Design method and design device of photoetching mask, storage medium and electronic equipment

Abstract

The invention discloses a photoetching mask design method and device, a storage medium and electronic equipment. The method comprises the following steps: determining a target type of a current photoetching mask; obtaining parameter information of a current photoetching mask, parameter information of a chip manufacturing process material and parameter information of operation of an exposure machine according to the target type; and determining target design parameters of the photoetching mask based on the parameter information of the photoetching mask, the parameter information of the chip process material and the working parameter information of the exposure machine. According to the design method provided by the invention, the exposure precision of the photoetching mask and the accuracy of process control can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of photolithography masks, and in particular to a method for designing a photolithography mask, a computer-readable storage medium, an electronic device, and a device for designing a photolithography mask. Background Art

[0002] In the semiconductor manufacturing process, photomasks are used in the mass production of downstream electronic components and are a key part of the downstream industry's production process connection. Photomasks will directly affect the quality of lithography.

[0003] In the current photolithography mask process control, process engineers will set some empirical parameters to control the photolithography process based on past experience and data, such as exposure dose, focus position and photoresist thickness, and determine the best process parameters through experiments and optimization to obtain the best exposure results. Although this method improves exposure accuracy and process control to a certain extent, they may not be able to fully compensate for the optical path error caused by changes in the thickness and quality of the mask body material, resulting in inaccurate process control, affecting the exposure results or poor exposure results. Summary of the invention

[0004] The present application aims to solve at least one of the technical problems in the related art to a certain extent. To this end, the first purpose of the present application is to propose a method for designing a photolithography mask, determine the target type of the current photolithography mask; obtain parameter information of the current photolithography mask, parameter information of the chip process material, and parameter information of the exposure machine according to the target type; determine the target design parameters of the photolithography mask based on the parameter information of the photolithography mask, the parameter information of the chip process material, and the parameter information of the exposure machine, thereby improving the exposure accuracy of the photolithography mask and the accuracy of process control.

[0005] A second object of the present application is to provide a computer-readable storage medium.

[0006] The third objective of the present application is to provide an electronic device.

[0007] The fourth objective of the present application is to provide a device for designing a photolithography mask.

[0008] To achieve the above-mentioned objectives, the first aspect of the present application proposes a method for designing a photolithography mask, the method comprising: determining a target type of a current photolithography mask; obtaining parameter information of the current photolithography mask, parameter information of a chip process material, and parameter information of an exposure machine according to the target type; and determining target design parameters of the photolithography mask based on the parameter information of the photolithography mask, the parameter information of the chip process material, and the parameter information of the exposure machine.

[0009] According to the design method of the photolithography mask of the embodiment of the present application, the target type of the current photolithography mask is determined, and the parameter information of the current photolithography mask, the parameter information of the chip process material, and the parameter information of the exposure machine are obtained according to the target type, and the target design parameters of the photolithography mask are determined based on the parameter information of the photolithography mask, the parameter information of the chip process material, and the parameter information of the exposure machine. Therefore, the method can improve the exposure accuracy of the photolithography mask and the accuracy of process control.

[0010] In addition, the method for designing a photolithography mask according to the above embodiment of the present application may also have the following additional technical features:

[0011] According to one embodiment of the present application, the parameter information of the photolithography mask includes thickness and flatness, the parameter information of the chip process material includes refractive index, extinction coefficient, graphic density of the pattern on the photolithography mask, and stacking thickness, and the parameter information of the exposure machine includes exposure conditions and operating temperature of the exposure machine. The target design parameters of the photolithography mask are determined based on the parameter information of the photolithography mask, the parameter information of the chip process material, and the parameter information of the exposure machine, including: determining the performance of the current photolithography mask under the parameter information of the photolithography mask, the parameter information of the chip process material, and the parameter information of the exposure machine based on a machine learning algorithm, wherein the performance includes: resolution and contrast, exposure uniformity, light absorption and transmittance, thermal stability, etching uniformity and selectivity, sidewall angle and shape, and at least one of pattern size and shape, durability and strength; based on the performance, the design parameters of the photolithography mask are adjusted to determine the target design parameters, wherein the design parameters include at least one of photoresist thickness, mold absorption layer and semi-transparent layer material thickness, etching parameters, and etching depth, and the corresponding adjustment relationship between the performance and the design parameters is: the resolution and contrast, exposure uniformity correspond to the photoresist thickness, the light absorption and transmittance, thermal stability correspond to the mold absorption layer and semi-transparent layer material thickness, the etching uniformity and selectivity, sidewall angle and shape correspond to the etching parameters, and the pattern size and shape, durability and strength correspond to the etching depth.

[0012] According to one embodiment of the present application, the method also includes: obtaining the photolithography mask process and processing parameter information and obtaining the photolithography mask post-process parameter information, wherein the photolithography mask process and processing parameter information include the type, temperature and concentration of the chemical solution, and the photolithography mask post-process parameter information includes the defect type and defect quantity; based on the photolithography mask process and processing parameter information and the photolithography mask post-process parameter information, the target design parameters of the photolithography mask are modified.

[0013] According to one embodiment of the present application, the target design parameters of the photolithography mask are modified based on the photolithography mask process and processing parameter information and the photolithography mask post-process parameter information, including: determining the performance of the current photolithography mask under the photolithography mask process and processing parameter information, the photolithography mask post-process parameter information and the target design parameters based on a machine learning algorithm; and modifying the target design parameters of the photolithography mask based on the performance.

[0014] According to an embodiment of the present application, the method further includes: adjusting the layout information of the integrated circuit based on the target design parameters.

[0015] According to an embodiment of the present application, the target type of photolithography mask includes: one of: a phase shift mask, a cutting mask and a multiple photolithography mask, and determining the target type of the current photolithography mask includes: determining the target type based on the design specifications and performance requirements of the chip.

[0016] According to an embodiment of the present application, the method further includes: pre-designing a pattern for the current photolithography mask; and verifying and checking a design specification based on the design pattern.

[0017] In order to achieve the above-mentioned purpose, a second embodiment of the present application proposes a computer-readable storage medium on which a program is stored, and when the program is executed by a processor, the above-mentioned method for designing a photolithography mask is implemented.

[0018] According to the computer-readable storage medium of the embodiment of the present application, by implementing the above-mentioned photolithography mask design method when executed, the exposure accuracy of the photolithography mask and the accuracy of process control can be improved.

[0019] To achieve the above-mentioned purpose, an electronic device proposed in the third aspect of the present application includes a memory, a processor, and a program stored in the memory and executable on the processor. When the processor executes the program, the above-mentioned photolithography mask design method is implemented.

[0020] According to the electronic device of the embodiment of the present application, by executing the above-mentioned method for designing a photolithography mask, the exposure accuracy of the photolithography mask and the accuracy of process control can be improved.

[0021] To achieve the above-mentioned objectives, the fourth aspect of the present application proposes a device for designing a photolithography mask, the device comprising: a first determination module, used to determine the target type of the current photolithography mask; an acquisition module, used to acquire parameter information of the current photolithography mask, parameter information of the chip process material, and parameter information of the exposure machine according to the target type; and a second determination module, used to determine the target design parameters of the photolithography mask based on the parameter information of the photolithography mask, the parameter information of the chip process material, and the parameter information of the exposure machine.

[0022] According to the photolithography mask design device of the embodiment of the present application, the first determination module is used to determine the target type of the current photolithography mask, the acquisition module is used to acquire the parameter information of the current photolithography mask, the parameter information of the chip process material, and the parameter information of the exposure machine according to the target type, and the second determination module is used to determine the target design parameters of the photolithography mask based on the parameter information of the photolithography mask, the parameter information of the chip process material, and the parameter information of the exposure machine. Thus, the device can improve the exposure accuracy of the photolithography mask and the accuracy of process control.

[0023] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 is a flow chart of a method for designing a photolithography mask according to an embodiment of the present application;

[0025] Figure 2 A flowchart of a method for designing a photolithography mask according to a specific example of the present application;

[0026] Figure 3 is a block diagram of an electronic device according to an embodiment of the present application;

[0027] Figure 4 Schematic diagram of a block diagram of a device for designing a photolithography mask according to an embodiment of the present application. DETAILED DESCRIPTION

[0028] Embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0029] The following describes a method for designing a photolithography mask, a computer-readable storage medium, an electronic device, and a device for designing a photolithography mask according to embodiments of the present application with reference to the accompanying drawings.

[0030] Figure 1 The figure is a flow chart of a method for designing a photolithography mask according to an embodiment of the present application.

[0031] like Figure 1 As shown, the method for designing a photolithography mask according to an embodiment of the present application may include the following steps:

[0032] S1, determine the target type of the current photolithography mask;

[0033] S2, obtaining parameter information of the current photolithography mask, parameter information of the chip process material, and parameter information of the exposure machine according to the target type;

[0034] S3, determining target design parameters of the photolithography mask based on parameter information of the photolithography mask, parameter information of chip process materials, and parameter information of the exposure machine operation.

[0035] Specifically, in the process of designing the photolithography mask, the target type of the current photolithography mask is first determined. Different types of photolithography masks can correspond to different design parameters, which can analyze the specific requirements of the integrated circuit (IC) design, including the required resolution, line width, alignment accuracy, interlayer alignment, etc. In addition, the current photolithography process capabilities are evaluated, such as the wavelength of the light source and the numerical aperture of the photolithography machine. According to the results of demand analysis and process evaluation, the appropriate mask type is selected, such as phase shift mask, cutting mask or multiple photolithography mask. For example, if a high-performance logic IC needs to be manufactured, the minimum line width is required to be 28 nanometers. After evaluation, it can be determined to use a phase shift mask to improve resolution and contrast.

[0036] After determining the target type of the current photolithography mask, the parameter information of the current photolithography mask, the parameter information of the chip process material, and the parameter information of the exposure machine can be obtained according to the target type. Among them, the parameter information of the current mask is collected, such as the characteristics and thickness of the mask material, the material of the absorption layer and the semi-transparent layer, etc. The parameter information of the chip process material is collected, such as the sensitivity of the photoresist, the chemical stability of the resist, etc. The parameter information of the exposure machine operation is collected, such as the wavelength of the light source, the exposure dose, the ambient temperature and humidity, etc.

[0037] After determining the parameter information of the photolithography mask, the parameter information of the chip process material, and the parameter information of the exposure machine, the target design parameters of the photolithography mask can be determined based on the parameter information of the photolithography mask, the parameter information of the chip process material, and the parameter information of the exposure machine. In other words, the target design parameters of the photolithography mask take into account the parameter information of the photolithography mask body, such as the thickness and quality data of the mask material, and incorporate them into the optical path calculation in the photolithography process. The optical path refers to the propagation path of light from the light source to the wafer, including the propagation in the mask material, which can more accurately calculate the propagation and phase change of light in the mask, thereby reducing the optical path error and improving the accuracy and consistency of the exposure pattern. The target design parameters of the photolithography mask also take into account the parameter information of the chip process material, such as the material properties and thickness of the oxide layer, photoresist, and polysilicon layer, which can be considered, and input into the artificial intelligence computing system for training the AI ​​model. The purpose of the training is to let the AI ​​learn how to predict the optimal photolithography mask design parameters based on these data. The trained AI system can provide precise control parameters, which are used to guide the manufacturing process of the photolithography mask to ensure that the mask can meet specific exposure requirements.

[0038] The target design parameters of the photolithography mask take into account the parameter information of the exposure machine. For example, the thermal stress that may be encountered during the manufacture and use of the photolithography mask can be simulated through an artificial intelligence computing system. Thermal stress is an internal stress caused by temperature changes, which may cause the mask material to deform. In the simulation process, the conditions of the actual exposure machine during the exposure process are added, including the power of the exposure light source, the exposure time, the type of light source (such as ultraviolet light, extreme ultraviolet light, etc.), and the operating temperature inside the exposure machine. The data obtained from the simulation is used to predict the possible impact of thermal stress on the mask shape and pattern, and pre-correction design is performed accordingly. Pre-correction design refers to adjusting the mask design according to the predicted deformation before the mask is manufactured to compensate for or reduce the deformation that may occur during the actual manufacturing and use process. In this way, the impact of thermal stress can be predicted and compensated before the mask is manufactured, thereby improving the accuracy and reliability of the mask, reducing errors and rework in the manufacturing process, and improving the overall performance of the photolithography process.

[0039] Therefore, the exposure precision of the photolithography mask and the accuracy of process control can be improved.

[0040] According to one embodiment of the present application, the parameter information of the photolithography mask includes thickness and flatness, the parameter information of the chip process material includes refractive index, extinction coefficient, graphic density of the pattern on the photolithography mask, and stacking thickness, and the parameter information of the exposure machine includes exposure conditions and operating temperature of the exposure machine. The target design parameters of the photolithography mask are determined based on the parameter information of the photolithography mask, the parameter information of the chip process material, and the parameter information of the exposure machine, including: determining the performance of the current photolithography mask under the parameter information of the photolithography mask, the parameter information of the chip process material, and the parameter information of the exposure machine based on a machine learning algorithm, wherein the performance includes: resolution and contrast, exposure uniformity, light absorption and transmittance, thermal stability, etching uniformity and selectivity, sidewall angle and shape, and at least one of pattern size and shape, durability and strength; adjusting the design parameters of the photolithography mask based on the performance to determine the target design parameters, wherein the design parameters include at least one of the photoresist thickness, the thickness of the mold absorption layer and the semi-transparent layer material, etching parameters, and etching depth, and the corresponding adjustment relationship between the performance and the design parameters is: resolution and contrast, exposure uniformity correspond to the photoresist thickness, light absorption and transmittance, thermal stability correspond to the thickness of the mold absorption layer and the semi-transparent layer material, etching uniformity and selectivity, sidewall angle and shape correspond to etching parameters, and pattern size and shape, durability and strength correspond to etching depth.

[0041] Specifically, the parameter information of the photolithography mask includes thickness and flatness. The thickness of the mask material affects the absorption and transmittance of light, and thus affects the quality and resolution of the exposure pattern. The flatness of the mask surface has an important influence on the exposure uniformity and resolution. The parameter information of the chip process material includes the refractive index, extinction coefficient, the pattern density of the pattern on the photolithography mask, and the stacking thickness. The refractive index of the material affects the propagation path and phase change of light in the material, and has an impact on the alignment and focusing of the exposure pattern. The extinction coefficient affects the attenuation of light in the material and is related to the exposure dose and the sensitivity of the photoresist. The density of the pattern affects the optical proximity effect during the photolithography process. The thickness of different material layers affects the interlayer alignment and the stability of the overall structure. The parameter information of the exposure machine includes the exposure conditions and operating temperature of the exposure machine. The exposure conditions include the wavelength of the light source, the exposure dose, the exposure time, etc., which directly affect the exposure effect of the photoresist. The operating temperature affects the sensitivity of the photoresist and the physical properties of the mask material, such as thermal expansion.

[0042] Therefore, when determining the target design parameters of the photolithography mask based on the above information, a machine learning algorithm can be used to analyze the above parameter information to predict the performance of the photolithography mask under specific conditions. For example, predict the performance of resolution and contrast (whether the photolithography mask can clearly transfer the pattern to the photoresist). Predict the performance of exposure uniformity (the consistency of exposure across the wafer). Predict the performance of light absorption and transmittance (the ability of the mask material to absorb and transmit light). Predict the performance of thermal stability (the performance stability of the photolithography mask at different temperatures). Predict the performance of etching uniformity and selectivity (the uniformity of the pattern and the selectivity of the material during etching). Predict the performance of sidewall angle and shape (the angle and shape of the sidewall of the pattern after etching), pattern size and shape (the size and shape of the pattern transferred to the wafer), durability and strength (the durability and mechanical strength of the mask material).

[0043] According to the performance predicted by the machine learning algorithm, the following design parameters are adjusted based on the performance: Photoresist thickness, adjusted to improve resolution and contrast, exposure uniformity. Mode absorption layer and semi-transparent layer material thickness, adjusted to improve light absorption and transmittance, thermal stability. Etching parameters, adjusted to improve etching uniformity and selectivity, sidewall angle and shape, etching depth, adjusted to control pattern size and shape, durability and strength. For example, resolution and contrast, exposure uniformity correspond to photoresist thickness, that is, increasing the photoresist thickness can improve contrast, but may reduce resolution, and the best balance needs to be found. Light absorption and transmittance, thermal stability correspond to the thickness of the mode absorption layer and semi-transparent layer material, that is, adjusting the thickness of these layers can improve light absorption and transmittance, as well as the thermal stability of the mask. Etching uniformity and selectivity, sidewall angle and shape correspond to etching parameters, that is, adjusting etching parameters such as etching time and etching solution concentration can improve etching uniformity and sidewall shape. Pattern size and shape, durability and strength correspond to etching depth, that is, etching depth directly affects the size and shape of the pattern, as well as the durability and strength of the mask.

[0044] Therefore, the design of the photolithography mask can be systematically optimized in many aspects to adapt to specific manufacturing conditions and improve the accuracy and yield of the photolithography process.

[0045] According to one embodiment of the present application, the design method of the photolithography mask also includes: obtaining photolithography mask process and processing parameter information and obtaining photolithography mask post-process parameter information, wherein the photolithography mask process and processing parameter information includes the type, temperature and concentration of the chemical solution, and the photolithography mask post-process parameter information includes the defect type and defect quantity; based on the photolithography mask process and processing parameter information and the photolithography mask post-process parameter information, the target design parameters of the photolithography mask are modified.

[0046] Specifically, in the process of manufacturing photolithography masks, various chemical solutions are also required for cleaning, etching or other treatments. The type, temperature and concentration of these chemical solutions are important parameters that directly affect the treatment effect and the quality of the mask. For example, the chemical solution used to etch the chromium layer may require a specific temperature and concentration to ensure the etching rate and uniformity. In addition, after the mask is manufactured and processed, it is necessary to check the defects on the mask, such as pinholes, scratches or pattern defects. Understanding the type and number of defects is crucial to evaluating the quality of the mask and determining whether further corrections are needed. Thus, the photolithography mask process and processing parameter information and the post-photolithography mask process parameter information can be obtained to correct the target design parameters of the photolithography mask according to the photolithography mask process and processing parameter information and the post-photolithography mask process parameter information.

[0047] For example, if it is found that the number of defects on the mask increases after treatment with a certain chemical solution, the concentration of the solution or the processing time may need to be adjusted. By adjusting the temperature and concentration of the chemical solution, or changing the etching and cleaning steps, defects can be reduced and the quality and yield of the mask can be improved. In addition, correcting the design parameters can also help improve the accuracy of the photolithography mask during the exposure process, ensuring that the pattern can be accurately transferred to the wafer.

[0048] For another example, suppose that during the photolithography mask manufacturing process, it is found that after using a certain concentration of etching solution, the number of pinhole defects on the mask exceeds the acceptable range. Therefore, the concentration of the etching solution can be reduced or increased to reduce the pinhole defects, and the processing temperature can be increased or decreased to optimize the etching rate and uniformity. Through these corrections, the photolithography mask manufacturing process can be optimized, defects can be reduced, the quality of the mask and the exposure accuracy can be improved, and ultimately the yield and performance of the integrated circuit can be improved.

[0049] According to one embodiment of the present application, the target design parameters of the lithography mask are modified based on the lithography mask process and processing parameter information and the lithography mask post-process parameter information, including: determining the performance of the current lithography mask under the lithography mask process and processing parameter information, the lithography mask post-process parameter information and the target design parameters based on a machine learning algorithm; and modifying the target design parameters of the lithography mask based on the performance.

[0050] Specifically, in order to achieve the best lithography effect, the performance of the current lithography mask under the lithography mask process and processing parameter information, lithography mask post-process parameter information and target design parameters can be determined according to the machine learning algorithm, so as to modify the target design parameters of the lithography mask according to the performance.

[0051] For example, a mixed solution of sulfuric acid and hydrogen peroxide is used for cleaning, the temperature of the chemical treatment is, for example, 40 degrees Celsius, and the concentration of the chemical solution is, for example, 10% sulfuric acid. Pinholes and scratches are found on the mask, such as 5 pinholes and 2 scratches. Under the target design parameters, such as the thickness of the photoresist is 1 micron, the thickness of the mold absorption layer and the semi-transparent layer material is 0.5 microns, and the etching parameters are: etching time 30 seconds, etching solution concentration 15%, and engraving depth 0.3 microns. Therefore, a machine learning algorithm can be used to predict the performance of the photolithography mask based on the above parameter information. The performance may include: resolution and contrast, exposure uniformity, light absorption and transmittance, thermal stability, etching uniformity and selectivity, sidewall angle and shape, pattern size and shape, durability and strength. Assume that the performance predicted by the machine learning algorithm is as follows: resolution and contrast do not meet expectations, exposure is uneven, light absorption and transmittance are below standard, and etching uniformity and selectivity are not ideal. Based on these predictions, the target design parameters can be modified as follows: For example, the photoresist thickness is increased to 1.2 microns to improve contrast and exposure uniformity, and the thickness of the mold absorption layer and semi-transparent layer is adjusted to 0.6 microns to improve light absorption and transmittance. The etching parameters are increased by increasing the etching time to 45 seconds and the etching solution concentration to 20% to improve etching uniformity and selectivity. The etching depth is adjusted to 0.4 microns to improve the sidewall angle and shape.

[0052] The mask can be re-manufactured with the new photoresist thickness and the mold absorption layer thickness, and the concentration of the chemical solution and the etching parameters can be adjusted. After the manufacturing is completed, check whether the number of defects has been reduced and whether the performance has met expectations. In addition, if the performance still does not meet expectations, the machine learning algorithm will make predictions and corrections again based on the new parameter information and performance until the optimal photolithography mask design parameters are found. In this way, the design of the photolithography mask can be comprehensively and systematically optimized to adapt to specific manufacturing conditions and improve the accuracy and yield of the photolithography process.

[0053] According to an embodiment of the present application, the method for designing a photolithography mask further includes: adjusting the layout information of the integrated circuit based on the target design parameters.

[0054] Specifically, when determining the target design parameters, the layout information of the integrated circuit is also adjusted according to the target design parameters. For example, the layout can be optimized based on the EDA (Electronic Design Automation) tool to adapt to the target design parameters such as the thickness of the photoresist, the thickness of the mold absorption layer and the semi-transparent layer material. The layout design can also be iteratively updated according to the results of manufacturing feedback and design verification to optimize performance and yield. Finally, the adjusted layout information is extracted and converted into a format suitable for manufacturing, such as a GDSII (Graphic Design System II) file. This file is a widely used file format for describing layout information in the field of integrated circuit (IC) design and manufacturing. The GDSII file contains detailed geometric data of the layout, including layer information, shape, pattern, and the connection relationship between them. This format allows designers and manufacturers to share and transfer layout data at different design and manufacturing stages.

[0055] According to an embodiment of the present application, the target type of the photolithography mask includes: one of: a phase shift mask, a cutting mask and a multiple photolithography mask, and determining the target type of the current photolithography mask includes: determining the target type based on the design specifications and performance requirements of the chip.

[0056] Specifically, the target type of photolithography mask may include one of a phase shift mask, a cutting mask, and a multiple photolithography mask. Among them, the phase shift mask uses the phase difference of light waves to enhance or weaken the interference effect of light, thereby improving the photolithography resolution. The cutting mask is a mask used to adjust the exposure amount of a specific area. It locally reduces the exposure amount by adding additional opaque areas on the mask, thereby achieving fine-tuning of the pattern edge. Multiple photolithography masks are a technology that builds complex three-dimensional structures through multiple exposure and development steps, allowing denser patterns to be created on the same layer without increasing the resolution of the photolithography machine.

[0057] When determining the target type of the current photolithography mask, the target type can be determined based on the design specifications and performance requirements of the chip. For example, during chip design, for the manufacture of high-density integrated circuits, such as advanced logic circuits and high-performance memories, where a single exposure step cannot achieve the required pattern density, the type of the current photolithography mask can be determined to be a multiple photolithography mask. For another example, during chip design, for dense pattern areas, such as the manufacture of logic circuits and memory circuits, the type of the current photolithography mask can be determined to be a phase shift mask to improve resolution and contrast. For another example, during chip design, for the case of adjusting the exposure amount of a specific area, the type of the current photolithography mask can be determined to be a cutting mask, which can improve the uniformity and accuracy of the pattern.

[0058] According to an embodiment of the present application, the method for designing a photolithography mask further includes: pre-designing a pattern for the current photolithography mask; and verifying and checking a design specification based on the design pattern.

[0059] Specifically, in the design method of the photolithography mask, the two key steps are to pre-design the current photolithography mask and verify and check the design specifications based on the design drawings, which can ensure that the mask design meets the manufacturing requirements and can accurately transfer the pattern to the wafer. That is to say, before the photolithography mask is manufactured, the design engineer can create a detailed design drawing according to the requirements of the circuit design. This drawing contains all the patterns that need to be formed on the wafer, such as transistors, wiring, contact holes, etc., and the design drawing needs to accurately define the size, shape and position of each pattern. The size of these patterns meets the limitations of the photolithography process and meets the requirements of circuit performance. After the design drawing is determined, a series of checks can be performed on the design drawing to ensure that all patterns meet the design rules of the manufacturing process. These rules may include line width, line spacing, contact hole size, etc.

[0060] Combine the following Figure 2 To describe the control method of the present application.

[0061] As a specific example, the method for designing a photolithography mask of the present application may include the following steps:

[0062] S101, determine the photolithography mask target type based on the chip design specifications and performance requirements.

[0063] S102, designing a pattern for the current photolithography mask in advance.

[0064] S103, verifying and checking the design specifications based on the design drawings.

[0065] S104, obtaining parameter information of the current photolithography mask, parameter information of the chip process material, and operating environment information of the exposure machine according to the target type.

[0066] S105, determining the performance of the current photolithography mask under the photolithography mask parameter information, chip process material parameter information and exposure machine working environment information based on the machine learning algorithm.

[0067] S106, adjusting design parameters of the photolithography mask based on the performance to determine target design parameters.

[0068] S107, obtaining photolithography mask process and processing parameter information and obtaining photolithography mask process post-parameter information.

[0069] S108, modifying the target design parameters of the photolithography mask based on the photolithography mask process and processing parameter information and the photolithography mask post-process parameter information.

[0070] In summary, according to the design method of the photolithography mask of the embodiment of the present application, the target type of the current photolithography mask is determined, and the parameter information of the current photolithography mask, the parameter information of the chip process material, and the parameter information of the exposure machine are obtained according to the target type, and the target design parameters of the photolithography mask are determined based on the parameter information of the photolithography mask, the parameter information of the chip process material, and the parameter information of the exposure machine. Therefore, the method can improve the exposure accuracy of the photolithography mask and the accuracy of process control.

[0071] Corresponding to the above embodiments, the present application also proposes a computer-readable storage medium.

[0072] The computer-readable storage medium of the embodiment of the present application stores a program thereon, and when the program is executed by a processor, the above-mentioned method for designing a photolithography mask is implemented.

[0073] According to the computer-readable storage medium of the embodiment of the present application, by executing the above-mentioned method for designing a photolithography mask, the exposure accuracy of the photolithography mask and the accuracy of process control can be improved.

[0074] Corresponding to the above embodiment, the present application also proposes an electronic device.

[0075] like Figure 3 As shown, the electronic device 200 of the embodiment of the present application may include: a memory 210, a processor 220, and a program stored in the memory 210 and executable on the processor 220. When the processor 220 executes the program, the above-mentioned photolithography mask design method is implemented.

[0076] According to the electronic device of the embodiment of the present application, by executing the above-mentioned method for designing a photolithography mask, the exposure accuracy of the photolithography mask and the accuracy of process control can be improved.

[0077] Corresponding to the above embodiments, the present application also proposes a photolithography mask design device.

[0078] like Figure 4 As shown, the device 100 for designing a photolithography mask according to an embodiment of the present application includes: a first determination module 110 , an acquisition module 120 , and a second determination module 130 .

[0079] The first determination module 110 is used to determine the target type of the current photolithography mask. The acquisition module 120 is used to acquire parameter information of the current photolithography mask, parameter information of the chip process material, and parameter information of the exposure machine according to the target type. The second determination module 130 is used to determine the target design parameters of the photolithography mask based on the parameter information of the photolithography mask, the parameter information of the chip process material, and the parameter information of the exposure machine.

[0080] According to one embodiment of the present application, the parameter information of the photolithography mask includes thickness and flatness, the parameter information of the chip process material includes refractive index, extinction coefficient, graphic density of the pattern on the photolithography mask, and stacking thickness, and the parameter information of the exposure machine includes exposure conditions and operating temperature of the exposure machine. The second determination module 130 determines the target design parameters of the photolithography mask based on the parameter information of the photolithography mask, the parameter information of the chip process material, and the parameter information of the exposure machine, and is specifically used to: determine the performance of the current photolithography mask under the parameter information of the photolithography mask, the parameter information of the chip process material, and the parameter information of the exposure machine based on a machine learning algorithm, wherein the performance includes: resolution and contrast, exposure uniformity, light absorption and At least one of transmittance, thermal stability, etching uniformity and selectivity, sidewall angle and shape, and pattern size and shape, durability and strength; adjusting the design parameters of the photolithography mask based on the performance to determine the target design parameters, wherein the design parameters include at least one of the photoresist thickness, the thickness of the mold absorption layer and the semi-transparent layer material, etching parameters, and etching depth, and the corresponding adjustment relationship between the performance and the design parameters is: resolution and contrast, exposure uniformity correspond to the photoresist thickness, light absorption and transmittance, thermal stability correspond to the thickness of the mold absorption layer and the semi-transparent layer material, etching uniformity and selectivity, sidewall angle and shape correspond to etching parameters, and pattern size and shape, durability and strength correspond to etching depth.

[0081] According to one embodiment of the present application, the acquisition module 120 is also used to: obtain photolithography mask process and processing parameter information and obtain photolithography mask post-process parameter information, wherein the photolithography mask process and processing parameter information includes the type, temperature and concentration of the chemical solution, and the post-photolithography mask process parameter information includes the defect type and defect quantity; based on the photolithography mask process and processing parameter information and the post-photolithography mask process parameter information, the target design parameters of the photolithography mask are modified.

[0082] According to one embodiment of the present application, the second determination module 130 modifies the target design parameters of the lithography mask based on the lithography mask process and processing parameter information and the lithography mask post-process parameter information, and is specifically used to: determine the performance of the current lithography mask under the lithography mask process and processing parameter information, the lithography mask post-process parameter information and the target design parameters based on a machine learning algorithm; and modify the target design parameters of the lithography mask based on the performance.

[0083] According to an embodiment of the present application, the second determination module 130 is further configured to: adjust the layout information of the integrated circuit based on the target design parameters.

[0084] According to one embodiment of the present application, the target type of photolithography mask includes: one of: a phase shift mask, a cutting mask and a multiple photolithography mask. The first determination module 110 determines the target type of the current photolithography mask, specifically for: determining the target type based on the design specifications and performance requirements of the chip.

[0085] According to an embodiment of the present application, the first determination module 110 is further used to: pre-design a pattern for the current photolithography mask; and verify and check the design specification based on the design pattern.

[0086] It should be noted that for details not disclosed in the device for designing the photolithography mask of the embodiment of the present application, please refer to the details disclosed in the method for designing the photolithography mask of the embodiment of the present application, and the details will not be repeated here.

[0087] According to the photolithography mask design device of the embodiment of the present application, the first determination module is used to determine the target type of the current photolithography mask, the acquisition module is used to acquire the parameter information of the current photolithography mask, the parameter information of the chip process material, and the parameter information of the exposure machine according to the target type, and the second determination module is used to determine the target design parameters of the photolithography mask based on the parameter information of the photolithography mask, the parameter information of the chip process material, and the parameter information of the exposure machine. Thus, the device can improve the exposure accuracy of the photolithography mask and the accuracy of process control.

[0088] It should be noted that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection portion with one or more wirings (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways if necessary, and then stored in a computer memory.

[0089] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0090] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0091] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of this application, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0092] In this application, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements, unless otherwise clearly defined. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0093] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in the field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A method for designing a photolithography mask, characterized in that: The method comprises: Determine the target type of the current photolithography mask; Acquire parameter information of the current photolithography mask, parameter information of chip process materials, and parameter information of exposure machine operation according to the target type; The target design parameters of the photolithography mask are determined based on the parameter information of the photolithography mask, the parameter information of the chip process material and the parameter information of the exposure machine operation.

2. The method for designing a photolithography mask according to claim 1, characterized in that: The parameter information of the photolithography mask includes thickness and flatness, the parameter information of the chip process material includes refractive index, extinction coefficient, pattern density of the pattern on the photolithography mask, and stacking thickness, the parameter information of the exposure machine operation includes exposure conditions and operating temperature of the exposure machine, and the target design parameters of the photolithography mask are determined based on the parameter information of the photolithography mask, the parameter information of the chip process material, and the parameter information of the exposure machine operation, including: Determine, based on a machine learning algorithm, the performance of the current photolithography mask under the photolithography mask parameter information, the chip process material parameter information, and the exposure machine operating parameter information, wherein the performance includes: resolution and contrast, exposure uniformity, light absorption and transmittance, thermal stability, etching uniformity and selectivity, sidewall angle and shape, and pattern size and shape, durability and strength; Based on the performance, the design parameters of the photolithography mask are adjusted to determine the target design parameters, wherein the design parameters include at least one of the photoresist thickness, the thickness of the mold absorption layer and the semi-transparent layer material, the etching parameters, and the etching depth, and the corresponding adjustment relationship between the performance and the design parameters is: the resolution and contrast, and the exposure uniformity correspond to the photoresist thickness, the light absorption and transmittance, and the thermal stability correspond to the thickness of the mold absorption layer and the semi-transparent layer material, the etching uniformity and selectivity, the sidewall angle and shape correspond to the etching parameters, and the pattern size and shape, durability, and strength correspond to the etching depth.

3. The method for designing a photolithography mask according to claim 2, characterized in that: The method further comprises: Acquiring the photolithography mask process and processing parameter information and acquiring the photolithography mask process post-parameter information, wherein the photolithography mask process and processing parameter information includes the type, temperature and concentration of the chemical solution, and the photolithography mask process post-parameter information includes the defect type and defect quantity; The target design parameters of the photolithography mask are modified based on the photolithography mask process and processing parameter information and the photolithography mask post-process parameter information.

4. The method for designing a photolithography mask according to claim 3, characterized in that: The step of modifying the target design parameters of the photolithography mask based on the photolithography mask process and processing parameter information and the photolithography mask post-process parameter information includes: Determine, based on a machine learning algorithm, the performance of the current photolithography mask under the photolithography mask process and processing parameter information, the photolithography mask post-process parameter information, and target design parameters; Target design parameters of the photolithography mask are modified based on the performance.

5. The method for designing a photolithography mask according to any one of claims 1 to 4, characterized in that: The method further comprises: The layout information of the integrated circuit is adjusted based on the target design parameters.

6. The method for designing a photolithography mask according to any one of claims 1 to 4, characterized in that: The target type of the photolithography mask includes: one of a phase shift mask, a cutting mask and a multiple photolithography mask, and the step of determining the target type of the current photolithography mask includes: The target type is determined based on the design specifications and performance requirements of the chip.

7. The method for designing a photolithography mask according to any one of claims 1 to 4, characterized in that: The method further comprises: Designing a pattern for the current photolithography mask in advance; Verification and inspection are performed based on the design specifications of the design drawings.

8. A computer-readable storage medium, characterized in that: A program is stored thereon, and when the program is executed by a processor, the method for designing a photolithography mask according to any one of claims 1 to 7 is implemented.

9. An electronic device, characterized in that: include: A memory, a processor, and a program stored in the memory and executable on the processor, wherein when the processor executes the program, the method for designing a photolithography mask according to any one of claims 1 to 7 is implemented.

10. A photolithography mask design device, characterized in that: The device comprises: A first determination module is used to determine the target type of the current photolithography mask; An acquisition module, used to acquire parameter information of the current photolithography mask, parameter information of chip process materials, and parameter information of exposure machine operation according to the target type; The second determination module is used to determine the target design parameters of the photolithography mask based on the parameter information of the photolithography mask, the parameter information of the chip process material and the parameter information of the exposure machine operation.

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