Method, device, equipment, medium and product for generating design pattern of mask plate

Abstract

The application discloses a mask design pattern generation method, device, equipment, medium and product. The generation method comprises the following steps: obtaining a to-be-optimized layout of a mask; the to-be-optimized layout comprises a first pattern and a second pattern; the first pattern is a main design pattern in the to-be-optimized layout; and the second pattern is a plurality of sub-resolution auxiliary patterns generated based on the main design pattern; inputting the first pattern and the second pattern into a preset pattern processing model; performing pattern processing on the first pattern and the second pattern based on the pattern processing model; and obtaining a design pattern of the mask, wherein the pattern processing comprises at least one of the following: pattern moving, pattern reducing, pattern enlarging, pattern rotating, pattern combining, pattern deleting, pattern edge processing and pattern deforming, and the efficiency of processing the pattern of the mask can be improved.

Description

Technical Field

[0001] This application belongs to the field of graphics processing technology, and in particular relates to a method, apparatus, device, medium and product for generating design graphics of a mask. Background Technology

[0002] Optical photomasks are structures created by precisely positioning various functional patterns on thin film, plastic, or glass substrates for selective exposure of photoresist coatings. Therefore, photomasks have a wide range of applications, especially in the field of photolithography. Consequently, the design pattern of a photomask is particularly important. Currently, generating the design pattern often requires pattern processing of the pattern to be optimized. However, existing technologies rely on manual pattern processing, resulting in low efficiency and a simplistic processing method. Summary of the Invention

[0003] This application provides a method, apparatus, device, medium, and product for generating design graphics of a mask, which can improve efficiency in processing mask graphics.

[0004] In a first aspect, embodiments of this application provide a method for generating a design graphic of a mask, comprising:

[0005] Obtain the layout to be optimized from the mask. The layout to be optimized includes a first graphic and a second graphic. The first graphic is the main design graphic in the layout to be optimized, and the second graphic is a number of sub-resolution auxiliary graphics generated based on the main design graphic.

[0006] The first and second graphics are input into a preset graphics processing model. Based on the graphics processing model, the first and second graphics are processed to obtain the design graphics of the mask. The graphics processing includes at least one of the following: graphics movement, graphics shrinking, graphics enlargement, graphics rotation, graphics combination, graphics deletion, graphics edge processing, and graphics deformation.

[0007] Secondly, embodiments of this application provide an apparatus for generating a design graphic of a mask, comprising:

[0008] The acquisition module is used to acquire the layout to be optimized of the mask. The layout to be optimized includes a first graphic and a second graphic. The first graphic is the main design graphic in the layout to be optimized, and the second graphic is a number of sub-resolution auxiliary graphics generated based on the main design graphic.

[0009] The processing module is used to input the first graphic and the second graphic into a preset graphic processing model, and perform graphic processing on the first graphic and the second graphic based on the graphic processing model to obtain the design graphic of the mask. The graphic processing includes at least one of the following: graphic movement, graphic shrinking, graphic enlargement, graphic rotation, graphic combination, graphic deletion, graphic edge processing, and graphic deformation.

[0010] Thirdly, embodiments of this application provide an electronic device, the device comprising:

[0011] Processor and memory storing computer program instructions;

[0012] The method for generating the design drawing of the mask used by the processor to execute the first aspect above when executing computer program instructions.

[0013] Fourthly, embodiments of this application provide a computer storage medium storing computer program instructions, which, when executed by a processor, implement the method for generating the design pattern of the mask described in the first aspect.

[0014] Fifthly, embodiments of this application provide a computer program product, including a computer program that, when processed by a processor, implements the method for generating a mask design pattern as described in the first aspect.

[0015] The mask design graphic generation method, apparatus, device, medium, and product provided in this application embodiment perform graphic processing on the main design graphic and sub-resolution auxiliary graphic in the layout to be optimized simultaneously through a graphic processing model, which can improve graphic processing efficiency. Furthermore, the above-mentioned graphic processing covers a variety of processes such as graphic movement, graphic shrinking, graphic enlargement, graphic rotation, graphic combination, graphic deletion, and graphic edge processing, which can process graphics from multiple aspects and improve the collaborative optimization and accuracy of graphic processing. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a flowchart illustrating a method for generating a mask design graphic according to some embodiments of this application.

[0018] Figure 2 This is a schematic diagram of an exemplary mask layout to be optimized.

[0019] Figure 3This is a flowchart illustrating another method for generating a mask design graphic, provided for some embodiments of this application.

[0020] Figure 4 This is a flowchart illustrating another method for generating a mask design graphic, provided in some embodiments of this application.

[0021] Figure 5 This is a flowchart illustrating another method for generating a mask design graphic, provided in some embodiments of this application.

[0022] Figure 6 This is a schematic diagram of an apparatus for generating a design graphic of a mask, provided for some embodiments of this application.

[0023] Figure 7 This is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0024] The features and exemplary embodiments of various aspects of this application will be described in detail below. To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain this application and not to limit it. For those skilled in the art, this application can be implemented without some of these specific details. The following description of the embodiments is merely to provide a better understanding of this application by illustrating examples.

[0025] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes the element.

[0026] Before describing the technical solutions provided in the embodiments of this application, in order to facilitate understanding of the embodiments of this application, this application first specifically explains the problems existing in the related technologies:

[0027] Generating a mask design pattern typically involves two steps. The first step is to generate a sub-resolution auxiliary pattern based on the master design pattern using inverse lithography technology (ILT), resulting in a mask design pattern that includes both the master design pattern and the sub-resolution auxiliary pattern. The second step is to perform image processing on the mask design pattern, such as optical proximity correction (OPC) processing. However, currently, this image processing relies on manual intervention, leading to low processing efficiency.

[0028] Based on this, embodiments of this application provide a method, apparatus, device, medium, and product for generating design graphics of a mask, which can solve the above-mentioned problems.

[0029] The following is a detailed description of a method for generating a mask design graphic according to an embodiment of this application.

[0030] In some embodiments, such as Figure 1 As shown, this application embodiment provides a method for generating a design graphic of a mask, the method including the following steps S110-S120:

[0031] S110: Obtain the layout to be optimized from the mask. The layout to be optimized includes a first graphic and a second graphic. The first graphic is the main design graphic in the layout to be optimized, and the second graphic is a number of sub-resolution auxiliary graphics generated based on the main design graphic.

[0032] Here, you can obtain, such as Figure 2 The mask layout to be optimized is shown below. Figure 2 This is a schematic diagram of an exemplary mask layout to be optimized, such as... Figure 2 The mask layout to be optimized as shown above includes a first graphic 201, which is the main design graphic of the mask; and a second graphic 202, which is a sub-resolution auxiliary graphic of the mask, which is a plurality of sub-resolution auxiliary graphics generated based on the first graphic, such as... Figure 2 As shown, the second graphic may include multiple second graphics, which are distributed around the first graphic.

[0033] S120: Input the first graphic and the second graphic into a preset graphic processing model, and perform graphic processing on the first graphic and the second graphic based on the graphic processing model to obtain the design graphic of the mask. The graphic processing includes at least one of the following: graphic movement, graphic shrinking, graphic enlargement, graphic rotation, graphic combination, graphic deletion, graphic edge processing, and graphic deformation.

[0034] The layout to be optimized, including the first and second graphics mentioned above, can be input into a preset graphics processing model. Graphical processing can be performed on the first and second graphics based on the graphics processing model to obtain the design graphics of the mask. OPC processing can be performed on the first and second graphics using the graphics processing model. Here, the steps of processing the first and second graphics using the graphics processing model include at least one of the following: graphics movement, graphics reduction, graphics enlargement, graphics rotation, graphics combination, graphics deletion, graphics edge processing, and graphics deformation.

[0035] In some examples, edge processing can be performed on the first or second graphic, such as performing an edge breaking operation on the first graphic to obtain the target line segment and moving the target line segment to the target position.

[0036] In some examples, the first and / or second graphics can be moved, shrunk, enlarged, rotated, combined, deleted, or deformed. For example, the first graphic can be translated to change the distance between the first and second graphics, the first and / or second graphics can be enlarged or shrunk to change the size of the first graphic, a part or the whole of the first graphic can be deleted, multiple first graphics can be merged into one first graphic, and the shape of the first graphic can be changed. Similarly, the second graphic can be subjected to similar operations.

[0037] This application embodiment uses a graphics processing model to simultaneously process the main design graphics and sub-resolution auxiliary graphics in the layout to be optimized, which can improve graphics processing efficiency. Furthermore, the above-mentioned graphics processing covers a variety of processes such as graphics movement, graphics shrinking, graphics enlargement, graphics rotation, graphics combination, graphics deletion, and graphics edge processing, which can process graphics from multiple aspects and improve the collaborative optimization and accuracy of graphics processing.

[0038] In some examples, the above-described graphic processing may also include transforming the graphic, such as changing a polygon into a rectangle, or changing straight lines on the edges of the graphic into curves.

[0039] When performing graphic processing on a layout to be optimized that includes a first graphic and a second graphic based on a graphic processing model, graphic processing can be performed on target areas or target graphics that do not conform to preset rules in order to improve the accuracy of graphic processing.

[0040] In some embodiments, such as Figure 3 As shown, the above-mentioned graphic processing of the first and second graphics based on the graphics processing model to obtain the design graphic of the mask may include the following steps S310-S320:

[0041] S310: The graphics processing model detects whether the first graphic and multiple second graphics conform to the preset rules, and identifies the target area in the first graphic that does not conform to the preset rules and the target graphic in the second graphic that does not conform to the preset rules; wherein, the preset rules are the geometric parameter rules of the mask graphic.

[0042] The image processing model can be used to detect whether the first and second images conform to preset rules. The preset rules can be the geometric parameter rules of the design image of the mask that are set manually. For example, the geometric parameter rules can include the size of the image area, the minimum distance between the image itself, that is, the minimum distance between any two points in the image, the distance between the images, the shape of the image, the line width of the image, and other geometric parameter rules that conform to the mask manufacturing rules.

[0043] Target areas that do not conform to the preset rules can be identified in the first graphic, and target graphics that do not conform to the preset rules can be identified in the second graphic.

[0044] S320: The target area and target graphic are processed by the graphic processing model to obtain the design graphic of the mask.

[0045] The target area and target graphic can be processed using a graphics processing model to obtain the design graphic of the mask. For example, the target area in the first graphic can be broken using a graphics processing model to obtain target line segments, and then the target line segments can be moved to the target position.

[0046] In some examples, the target preset rules corresponding to the target graphics that do not conform to the preset rules can be determined. For example, if the size of the target graphics does not conform to the preset rules, graphic processing such as graphics enlargement or graphics reduction can be performed on the target graphics. Or, if the distance between the target graphics and the first graphics does not conform to the preset rules, graphic processing such as graphics movement can be performed on the target graphics. These will not be elaborated here.

[0047] This application embodiment first detects the layout to be optimized, which includes a first graphic and a second graphic, using a graphic processing model. It identifies target areas in the first graphic that do not conform to preset rules, and target images in the second graphic that do not conform to preset rules. Graphic processing is then performed on the target areas and target graphics, which can achieve simultaneous graphic processing of the first graphic and the second graphic, thereby improving the accuracy and collaborative optimization of the processing of the first graphic and the second graphic.

[0048] It is conceivable that after obtaining the design pattern of the mask, it can be inspected to determine the deviation value between the exposure outline of the design pattern and the pattern to be optimized, and to determine whether it can be used as the process pattern for the mask manufacturing process. Here, the process pattern is a pattern that can be used in the mask manufacturing process.

[0049] In some embodiments, such as Figure 4 As shown, after step S120 above—processing the target area and target graphic using a graphic processing model to obtain the design graphic of the mask—the generation method may further include the following steps S410-S430:

[0050] S410: Perform exposure processing on the design graphic to obtain the exposed graphic.

[0051] The above design graphic can be exposed to obtain an exposed graphic. Here, an exposure simulation application can be used to expose the above design graphic to obtain an exposed graphic.

[0052] S420: Determine the deviation value between the layout to be optimized and the exposure pattern based on the layout to be optimized and the exposure pattern.

[0053] The deviation between the layout to be optimized and the exposure pattern can be determined using the layout to be optimized and the exposure pattern. For example, the deviation can be determined based on the edge placement error (EPE) in different regions of the layout to be optimized and the exposure pattern. Edge placement error is an indicator used to measure the quality of correction; the smaller the edge placement error, the closer the exposure pattern is to the layout to be optimized.

[0054] In some examples, the above deviation values ​​can be the average or weighted average of the edge placement errors of the layout to be optimized and the exposure pattern in different areas.

[0055] S430: If the deviation value is less than or equal to the preset threshold, determine the design drawing as the process drawing of the mask.

[0056] When the above deviation value is less than or equal to a preset threshold, it indicates that the above design pattern can be used as a process pattern for process production as a mask.

[0057] It is conceivable that when the above deviation value is determined to be greater than the above preset threshold, the design graphic can be re-input into the above graphic processing model to process the design graphic and obtain a new design graphic. Then, based on the exposure processing of the new design graphic, a new exposure graphic is obtained. Then, the deviation value between the new exposure graphic and the layout to be optimized is determined to determine whether the new design graphic can be used as a process graphic. This process is repeated until a process graphic of a mask that meets the requirements is output. The specific steps are the same as the steps for determining the error value described above, and will not be repeated here.

[0058] In this embodiment, after generating the design pattern, an exposed pattern is obtained by exposing the design pattern. The deviation value between the exposed pattern and the layout to be optimized is determined to determine whether it can be used as a process pattern. If the deviation value is less than or equal to a preset threshold, the design pattern can be used as a process pattern, thus obtaining a process pattern with a more optimized exposure profile.

[0059] In some embodiments, the deviation value includes the edge placement error or the square of the Euler distance between the pixel matrix of the exposed pattern and the pixel matrix of the layout to be optimized.

[0060] The deviation value can be the edge placement error. In some examples, the deviation value can be the average or weighted average of the edge placement errors of the layout to be optimized and the exposure pattern in different areas. Or...

[0061] The aforementioned deviation value can be the square of the Euler distance between the pixel matrix of the exposed pattern and the pixel matrix of the pattern to be optimized. Here, the first pixel value of each pixel in the exposed pattern is determined, thus determining the first pixel matrix, and the second pixel value of each pixel in the pattern to be optimized is determined, thus determining the second pixel matrix. The square of the Euler distance is then determined based on the first and second pixel matrices.

[0062] In some examples, the above deviation values ​​meet the following conditions:

[0063]

[0064] Where F is the deviation value, M and N represent the number of rows and columns of the target graphic, i and j are the row index and column index, a is the first pixel value, and b is the second pixel value.

[0065] The embodiments of this application, by including the edge placement error or the square of the Euler distance in the above-mentioned deviation values, can improve the accuracy of the determined deviation values, which is beneficial to the accuracy of determining whether the above-mentioned design graphics can be used as process graphics, and improve the process level.

[0066] It can be conceivable that when processing graphics based on the above graphics processing model, the initial model can be trained first to obtain the above graphics processing model.

[0067] In some embodiments, before step S120 above—inputting the first graphic and the second graphic into a preset graphic processing model, and performing graphic processing on the first graphic and the second graphic based on the graphic processing model to obtain the design graphic of the mask—the generation method may further include the following steps:

[0068] Training samples are acquired, including sample design graphics and sample process graphics generated based on the sample design graphics. The sample design graphics are input into an initial model, and the initial model is used to process the sample design graphics to obtain adjusted graphics. The initial model is a model built based on a deep learning algorithm. Based on the deviation between the sample process graphics and the adjusted graphics, the initial model is trained to obtain a graphics processing model. Here, the initial module is a model built based on a supervised learning algorithm.

[0069] Training samples can be obtained, including multiple sample design graphics and sample process graphics generated based on the sample design graphics, where one sample design graphic corresponds to one sample process graphic. The sample design graphics and sample process graphics can be used as a pre-training set input to the initial model. The initial model performs graphic processing on the sample design graphics to obtain adjusted graphics. The graphic processing steps of the initial model on the sample design graphics include at least one of the following: graphic movement, graphic reduction, graphic enlargement, graphic rotation, graphic combination, graphic deletion, and graphic edge processing. The initial model can be trained based on the deviation between the sample process graphics and the adjusted graphics to obtain the aforementioned graphic processing model.

[0070] This application embodiment trains an initial model based on training samples to obtain a graphics processing model, which can improve the accuracy of the graphics processing model in graphics processing, and thus improve the accuracy of the generated design graphics.

[0071] Before obtaining the above-mentioned layout to be optimized, a second graphic can be generated based on the first graphic obtained above.

[0072] In some embodiments, such as Figure 5 As shown, before step S110 above: obtaining the layout to be optimized from the mask, the generation method may further include:

[0073] S510: Obtain the first pattern and operating condition information, including the type of photoresist, light source information, and the geometric parameter rules of the mask pattern input by the user.

[0074] The system can acquire a first graphic and operating condition information. Here, the first graphic is the main design graphic of the photomask input by the user. The operating condition information may include the type of photoresist, light source information, and geometric parameter rules of the photomask. The type of photoresist may include positive and negative photoresist. The light source information may include the number of light sources and the relative position information of the light sources and the photomask in the photolithography process. The geometric parameter rules may include the number, size, shape, and distance of the second graphic from the first graphic.

[0075] S520: Based on the first pattern, the type of photoresist, the light source information, and the geometric parameter rules, the second pattern is generated through inversion lithography.

[0076] The second pattern can be generated by ILT based on the first pattern, the type of photoresist, the light source information, and the geometric parameter rules.

[0077] In some embodiments, the first graphic and operating condition information described above can be input into a graphic generation model to obtain the second graphic described above.

[0078] In some examples, a first initial model can be pre-set, and the first initial model can be trained using a first training sample to obtain the above-mentioned graphics generation model. Here, the steps for generating the graphics generation model may include:

[0079] A first training sample is obtained, comprising a sample image, sample condition information, and a third image. The third image is a sub-resolution auxiliary image. The sample condition information includes the sample type of photoresist, sample information of the light source, and sample geometric parameter rules. The sample image, sample type, sample information of the light source, and sample geometric parameter rules are input into a first initial model to generate an image. The first initial model is trained based on the deviation between the third image and the first image to obtain the aforementioned image generation model. This method of training the first initial model to obtain the image generation model can improve the accuracy of the second image generated by the aforementioned image generation model.

[0080] In some examples, without specific geometric parameter rules, the above-mentioned graphics generation model can output universal sub-resolution auxiliary graphics when only the main design graphics and working condition information are input.

[0081] This application embodiment improves the accuracy and efficiency of the generated second graphic by generating a second graphic based on the first graphic and operating condition information before obtaining the layout to be optimized.

[0082] In some embodiments, a design model including the above-mentioned graphics generation model and graphics processing model can be set to realize the situation where the first graphics and working condition information are input into the above-mentioned design model, and the process graphics of the mask are output through the design model to improve the efficiency of generating process graphics.

[0083] Based on the same inventive concept, embodiments of this application also provide an apparatus for generating design patterns of a mask.

[0084] In some embodiments, such as Figure 6 As shown, this application embodiment provides an apparatus for generating a design graphic of a mask, the apparatus including:

[0085] The acquisition module 601 is used to acquire the layout to be optimized of the mask. The layout to be optimized includes a first graphic and a second graphic. The first graphic is the main design graphic in the layout to be optimized, and the second graphic is a plurality of sub-resolution auxiliary graphics generated based on the main design graphic.

[0086] The processing module 602 is used to input the first graphic and the second graphic into a preset graphic processing model, and perform graphic processing on the first graphic and the second graphic based on the graphic processing model to obtain the design graphic of the mask. The graphic processing includes at least one of the following: graphic movement, graphic shrinking, graphic enlargement, graphic rotation, graphic combination, graphic deletion, graphic edge processing, and graphic deformation.

[0087] In this embodiment, the acquisition module obtains the layout to be optimized, and the processing module inputs the initial actual graphics into the graphics processing model to simultaneously process the main design graphics and sub-resolution auxiliary graphics in the layout to be optimized. This can improve the efficiency of graphics processing. Furthermore, the above-mentioned graphics processing covers a variety of processes such as graphics movement, graphics shrinking, graphics enlargement, graphics rotation, graphics combination, graphics deletion, graphics edge processing, and graphics deformation, which can process graphics from multiple aspects and improve the accuracy of graphics processing.

[0088] In some embodiments, the second graphic includes multiple:

[0089] The processing module can be specifically used for:

[0090] The image processing model detects whether the first image and multiple second images conform to preset rules, and identifies target areas in the first image that do not conform to the preset rules and target images in the second images that do not conform to the preset rules; wherein, the preset rules are the geometric parameter rules of the mask image.

[0091] The target area and target graphic are processed by a graphic processing model to obtain the design graphic of the mask.

[0092] In some embodiments, the processing module may also be used for:

[0093] The design graphic is subjected to exposure processing to obtain an exposed graphic;

[0094] Based on the layout to be optimized and the exposure pattern, determine the deviation value between the layout to be optimized and the exposure pattern;

[0095] If the deviation value is less than or equal to the preset threshold, the design graphic is determined to be the process graphic of the mask.

[0096] In some embodiments, the deviation value includes the edge placement error or the square of the Euler distance between the pixel matrix of the exposed pattern and the pixel matrix of the layout to be optimized.

[0097] In some embodiments, the acquisition module can also be used for:

[0098] Acquire training samples, which include sample design graphics and sample process graphics generated based on the sample design graphics;

[0099] The sample design graphic is input into the initial model, and the graphic is processed based on the initial model to obtain the adjusted graphic. The initial model is a model built based on a deep learning algorithm.

[0100] Based on the deviation between the sample process graphics and the adjusted graphics, the initial model is trained to obtain the graphics processing model.

[0101] In some embodiments, the acquisition module can also be used for:

[0102] Acquire the first graphic and operating condition information, including the type of photoresist, light source information, and geometric parameter rules of the mask graphic input by the user;

[0103] Based on the first pattern, the type of photoresist, the light source information, and the geometric parameter rules, a second pattern is generated using inversion lithography technology.

[0104] The apparatus described above is used to implement the method for generating the design pattern of the corresponding mask in any of the foregoing embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0105] Figure 7 A schematic diagram of the hardware structure of an electronic device is provided in the application embodiment.

[0106] The electronic device 700 may include a processor 701 and a memory 702 storing computer program instructions.

[0107] Specifically, the processor 701 may include a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0108] Memory 702 may include mass storage for data or instructions. For example, and not limitingly, memory 702 may include a hard disk drive (HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, memory 702 may include removable or non-removable (or fixed) media. Where appropriate, memory 702 may be internal or external to the integrated gateway disaster recovery device. In a particular embodiment, memory 702 is non-volatile solid-state memory.

[0109] In a particular embodiment, memory 702 includes read-only memory (ROM). Where appropriate, the ROM may be a mask-programmed ROM, a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM), an electrically rewritable ROM (EAROM), or flash memory, or a combination of two or more of these.

[0110] Memory may include read-only memory (ROM), random access memory (RAM), disk storage media devices, optical storage media devices, flash memory devices, and electrical, optical, or other physical / tangible memory storage devices. Therefore, typically, memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to the first aspect of this application.

[0111] The processor 701 reads and executes computer program instructions stored in the memory 702 to implement any of the mask design pattern generation methods in the above embodiments.

[0112] In one example, the electronic device may also include a communication interface 703 and a bus 704. Wherein, as... Figure 7 The processor 701, memory 702, and communication interface 703 are connected through bus 704 and complete communication with each other.

[0113] The communication interface 703 is mainly used to realize communication between various modules, devices, units and / or equipment in the embodiments of this application.

[0114] Bus 704 includes hardware, software, or both, that couples components of an online data traffic metering device together. For example, and not limitingly, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a Microchannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses, or combinations of two or more of these. Where appropriate, bus 704 may include one or more buses. Although specific buses are described and illustrated in embodiments of this application, any suitable bus or interconnect is contemplated herein.

[0115] The electronic device described in the above embodiments is used to implement the method for generating the design pattern of the corresponding mask in any of the foregoing embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0116] Furthermore, in conjunction with the mask design pattern generation method in the above embodiments, this application embodiment can provide a computer storage medium for implementation. This computer storage medium stores computer program instructions; when these computer program instructions are executed by a processor, they implement any of the mask design pattern generation methods in the above embodiments.

[0117] Furthermore, in conjunction with the mask design pattern generation method in the above embodiments, this application embodiment can provide a computer program product for implementation. When the instructions of this computer program product are executed by the processor of an electronic device, they implement any of the mask design pattern generation methods in the above embodiments.

[0118] Those skilled in the art should understand that the discussion of any of the above embodiments is merely exemplary and is not intended to imply that the scope of this application (including the claims) is limited to these examples; within the framework of this application, the technical features of the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other variations of different aspects of the embodiments of this application as described above, which are not provided in the details for the sake of brevity.

[0119] The functional blocks shown in the above-described structural diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this application are programs or code segments used to perform the required tasks. Programs or code segments can be stored on a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried on a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio frequency (RF) links, etc. Code segments can be downloaded via computer networks such as the Internet, intranets, etc.

[0120] It should also be noted that the exemplary embodiments mentioned in this application describe methods or apparatuses based on a series of steps or devices. However, this application is not limited to the order of the above steps; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0121] The aspects of this application have been described above with reference to flowchart illustrations and / or block diagrams of methods, apparatus (devices), and computer program products according to embodiments of this application. It should be understood that each block in the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It is also understood that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by dedicated hardware performing the specified functions or actions, or can be implemented by a combination of dedicated hardware and computer instructions.

[0122] The above description is merely a specific embodiment of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the devices, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the protection scope of this application.

Claims

1. A method for generating a design graphic using a mask, characterized in that, include: Obtain the layout to be optimized from the mask, the layout to be optimized includes a first graphic and a second graphic, the first graphic is the main design graphic in the layout to be optimized, and the second graphic is a plurality of sub-resolution auxiliary graphics generated based on the main design graphic; The first graphic and the second graphic are input into a preset graphic processing model. Based on the graphic processing model, the first graphic and the second graphic are processed to obtain the design graphic of the mask. The graphic processing includes at least one of the following: graphic movement, graphic shrinking, graphic enlargement, graphic rotation, graphic combination, graphic deletion, graphic edge processing, and graphic deformation. Based on the aforementioned graphics processing model, the first and second graphics are processed to obtain the design graphics of the mask, including: The image processing model detects whether the first image and multiple second images conform to preset rules, and identifies target regions in the first image that do not conform to the preset rules and target images in the second images that do not conform to the preset rules; wherein, the preset rules are geometric parameter rules of the mask image; The target region and the target graphic are processed by a deep learning algorithm in the graphic processing model to obtain the design graphic of the mask; wherein, the graphic edge processing includes breaking the edge of the graphic to obtain the target line segment and moving the target line segment to a preset position, and the graphic deformation includes changing the graphic from a polygon to a rectangle, or changing the edge of the graphic from a straight line to a curve.

2. The method for generating a design graphic of a mask according to claim 1, characterized in that, After processing the target region and the target graphic using a graphics processing model to obtain the design graphic of the mask, the generation method further includes: The design graphic is subjected to exposure processing to obtain an exposed graphic; Based on the layout to be optimized and the exposure pattern, determine the deviation value between the layout to be optimized and the exposure pattern; If the deviation value is less than or equal to a preset threshold, the design pattern is determined to be a process pattern of the mask.

3. The method for generating a design graphic of a mask according to claim 2, characterized in that, The deviation value includes edge placement error or the square of the Euler distance between the pixel matrix of the exposed pattern and the pixel matrix of the pattern to be optimized.

4. The method for generating a design graphic of a mask according to claim 1, characterized in that, Before inputting the first graphic and the second graphic into a preset graphic processing model, and performing graphic processing on the first graphic and the second graphic based on the graphic processing model to obtain the design graphic of the mask, the generation method further includes: Obtain training samples, which include sample design graphics and sample process graphics generated based on the sample design graphics; The sample design graphic is input into the initial model, and the graphic is processed based on the initial model to obtain the adjusted graphic. The initial model is a model built based on a deep learning algorithm. Based on the deviation between the sample process graphic and the adjusted graphic, the initial model is trained to obtain the graphic processing model.

5. The method for generating a design graphic of a mask according to claim 1, characterized in that, Before obtaining the optimized layout of the mask, the generation method further includes: The first graphic and working condition information are obtained, wherein the working condition information includes the type of photoresist, light source information, and geometric parameter rules of the mask graphic input by the user; The second pattern is generated based on the first pattern, the type of photoresist, the light source information, and the geometric parameter rules through inversion lithography.

6. An apparatus for generating a design graphic of a mask, characterized in that, include: The acquisition module is used to acquire the layout to be optimized of the mask, the layout to be optimized includes a first graphic and a second graphic, the first graphic is the main design graphic in the layout to be optimized, and the second graphic is a plurality of sub-resolution auxiliary graphics generated based on the main design graphic; The processing module is used to input the first graphic and the second graphic into a preset graphic processing model, and perform graphic processing on the first graphic and the second graphic based on the graphic processing model to obtain the design graphic of the mask. The graphic processing includes at least one of the following: graphic movement, graphic shrinking, graphic enlargement, graphic rotation, graphic combination, graphic deletion, graphic edge processing, and graphic deformation. Based on the aforementioned graphics processing model, the first and second graphics are processed to obtain the design graphics of the mask, including: The image processing model detects whether the first image and multiple second images conform to preset rules, and identifies target regions in the first image that do not conform to the preset rules and target images in the second images that do not conform to the preset rules; wherein, the preset rules are geometric parameter rules of the mask image; The target region and the target graphic are processed by a deep learning algorithm in the graphic processing model to obtain the design graphic of the mask; wherein, the graphic edge processing includes breaking the edge of the graphic to obtain the target line segment and moving the target line segment to a preset position, and the graphic deformation includes changing the graphic from a polygon to a rectangle, or changing the edge of the graphic from a straight line to a curve.

7. An electronic device, characterized in that, The device includes: a processor, and a memory storing computer program instructions; The processor reads and executes the computer program instructions to implement the method for generating a design graphic of a mask as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer program instructions that, when executed by a processor, implement the method for generating a mask design drawing as described in any one of claims 1 to 5.

9. A computer program product, comprising a computer program, characterized in that, When the computer program is processed by a processor, it implements the method for generating a design drawing of a mask as described in any one of claims 1 to 5.

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