattern parameters, photoluminescence parameters and film parameters of the multiple target contact patterns 30 are known. The film parameters include the number of stacks, film material, film thickness and photoresist parameters. Figure 7 The middle (2) diagram shows that Figure 7 The graph in Figure (1) and its known parameters are input into the optical correction model for correction, resulting in a purely optically corrected graph. Figure 7 The middle (3) diagram shows that Figure 7 The corrected layout is obtained by inputting the graphic and its known parameters into the target layout correction model in Figure (2). Figure 7 The diagram in Figure (4) is based on... Figure 7 The corrected layout in Figure (3) yields the contact pattern 31 on the target photomask after exposure. Through comparison... Figure 7 In Figure (4), the target contact pattern 30 and the exposed contact pattern 31 are shown. It is found that the key dimensions of the target contact pattern 30 and the exposed contact pattern 31 are basically the same, which meets the expected requirements.

[0073] Please refer to Figure 8 , Figure 8 The green line illustrates the distribution of correction time for each of the following test layouts (DB1, DB2, DB3, DB4, and DB5), which include contact patterns (1C), using the target layout correction model in this embodiment to correct the contour error to less than or equal to 0.1 nm. The known parameters of the first test layout (DB1), second test layout (DB2), third test layout (DB3), fourth test layout (DB4), and fifth test layout (DB5) are different. Figure 8 The red line illustrates the distribution of correction time for the first test pattern DB1, the second test pattern DB2, the third test pattern DB3, the fourth test pattern DB4, and the fifth test pattern DB5, which include a grid pattern (1G), respectively, using conventional photomask pattern correction methods to correct the contour error to less than or equal to 0.01nm. By comparing the green and red lines, it can be found that the photomask correction method in this embodiment reduces the pattern correction time by 20% while ensuring that the pattern correction accuracy is not reduced.

[0074] In some embodiments, the photochemical reaction parameters further include a function of the effect of baking on the critical dimension (CD) of the post-exposure pattern. Post-exposure baking (PEB) is a critical step in photolithography, especially in chemically amplified resist (CAR) systems, where it significantly affects the CD of the post-exposure pattern. After exposure, the photoacid-generating agent in the photoresist produces acid. During baking, the acid diffuses within the photoresist, catalyzing the deprotection reaction. The diffusion length is related to baking temperature and time. Increased temperature accelerates acid diffusion and reaction rates, leading to a smaller (positive resist) or larger (negative resist) CD, but excessively high temperatures may cause over-diffusion, resulting in rough pattern edges. Extending the baking time has a similar effect to increasing temperature, but with a saturation effect (continuing baking after the reaction is complete has no significant effect). Exposure dose can synergistically affect baking. At high exposure doses, the sensitivity of baking to the CD decreases (because the acid concentration is already saturated).

[0075] In some embodiments, the influence of development rate on the critical dimension (CD) of the pattern after exposure is described as a function. Development rate is one of the core parameters in photolithography that determines the morphology and critical dimension (CD) of the pattern after exposure. Development rate is closely related to the solubility characteristics of the photoresist, exposure dose, baking conditions, etc., and its functional relationship directly affects the resolution, sidewall morphology, and CD uniformity of the pattern. Development rate saturates with increasing dose (exhibiting a non-linear relationship). High-dose areas have fast development rates, while low-dose areas have slow development rates. Dense patterns may have lower development rates than isolated patterns due to limited developer penetration, leading to CD differences.

[0076] The impact of development rate on critical dimensions is a dynamic equilibrium process. In the embodiments of this application, the development parameters, photoresist characteristics, and synergistic effects with other process steps (exposure, baking) are precisely controlled by the target layout correction model to achieve high-fidelity transfer of the pattern.

[0077] It should be understood that, although Figure 1 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order in which these steps are executed, and they can be performed in other orders. Figure 1At least some of the steps in the process may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but may be executed at different times. The execution order of these steps or stages is not necessarily sequential, but may be executed in turn or alternately with other steps or at least some of the steps or stages in other steps.

[0078] like Figure 9 As shown, in some embodiments, a photomask correction device 1000 is provided, including a test pattern acquisition module 101, an optical correction model acquisition module 102, a photochemical reaction parameter acquisition module 103, a target pattern correction model acquisition module 104, and a target photomask acquisition module 105. The test pattern acquisition module 101 is used to acquire a test pattern with known parameters, including pattern parameters, yellow light parameters, and film parameters. The film parameters include the number of layers, film material, film thickness, and photoresist parameters. The optical correction model acquisition module 102 is used to train an initial optical proximity effect correction model based on the known parameters, and then to the cost evaluation function and... The optical correction model is obtained by minimizing the root mean square value. The photochemical reaction parameter acquisition module 103 is used to acquire the photochemical reaction parameters of the test pattern, including the reaction rate and diffusion rate in the dense and sparse regions of the pattern, as well as the reaction rate and diffusion rate of photoacids and photobases in the tangential and normal directions. The target pattern correction model acquisition module 104 is used to train the optical correction model based on the photochemical reaction parameters until the cost evaluation function and the root mean square value are minimized, thus obtaining the target pattern correction model. The target photomask acquisition module 105 is used to input the initial pattern into the target pattern correction model to obtain the corrected pattern, and then obtain the target photomask based on the corrected pattern.

[0079] In some embodiments, the photochemical reaction parameters further include: a function of the effect of baking on the critical dimensions of the exposed layout.

[0080] In some embodiments, a function describing the effect of the development rate on the critical dimensions of the exposed layout is used.

[0081] In some embodiments, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps of any photomask correction method in the embodiments of this application.

[0082] In some embodiments, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps of any photomask correction method in the embodiments of this application.

[0083] In some embodiments, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps of any of the photomask correction methods described above.

[0084] The unexpected technical effect of this application is that by training an initial optical proximity effect correction model using a test pattern and its known parameters until both the cost evaluation function and the root mean square value are minimized, an optical correction model is obtained. This optical correction model can correct for the optical proximity effect, avoiding the adverse effects of optical errors and other optical factors on the pre-exposure pattern. Furthermore, optical factors have a high proportion of influence on the final post-exposure pattern error, sometimes exceeding 80%. Therefore, establishing an optical correction model that can at least avoid the optical proximity effect can significantly shorten the model training time. Then, the optical correction model is trained using the photochemical reaction parameters of the test pattern to obtain a target pattern correction model. This target pattern correction model can compensate for errors caused by the photochemical reaction parameters, ensuring that the post-exposure photomask pattern matches the user's desired target pattern.

[0085] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include non-volatile, volatile, or combinations thereof. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), or graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application can include relational databases, non-relational databases, or combinations thereof. Non-relational databases can include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application can be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, or quantum computing-based data processing logic devices, etc., and are not limited to these.

[0086] Please note that the above embodiments are for illustrative purposes only and do not imply any limitation on this application.

[0087] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0088] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0089] The embodiments described above are merely examples of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these modifications and improvements all fall within the protection scope of this application.

Claims

1. A method for photomask correction, characterized in that, include: Obtain a test layout with known parameters, wherein the test layout includes multiple sub-patterns that are periodically distributed by periodically repeating the block with known parameters. The known parameters include pattern parameters, yellow light parameters, and film layer parameters. The film layer parameters include the number of layers, film material, film thickness, and photoresist parameters. The yellow light parameters include yellow light wavelength, light intensity, and light source parameters of the lithography machine. Using the known parameters as input and the coordinate information of the center point coordinates of the multiple sub-graphics in the exposed layout as output, the initial optical proximity effect correction model is trained until the cost evaluation function and the root mean square value are minimized, thus obtaining an optical correction model used to avoid the optical proximity effect and shorten the model training time. The photochemical reaction parameters of the test pattern are obtained, including the reaction rate and diffusion rate in the dense and sparse regions of the pattern, as well as the reaction rate and diffusion rate of photoacids and photobases in the tangential and normal directions. The optical correction model is trained based on the photochemical reaction parameters until the cost evaluation function and root mean square value are minimized, thus obtaining the target layout correction model used to compensate for the graphic deformation caused by the anisotropy of the photochemical reaction. The initial layout is input into the target layout correction model to obtain a corrected layout with a contour error of less than or equal to 0.1 nm, and a target photomask is obtained based on the corrected layout.

2. The photomask correction method according to claim 1, characterized in that, The graphic parameters include at least one of the following: graphic point coordinates, sub-graphic shape, spacing, and line width.

3. The photomask correction method according to claim 1, characterized in that, The multiple sub-patterns include grid patterns or conductive contact patterns.

4. The photomask correction method according to any one of claims 1-3, characterized in that, The photochemical reaction parameters also include: a function of the effect of baking on the critical dimensions of the exposed pattern, and / or a function describing the effect of the development rate on the critical dimensions of the exposed pattern.

5. The photomask correction method according to any one of claims 1-3, characterized in that, The light source parameters exposed by the lithography machine include light source type, numerical aperture, coherence factor, and dose.

6. The photomask correction method according to any one of claims 1-3, characterized in that, The shape of the sub-graphics in the test version includes at least one of the following: circle, polygon, crescent, sector, and ring.

7. A photomask correction device, characterized in that, include: The test pattern acquisition module is used to acquire a test pattern with known parameters. The test pattern includes multiple periodically distributed sub-patterns obtained by periodically repeating blocks with known parameters. The known parameters include pattern parameters, light emission parameters, and film layer parameters. The film layer parameters include the number of layers, film material, film thickness, and photoresist parameters. The light emission parameters include light emission wavelength, light intensity, and light source parameters of the lithography machine. The optical correction model acquisition module is used to take the known parameters as input, output the coordinate information of the center point coordinates of the multiple sub-graphics in the exposed layout, train the initial optical proximity effect correction model until the cost evaluation function and root mean square value are minimized, and obtain the optical correction model used to avoid the optical proximity effect and shorten the model training time. The photochemical reaction parameter acquisition module is used to acquire the photochemical reaction parameters of the test pattern. The photochemical reaction parameters include: the reaction rate and diffusion rate in the dense and sparse regions of the pattern, as well as the reaction rate and diffusion rate of photoacids and photobases in the tangential and normal directions. The target layout correction model acquisition module is used to train the optical correction model based on the photochemical reaction parameters until the cost evaluation function and root mean square value are minimized, thereby obtaining the target layout correction model used to compensate for the graphic deformation caused by the anisotropy of photochemical reaction. The target photomask acquisition module is used to input the initial layout into the target layout correction model to obtain a corrected layout with a contour error of less than or equal to 0.1 nm, so as to obtain the target photomask based on the corrected layout.

8. The photomask correction device according to claim 7, characterized in that, The photochemical reaction parameters also include: a function of the effect of baking on the critical dimensions of the exposed pattern, and / or a function describing the effect of the development rate on the critical dimensions of the exposed pattern.

9. A photomask correction device, comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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