CN116841135B - Mask pattern optimization method, mask pattern optimization device, exposure equipment and storage medium - Google Patents

Mask pattern optimization method, mask pattern optimization device, exposure equipment and storage medium Download PDF

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Publication number
CN116841135B
CN116841135B CN202311111059.3A CN202311111059A CN116841135B CN 116841135 B CN116841135 B CN 116841135B CN 202311111059 A CN202311111059 A CN 202311111059A CN 116841135 B CN116841135 B CN 116841135B
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mask pattern
pixel
pattern
node
preset number
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CN116841135A (en
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和琨
牛志元
陈健
杜德川
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Guangke Xintu Beijing Technology Co ltd
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Guangke Xintu Beijing Technology Co ltd
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    • G—PHYSICS
    • G03—PHOTOGRAPHY; CINEMATOGRAPHY; ANALOGOUS TECHNIQUES USING WAVES OTHER THAN OPTICAL WAVES; ELECTROGRAPHY; HOLOGRAPHY
    • G03F—PHOTOMECHANICAL PRODUCTION OF TEXTURED OR PATTERNED SURFACES, e.g. FOR PRINTING, FOR PROCESSING OF SEMICONDUCTOR DEVICES; MATERIALS THEREFOR; ORIGINALS THEREFOR; APPARATUS SPECIALLY ADAPTED THEREFOR
    • G03F7/00—Photomechanical, e.g. photolithographic, production of textured or patterned surfaces, e.g. printing surfaces; Materials therefor, e.g. comprising photoresists; Apparatus specially adapted therefor
    • G03F7/70—Microphotolithographic exposure; Apparatus therefor
    • G03F7/70483—Information management; Active and passive control; Testing; Wafer monitoring, e.g. pattern monitoring
    • G03F7/70491—Information management, e.g. software; Active and passive control, e.g. details of controlling exposure processes or exposure tool monitoring processes
    • G—PHYSICS
    • G03—PHOTOGRAPHY; CINEMATOGRAPHY; ANALOGOUS TECHNIQUES USING WAVES OTHER THAN OPTICAL WAVES; ELECTROGRAPHY; HOLOGRAPHY
    • G03F—PHOTOMECHANICAL PRODUCTION OF TEXTURED OR PATTERNED SURFACES, e.g. FOR PRINTING, FOR PROCESSING OF SEMICONDUCTOR DEVICES; MATERIALS THEREFOR; ORIGINALS THEREFOR; APPARATUS SPECIALLY ADAPTED THEREFOR
    • G03F1/00—Originals for photomechanical production of textured or patterned surfaces, e.g., masks, photo-masks, reticles; Mask blanks or pellicles therefor; Containers specially adapted therefor; Preparation thereof
    • G03F1/68—Preparation processes not covered by groups G03F1/20 - G03F1/50
    • G03F1/76—Patterning of masks by imaging
    • G—PHYSICS
    • G03—PHOTOGRAPHY; CINEMATOGRAPHY; ANALOGOUS TECHNIQUES USING WAVES OTHER THAN OPTICAL WAVES; ELECTROGRAPHY; HOLOGRAPHY
    • G03F—PHOTOMECHANICAL PRODUCTION OF TEXTURED OR PATTERNED SURFACES, e.g. FOR PRINTING, FOR PROCESSING OF SEMICONDUCTOR DEVICES; MATERIALS THEREFOR; ORIGINALS THEREFOR; APPARATUS SPECIALLY ADAPTED THEREFOR
    • G03F7/00—Photomechanical, e.g. photolithographic, production of textured or patterned surfaces, e.g. printing surfaces; Materials therefor, e.g. comprising photoresists; Apparatus specially adapted therefor
    • G03F7/70—Microphotolithographic exposure; Apparatus therefor
    • G03F7/70408—Interferometric lithography; Holographic lithography; Self-imaging lithography, e.g. utilizing the Talbot effect
    • G—PHYSICS
    • G03—PHOTOGRAPHY; CINEMATOGRAPHY; ANALOGOUS TECHNIQUES USING WAVES OTHER THAN OPTICAL WAVES; ELECTROGRAPHY; HOLOGRAPHY
    • G03F—PHOTOMECHANICAL PRODUCTION OF TEXTURED OR PATTERNED SURFACES, e.g. FOR PRINTING, FOR PROCESSING OF SEMICONDUCTOR DEVICES; MATERIALS THEREFOR; ORIGINALS THEREFOR; APPARATUS SPECIALLY ADAPTED THEREFOR
    • G03F7/00—Photomechanical, e.g. photolithographic, production of textured or patterned surfaces, e.g. printing surfaces; Materials therefor, e.g. comprising photoresists; Apparatus specially adapted therefor
    • G03F7/70—Microphotolithographic exposure; Apparatus therefor
    • G03F7/70425—Imaging strategies, e.g. for increasing throughput or resolution, printing product fields larger than the image field or compensating lithography- or non-lithography errors, e.g. proximity correction, mix-and-match, stitching or double patterning
    • G—PHYSICS
    • G03—PHOTOGRAPHY; CINEMATOGRAPHY; ANALOGOUS TECHNIQUES USING WAVES OTHER THAN OPTICAL WAVES; ELECTROGRAPHY; HOLOGRAPHY
    • G03F—PHOTOMECHANICAL PRODUCTION OF TEXTURED OR PATTERNED SURFACES, e.g. FOR PRINTING, FOR PROCESSING OF SEMICONDUCTOR DEVICES; MATERIALS THEREFOR; ORIGINALS THEREFOR; APPARATUS SPECIALLY ADAPTED THEREFOR
    • G03F7/00—Photomechanical, e.g. photolithographic, production of textured or patterned surfaces, e.g. printing surfaces; Materials therefor, e.g. comprising photoresists; Apparatus specially adapted therefor
    • G03F7/70—Microphotolithographic exposure; Apparatus therefor
    • G03F7/70483—Information management; Active and passive control; Testing; Wafer monitoring, e.g. pattern monitoring
    • G03F7/70491—Information management, e.g. software; Active and passive control, e.g. details of controlling exposure processes or exposure tool monitoring processes
    • G03F7/70508—Data handling in all parts of the microlithographic apparatus, e.g. handling pattern data for addressable masks or data transfer to or from different components within the exposure apparatus

Abstract

The application relates to the technical field of photoetching of semiconductor manufacture, and discloses a mask pattern optimization method, a device, exposure equipment and a storage medium. After the state change of the position of a certain pixel point in the mask pattern is calculated again and again like the traditional direct searching algorithm, the difference degree between the corresponding imaging pattern of the mask pattern and the target pattern is not required, and the calculation efficiency of the difference degree is greatly improved, so that the optimization efficiency of the mask pattern is improved.

Description

Mask pattern optimization method, mask pattern optimization device, exposure equipment and storage medium
Technical Field
The present application relates to the field of photolithography technology for semiconductor manufacturing, and in particular, to a mask pattern optimization method, apparatus, exposure device, and storage medium.
Background
With the rapid development of the information technology industry, computing holographic lithography (also called computing lithography) has become a main technology in lithography technology, and the industry also tends to optimize a binary mask of a large-size chip based on computing holographic lithography, so as to realize the manufacture of the large-size chip.
When a binary mask of a large-size chip is optimized by conventional computational holographic lithography, the contribution of all pixel points in a mask pattern on the binary mask to imaging is usually evaluated again and again by using a direct search algorithm, and then the difference degree of the corresponding imaging pattern of the mask pattern and a target pattern on a preset wafer is compared to determine a final mask pattern optimization result.
However, the direct search algorithm has a time dependency in nature, i.e. the evaluation of new pixels on the mask pattern depends on the result of the previous pixel, whereas the dimension of the mask pattern (i.e. the number of pixels) of a large-sized chip tends to be large. This results in an increase in the time taken for the direct search to complete an evaluation of all pixels on the mask pattern at one time, thereby greatly increasing the duration of optimization of the mask pattern. Therefore, how to improve the optimization efficiency of the mask pattern has become a technical problem to be continuously solved.
Disclosure of Invention
In view of the above, the present application provides a method, apparatus, exposure apparatus, and storage medium for optimizing a mask pattern to solve the problem of how to improve the efficiency of optimizing a mask pattern.
In a first aspect, the present application provides a method for optimizing a mask pattern, applied to an exposure apparatus of a chip manufacturing process, the exposure apparatus including a master node and at least one slave node, each node storing a target pattern and the mask pattern, the method being performed by the master node, the method comprising:
selecting a first preset number of pixel points from the mask pattern in the current iteration period;
according to a preset pixel value overturning rule, overturning the pixel value of each pixel point in the first preset number to obtain a plurality of element combinations, wherein elements in each element combination correspond to the states of the positions of different pixel points in the first preset number;
distributing part of element combinations in the element combinations to at least one slave node so that different slave nodes respectively determine slave node difference degrees between a new imaging pattern and a target pattern according to the received element in each element combination and the mask pattern, wherein each new imaging pattern is generated based on the element in the element combination and the mask pattern;
Determining a main node difference degree between a new imaging pattern and a target pattern according to the elements in each element combination stored in the main node and the mask pattern;
obtaining slave node difference degrees fed back by all slave nodes;
determining an optimization result of the mask pattern in the current iteration period according to all the master node difference degrees, all the slave node difference degrees and the initial difference degrees, wherein the initial difference degrees are the difference degrees between the imaging pattern generated by the mask pattern before updating under the irradiation of the target light source and the target pattern;
when the optimization result is determined to be not in accordance with the preset iterative optimization condition, taking the optimization result as a mask pattern of the next iterative period, and entering the next iterative period;
or stopping the optimization operation when the optimization result is determined to meet the preset iterative optimization condition.
In the above technical solution, a plurality of nodes are set in the exposure apparatus, and the target pattern and the mask pattern are stored in each node, so that it can be ensured that different nodes in the system can perform independent operation according to the data stored in the nodes. In this way, in the current iteration period, the master node selects a first preset number of pixel points from the mask patterns stored by the master node, and according to a preset pixel value overturning rule, the pixel value of each pixel point in the first preset number is overturned to obtain a plurality of element combinations, and then part of element combinations in the plurality of element combinations can be distributed to at least one slave node. And the elements in each element combination correspond to the states of the positions of different pixel points in the first preset number, so that the master node and the different slave nodes can independently and parallelly determine the difference degree between a new imaging pattern and the target pattern according to the elements in each element combination representing different states and the mask patterns stored by the master node and the different slave nodes, so that the optimization result of the preset mask patterns in the current iteration period is determined according to the difference degree determined by all the nodes, and whether the optimization operation is stopped is determined. The method realizes the calculation of the difference degree of the imaging pattern and the target pattern corresponding to the element combination stored by the nodes in parallel, and the difference degree between the imaging pattern and the target pattern corresponding to the mask pattern is greatly accelerated after the state change of the position of a certain pixel point in the mask pattern is calculated again and again as in the traditional direct searching algorithm, so that the calculation efficiency of the difference degree is greatly accelerated, and the optimization efficiency of the mask pattern is accelerated. For example, if N pixel points are selected, through the above steps, the master node and the slave node can simultaneously realize the evaluation of N pixel points on the mask pattern, and if the total number of pixel points on the mask pattern is M, the number of calculation times required for completing one evaluation of all pixel points on the mask pattern is about M/N, so that the calculation speed can achieve N times of acceleration, and the optimization efficiency is greatly improved.
In an optional embodiment, the mask pattern is a pattern on a holographic binary mask, and the turning over pixel values of the pixel points at each position in the first preset number according to a preset pixel value turning rule, to obtain a plurality of element combinations, includes: combining the first preset number of pixel points based on a plurality of candidate pixel values corresponding to each pixel point in the first preset number, so as to obtain a plurality of pixel point combinations, wherein each pixel point combination is composed of the first preset number of pixel points; according to the pixel value of each pixel in each pixel combination and the initial pixel value of each pixel in the first preset number, the change of the state of the position of each pixel in each pixel combination is respectively determined, the change is expressed in a binary form, the element combination corresponding to each pixel combination is obtained, and the initial pixel value is the pixel value of the pixel in the mask pattern before updating.
In the above technical solution, based on a plurality of candidate pixel values corresponding to each pixel point in the first preset number, the first preset number of pixel points are combined to obtain a plurality of pixel point combinations, so as to realize traversal of all possible values of the pixel points after the plurality of pixel points are selected. And then, according to the pixel value of each pixel in each pixel combination and the initial pixel value of each pixel in the first preset number, the state change of the position of each pixel in each pixel combination is respectively determined, and the change is expressed in a binary form, so that the element combination corresponding to each pixel combination is obtained, and the element combination in the binary form is obtained, so that only one or more binary numbers can be conveniently transmitted when data are transmitted to different slave nodes in the subsequent process, the transmission of the pixel values of a plurality of pixels is avoided, the communication pressure is reduced, and the communication cost is saved.
In an alternative embodiment, determining a master node difference between a new imaged pattern and a target pattern based on the mask pattern and the elements in each combination of elements stored in the master node, respectively, includes: respectively modifying the pixel values of the first preset number of pixel points in the mask pattern according to the elements in each element combination stored in the main node and the initial pixel values of each pixel point in the first preset number to obtain an updated mask pattern; according to the pixel value of each pixel point in each updated mask pattern and the diffraction rule of light, respectively determining a new imaging pattern corresponding to each updated mask pattern; and respectively determining the difference degree of the main node between each new imaging pattern and the target pattern according to the pixel value of each pixel point in each new imaging pattern and the pixel value of each pixel point in the target pattern.
In the above technical solution, the pixel values of the first preset number of pixels in the mask pattern are modified based on the stored elements in each element combination and the initial pixel values of each pixel in the first preset number, so as to obtain updated mask patterns corresponding to different element combinations, thereby determining new imaging patterns corresponding to each updated mask pattern, further calculating the difference degree of main nodes between each new imaging pattern and the target pattern, and realizing possible evaluation of different values of the pixels stored by the mask pattern.
In an alternative embodiment, determining the optimization result of the mask pattern in the current iteration period according to all the master node differences, all the slave node differences and the initial differences comprises: selecting the minimum difference degree with the smallest numerical value from all the master node difference degrees, all the slave node difference degrees and the initial difference degrees, and determining the value of the initial difference degree as the value of the minimum difference degree; acquiring an element combination corresponding to the minimum difference degree, modifying the pixel values of the first preset number of pixel points in the mask pattern according to the element in the element combination corresponding to the minimum difference degree and the initial pixel value of each pixel point in the first preset number, and determining the modified mask pattern as an optimization result.
In the above technical solution, the element combination corresponding to the minimum difference is obtained, and the pixel values of the first preset number of pixels in the mask pattern are modified according to the element in the element combination corresponding to the minimum difference and the initial pixel value of each pixel in the first preset number, and the modified mask pattern is determined as the optimization result.
In an alternative embodiment, when it is determined that the optimization result does not meet the preset iterative optimization condition, the optimization result is used as a mask pattern of the next iteration period, and before the next iteration period is entered, the method further includes: and distributing the element combination corresponding to the minimum difference degree to different slave nodes so that the different slave nodes update the mask patterns stored by themselves according to the elements in the element combination corresponding to the minimum difference degree and the initial pixel value of each pixel point in the first preset number.
In the above technical solution, after the master node determines the optimization result of the current iteration period, the element combination corresponding to the minimum difference degree is further distributed to all the slave nodes in the exposure device, so that each slave node can timely update the mask pattern stored by itself according to the element in the element combination corresponding to the minimum difference degree, and therefore, when the master node continues to perform the optimization operation, the operation can be performed on the mask pattern updated recently, and the accuracy of mask pattern optimization is ensured.
In an alternative embodiment, the method further comprises, prior to selecting the first preset number of pixels from the mask pattern: respectively initializing the phase and amplitude of each pixel point in the mask pattern and the target pattern; and determining the phase and the amplitude corresponding to each pixel point in the mask pattern and the target pattern stored by the slave node respectively.
In the technical scheme, the master node determines that the slave node independently initializes the mask pattern and the target pattern stored by the master node, and does not send the initialized mask pattern and target pattern to different slave nodes through a communication network, so that the transmission of high-dimensional pattern data is avoided, and the communication cost can be saved.
In an alternative embodiment, selecting a first preset number of pixel points from the mask pattern includes: based on a direct search algorithm, a first preset number of pixel points is selected from the mask pattern, the first preset number being a positive integer greater than or equal to 2.
In the technical scheme, the pixel values of at least two pixel points are changed at one time by utilizing the direct search algorithm, so that the difference degree of a plurality of pixel points after being changed is conveniently calculated at the subsequent time, the defect that the pixel value of only one pixel point is changed at each time for evaluation is avoided, the time consumption for evaluating all the pixel points on the mask pattern at one time can be greatly reduced, and the mask pattern optimization efficiency is improved.
In a second aspect, the present application provides an optimizing apparatus of a mask pattern, applied to an exposure device of a chip preparation process, the exposure device including a master node and at least one slave node, each node storing a target pattern and a mask pattern, the apparatus being executed by the master node, the apparatus including a selection module, a flipping module, a distribution module, a first determination module, an acquisition module, a second determination module, and a third determination module.
The selecting module is used for selecting a first preset number of pixel points from the mask pattern in the current iteration period;
The overturning module is used for overturning the pixel value of the pixel point of each position in the first preset quantity according to a preset pixel value overturning rule to obtain a plurality of element combinations, and the elements in each element combination correspond to the states of the positions of different pixel points in the first preset quantity;
the distribution module is used for distributing part of element combinations in the element combinations to at least one slave node so that different slave nodes respectively determine slave node difference degrees between a new imaging pattern and a target pattern according to the received elements in each element combination and the mask pattern, and each new imaging pattern is generated based on the elements in the element combination and the mask pattern;
the first determining module is used for determining the difference degree of the main node between a new imaging pattern and a target pattern according to the elements in each element combination stored in the main node and the mask pattern;
the acquisition module is used for acquiring the slave node difference degree fed back by all the slave nodes;
the second determining module is used for determining an optimization result of the mask pattern in the current iteration period according to all the master node difference degrees, all the slave node difference degrees and the initial difference degrees, wherein the initial difference degrees are difference degrees between an imaging pattern and a target pattern generated by the mask pattern before updating under the irradiation of the target light source;
The third determining module is used for taking the optimization result as a mask pattern of the next iteration period and entering the next iteration period when the optimization result is determined to be not in accordance with the preset iteration optimization condition;
or stopping the optimization operation when the optimization result is determined to meet the preset iterative optimization condition.
In a third aspect, the present application provides an exposure apparatus applied to a chip preparation process, including a memory and a processor, where the memory and the processor are communicatively connected to each other, and the memory stores computer instructions, and the processor executes the computer instructions, thereby executing the optimization method of the mask pattern.
In a fourth aspect, the present application provides a computer-readable storage medium having stored thereon computer instructions for causing a computer to perform the above-described mask pattern optimization method.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present application, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic view of a structure of an exposure apparatus applied to a chip manufacturing process according to an embodiment of the present application;
FIG. 2 is a flow chart of a method of optimizing a mask pattern according to an embodiment of the present application;
FIG. 3 is a flow chart of another method of optimizing a mask pattern according to an embodiment of the present application;
FIG. 4 is a flow chart of yet another method of optimizing a mask pattern according to an embodiment of the present application;
FIG. 5 is a block diagram of a mask pattern optimizing apparatus according to an embodiment of the present application;
fig. 6 is a schematic diagram of a hardware configuration of still another exposure apparatus according to an embodiment of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
It should be understood that the "indication" mentioned in the embodiments of the present application may be a direct indication, an indirect indication, or an indication having an association relationship. For example, a indicates B, which may mean that a indicates B directly, e.g., B may be obtained by a; it may also indicate that a indicates B indirectly, e.g. a indicates C, B may be obtained by C; it may also be indicated that there is an association between a and B.
In the description of the embodiments of the present application, the term "corresponding" may indicate that there is a direct correspondence or an indirect correspondence between the two, or may indicate that there is an association between the two, or may indicate a relationship between the two and the indicated, configured, etc.
In the embodiment of the present application, the "predefining" may be implemented by pre-storing corresponding codes, tables or other manners that may be used to indicate relevant information in devices (including, for example, terminal devices and network devices), and the present application is not limited to the specific implementation manner thereof.
With the rapid development of the information technology industry, chip feature sizes continue to shrink along with moore's law, where photolithography plays an extremely important role. The accurate photoetching technology not only determines the quality and performance of the chip, but also reduces the production cost.
The calculation holographic lithography is to utilize the diffraction principle of light, simulate and obtain a holographic mask plate by means of a computer high-efficiency numerical method, and irradiate the holographic mask plate by adopting a selected light source to form a target pattern on the surface of a wafer so as to realize exposure. In principle, a holographic mask is essentially different from a traditional projection type photoetching mask, the traditional projection type photoetching mask is basically consistent with an imaged space image and corresponds to each other point to point, in the computational holographic photoetching technology, the imaged space image (namely an imaging pattern) is difficult to identify through the holographic mask, one point on the space image is contributed by diffraction and interference of all pixel points of a mask pattern on the holographic mask, and the space image is insensitive to local defects of the mask pattern on the holographic mask. The characteristics reduce the processing difficulty of the holographic mask plate and the use and maintenance cost. On the other hand, the imaging process does not need a lens, so that the manufacturing difficulty and the processing cost of the holographic photoetching machine are greatly reduced.
The optimization of the mask pattern of the holographic mask is a key technology in calculating holographic lithography, and most of the existing mask processing technologies are considered to be binary amplitude masks, namely, only light-transmitting and light-non-transmitting areas exist on the mask, or binary phase masks, namely, the mask is fully light-transmitting, but the phase of some areas can be changed after light passes through. As a direct search algorithm of one of many binary mask optimization methods, the method can be used for directly evaluating the contribution of all pixel points on the mask to an imaging pattern, so that the method can often obtain a better solution than other iterative methods, and can be better combined with other methods, such as simulated annealing and the like, so as to obtain a better solution. However, this method has essentially a time dependence, i.e. the evaluation of new pixels on the mask pattern depends on the result of the previous pixel, and as the scale of the problem increases, the search space of the direct search algorithm becomes exponentially larger, and the computation time is unacceptable. To meet the manufacturing requirements of modern large-size chips, improvements are needed for optimization methods for mask patterns using direct search algorithms.
Fig. 1 is a schematic structural view of an exposure apparatus applied to a chip manufacturing process in an embodiment of the present application, the exposure apparatus including a master node 110 and at least one slave node 120, each of which has a mask pattern and a target pattern prestored therein.
The master node 110 and the slave node 120 are each processors having communication, storage, and data processing functions. Alternatively, the master node 110 and the slave node 120 are respectively graphics processors (Graphics Processing Unit, GPU) independent of each other, or the master node 110 and the slave node 120 are respectively data processors independent of each other, the data processors being composed of at least one central processor (Central Processing Unit, CPU) and at least one GPU. The master node is communicatively connected to each slave node to facilitate subsequent optimization operations of the mask pattern.
Alternatively, the master node 110 and at least one slave node 120 in the exposure apparatus may be disposed in the same computer apparatus of the exposure apparatus, or may be disposed in different computer apparatuses of the exposure apparatus, respectively.
Alternatively, the exposure apparatus may be a lithographic apparatus having a computer processing function, or a computer apparatus having a lithographic function.
Optionally, after optimization of the mask pattern is completed, a mask fabrication process may also be entered, and a reticle is fabricated based on the optimized mask pattern so that chip fabrication may be performed in the exposure apparatus using the newly fabricated reticle.
In the conventional optimization method of the mask pattern by using the direct search algorithm, the pixel value of a certain pixel point of the mask pattern on the holographic mask is usually changed once and again, so that the imaging quality change caused by the change of the pixel value of the pixel point is evaluated, and whether the pixel point change is received is judged, when the dimension of the mask pattern is larger, the pixel value of only one pixel point is changed at a time, and the evaluation time is obviously greatly increased once for evaluating all the pixel points on the mask pattern, so that the engineering requirement is difficult to meet. Therefore, the pixel values of the plurality of pixel points can be changed at one time, and various values of the pixel values of the plurality of pixel points can be distributed to different nodes for calculation, so that the time for evaluation is greatly shortened, and the optimization efficiency of the mask pattern is improved. As shown in fig. 2, fig. 2 is a flowchart illustrating a method for optimizing a mask pattern in an embodiment of the present application, which is used for an exposure apparatus, which may be the exposure apparatus shown in fig. 1, and which is performed by a master node in the exposure apparatus, which may be the master node 110 shown in fig. 1. The method may comprise the steps of:
in step 201, a first preset number of pixels are selected from the mask pattern in the current iteration period.
The exposure device comprises a master node and at least one slave node, wherein each node stores a target pattern and a mask pattern. The first preset number is a positive integer greater than or equal to 2, and may be set by itself, for example, 3 or 4, etc., which is not particularly limited in the embodiment of the present application, and the first preset number is denoted as N in the embodiment of the present application. The target pattern is a preset pattern to be printed on the wafer in the chip preparation process. The mask pattern is a pattern to be optimized on the holographic binary mask, and after the optimized mask pattern is subjected to light diffraction and interference under the irradiation of the target light source when the optimization operation of the mask pattern is finished, the formed imaging pattern is very close to or consistent with the target pattern. The target light source is a light source for lithography in an exposure apparatus. In the current iteration period, the master node randomly selects N pixel points from the mask pattern.
Step 202, according to a preset pixel value inversion rule, pixel values of pixel points at each position in a first preset number are inverted to obtain a plurality of element combinations.
The elements in each element combination correspond to states of positions of different pixel points in the first preset number. The preset pixel inversion rule is used for indicating the main node to determine whether to change the state of the position of the current pixel point. It should be noted that, the state of the position of the pixel point on the mask pattern is related to the type of the holographic binary mask, and when the holographic binary mask is the holographic binary amplitude mask, the state of the position of the pixel point on the mask pattern is transparent or opaque; when the holographic binary mask is a holographic binary phase mask, the state of the position of the pixel point on the mask pattern is that the phase of the position of the pixel point is 0, or the phase of the position of the pixel point is pi.
Whether the mask pattern is a pattern on a holographic binary amplitude mask or a pattern on a holographic binary phase mask, the states of the positions of each pixel point in the mask pattern are two, which means that the pixel value of each pixel point in the N pixel points is possible to be two, and the two states are used for indicating the positions of the pixel points. Therefore, the main node will have 2 when turning over the pixel value of the pixel point at each position of the N pixel points according to the preset pixel value turning rule N The possibility of the flip is obtained, so that the master node obtains 2 N And each element combination comprises N elements, and each element indicates the state of the corresponding pixel point in the mask pattern.
It should be noted that, the element pairs in each element combination are in one-to-one correspondence with the pixel points in the N pixel points, and the pixel points corresponding to the elements are recorded in each element combination. For example, 3 pixel points are selected in the mask pattern: p (i) p ，j p )，Q(i q ，j q ) R (i) r ，j r ). The master node is turning over P (i p ，j p )，Q(i q ，j q ) R (i) r ，j r ) After the pixel value of (2), 8 element combinations can be obtained, wherein each element combination has three elements, and three elements in a certain element combination are respectively element 0, element 1 and element 2, so that the element 0 in the element combination corresponds to P (i) p ，j p ) Element 1 corresponds to Q (i q ，j q ) Element 2 corresponds to R (i r ，j r )。
Step 203, distributing part of element combinations in the element combinations to at least one slave node, so that different slave nodes respectively determine the slave node difference degree between a new imaging pattern and the target pattern according to the received elements in each element combination and the mask pattern.
Wherein each new imaging pattern is generated based on elements in one element combination and the mask pattern. The slave node difference degree determined by each slave node is used for indicating the proximity degree between the new imaging pattern corresponding to the element combination received by the slave node and the target pattern stored by the slave node.
The master node will store 2 N Some of the element combinations, the remaining element combinations are distributed to at least one slave node. Thus, different slave nodes calculate pixel values of pixel points corresponding to each element in each element combination according to the state of the pixel points corresponding to the element indicated by each element in each element combination in the mask pattern, so as to modify the mask pattern stored by the slave nodes, calculate an imaging pattern corresponding to the modified mask pattern, and obtain a new imaging pattern, so that the slave node difference degree between the new imaging pattern and the target pattern is calculated by using the same method (the method is described in the following embodiments) as the master node until each element combination is calculated, and feed back the calculated slave node difference degree to the master node.
It should be noted that, the slave node may calculate, based on any one of the mask imaging calculation methods applied to the calculation holographic lithography, an imaging pattern of the modified mask pattern after the irradiation of the target light source, that is, a new imaging pattern, based on the pixel value of the target pixel point, the diffraction rule of the light, and the modified mask pattern.
Step 204, determining a degree of difference between the new imaging pattern and the target pattern according to the elements in each element combination stored in the master node and the mask pattern.
Each primary node difference degree determined by the primary node is used for indicating the proximity degree between a new imaging pattern corresponding to the element combination stored by the primary node and a target pattern stored by the primary node.
The master node calculates a pixel value of a pixel point corresponding to each element in each element combination according to the state of the pixel point corresponding to the element indicated by the element in each element combination stored in the master node in the mask pattern, so as to modify the mask pattern stored in the master node. And then calculating an imaging pattern corresponding to the modified mask pattern by using a mask imaging calculation method which is the same as that of the slave node, so as to obtain a new imaging pattern, thereby calculating the difference degree of the master node between the new imaging pattern and the target pattern until each element combination is calculated.
Step 205, obtaining the slave node difference degree fed back by all the slave nodes.
The master node receives the slave node difference degree fed back by all the slave nodes.
Step 206, determining the optimization result of the mask pattern in the current iteration period according to the difference degrees of all the master nodes, the difference degrees of all the slave nodes and the initial difference degrees.
Wherein the initial degree of difference is a degree of difference between an imaging pattern generated by the mask pattern before updating under irradiation of the target light source and the target pattern. The master node finds an imaging pattern closest to the target pattern from all the master node differences, all the slave node differences and the initial differences, and further determines a mask pattern corresponding to the imaging pattern as an optimization result of the current iteration period.
And step 207, when the optimization result is determined not to meet the preset iterative optimization condition, taking the optimization result as a mask pattern of the next iterative period, and entering the next iterative period.
Or stopping the optimization operation when the optimization result is determined to meet the preset iterative optimization condition.
After determining the optimization result in the current iteration period, the master node also determines whether the optimization result meets the preset optimization iteration condition so as to determine whether to continue the optimization operation. The preset iterative optimization conditions in the embodiment of the application are set to at least one of the degree of difference between the imaging pattern and the target pattern which is kept unchanged, the degree of difference between the imaging pattern and the target pattern which is changed less, and the definition and the resolution of the imaging pattern corresponding to the optimization result which meet the preset values, so that the optimization operation is stopped. The preset value can be designed by itself, the embodiment of the application is not particularly limited, in addition, the definition and resolution of the imaging pattern are part of the index of the pattern quality of the imaging pattern, and other pattern quality indexes can be set by itself.
In the embodiment of the application, a plurality of nodes are arranged in the exposure equipment, and the target pattern and the mask pattern are stored in each node, so that different nodes in the system can be ensured to independently operate according to the data stored by the nodes. In this way, in the current iteration period, the master node selects a first preset number of pixel points from the mask patterns stored by the master node, and according to a preset pixel value overturning rule, the pixel value of each pixel point in the first preset number is overturned to obtain a plurality of element combinations, and then part of element combinations in the plurality of element combinations can be distributed to at least one slave node. And the elements in each element combination correspond to the states of the positions of different pixel points in the first preset number, so that the master node and the different slave nodes can independently and parallelly determine the difference degree between a new imaging pattern and the target pattern according to the elements in each element combination representing different states and the mask patterns stored by the master node and the different slave nodes, so that the optimization result of the preset mask patterns in the current iteration period is determined according to the difference degree determined by all the nodes, and whether the optimization operation is stopped is determined. The method realizes the calculation of the difference degree of the imaging pattern and the target pattern corresponding to the element combination stored by the nodes in parallel, and the difference degree between the imaging pattern and the target pattern corresponding to the mask pattern is greatly accelerated after the state change of the position of a certain pixel point in the mask pattern is calculated again and again as in the traditional direct searching algorithm, so that the calculation efficiency of the difference degree is greatly accelerated, and the optimization efficiency of the mask pattern is accelerated. For example, if N pixel points are selected, through the above steps, the master node and the slave node can simultaneously realize the evaluation of N pixel points on the mask pattern, and if the total number of pixel points on the mask pattern is M, the number of calculation times required for completing one evaluation of all pixel points on the mask pattern is about M/N, so that the calculation speed can achieve N times of acceleration, and the optimization efficiency is greatly improved.
In order to improve the optimization efficiency of the mask pattern while also saving the communication cost between nodes, another optimization method of the mask pattern is proposed, as shown in fig. 3, for an exposure apparatus, which may be the exposure apparatus shown in fig. 1, which is performed by a master node in the exposure apparatus, which may be the master node 110 shown in fig. 1. The method may comprise the steps of:
step 301, selecting a first preset number of pixel points from the mask pattern in the current iteration period.
Please refer to step 201 in the embodiment shown in fig. 2 in detail, which is not described herein.
Optionally, before selecting the first preset number of pixels from the mask pattern, the master node further initializes the phase and amplitude of each pixel in the mask pattern and the target pattern, respectively;
and determining the phase and amplitude corresponding to each pixel point in the mask pattern and the target pattern stored by the slave nodes respectively.
When the mask pattern is a pattern on the holographic binary amplitude mask, the master node randomly assigns 0 or 1 to the amplitude of each pixel point in the mask pattern, and assigns the phase of each pixel point as a constant; when the mask pattern is a pattern on the holographic binary phase mask, the master node randomly assigns 0 or pi to the phase of each pixel point in the mask pattern, and assigns the amplitude of each pixel point as a constant, so that the initialization of the mask pattern is completed, and the pixel values H (i, j) of each pixel point in the mask pattern are obtained. The master node calculates the pixel value P (m, n) of each pixel point in the target pattern based on any existing pixelation method of the target pattern. When the master node receives the initialization completion information fed back by each slave node, the master node determines the phase and amplitude corresponding to each pixel point in the mask pattern and the target pattern stored by the master node respectively. Wherein (m, n) represents the coordinate values of the pixel points in the target pattern, and (i, j) represents the coordinate values of the pixel points in the mask pattern. Before selecting a first preset number of pixels from the mask pattern refers to before the beginning of a first iteration cycle of mask pattern optimization.
It can be understood that when the master node initializes the mask pattern and the target pattern respectively, the slave node also initializes the phase and the amplitude corresponding to each pixel point in the mask pattern and the target pattern stored by itself respectively using the same initialization method as the master node, so as to obtain the pixel value H (i, j) of each pixel point in the mask pattern stored by itself and the pixel value P (m, n) of each pixel point in the target pattern, and sends initialization completion information to the master node after the initialization is completed, so as to facilitate the efficient optimization of the mask pattern.
The master node determines that the slave node independently initializes the mask pattern and the target pattern stored by the master node, and does not send the initialized mask pattern and target pattern to different slave nodes through a communication network, so that the transmission of high-dimension pattern data is avoided, and the communication cost can be saved.
Optionally, after initializing the mask pattern and the target pattern, the master node further calculates an imaging pattern generated by the initialized mask pattern under the irradiation of the target light source according to the diffraction rule of the light and the pixel values H (i, j) of each pixel point in the initialized mask pattern (i.e. the mask pattern before updating) based on the mask pattern imaging calculation method used in the embodiment shown in fig. 2, to obtain the pixel values E of each pixel point of the imaging pattern 0 (m, n) and then the pixel value E of each pixel point of the imaging pattern 0 (m, n) substituting the pixel value P (m, n) of each pixel point in the target pattern into the formulaCalculate the initial degree of difference loss 0 ，/>Representing the pixel value of the j-th pixel point in the imaging pattern generated by the initialized mask pattern under the irradiation of the target light source,/for the imaging pattern>And (3) representing the pixel value of the j-th pixel point in the target pattern, and n represents the total number of all pixel points in the target pattern so as to facilitate the subsequent optimization of the mask pattern.
Optionally, in order to improve the optimization efficiency of the mask pattern, step 301, selecting a first preset number of pixels from the mask pattern in the current iteration period may include:
a first preset number of pixel points is selected from the mask pattern based on a direct search algorithm.
Wherein the first preset number is a positive integer greater than or equal to 2. The master node may select N pixel points in the mask pattern based on a direct search algorithm, which may be a linear frequency modulation Scaling (CS), a generalized mode search (generalised pattern search, GPS), or a grid adaptive direct search (mesh adaptive direct search, MADS), which is not particularly limited in the embodiment of the present application.
Therefore, when the mask pattern is optimized later, the pixel values of at least two pixel points can be changed at one time by utilizing a direct search algorithm, so that the degree of difference of a plurality of pixel points after being changed is calculated at one time later, the defect that the pixel value of one pixel point is only changed each time and then is evaluated is avoided, the time consumption of evaluating all the pixel points on the mask pattern at one time can be greatly reduced, and the mask pattern optimization efficiency is improved.
Step 302, according to a preset pixel value inversion rule, pixel values of pixel points at each position in a first preset number are inverted to obtain a plurality of element combinations.
Please refer to step 202 in the embodiment shown in fig. 2 in detail, which is not described herein.
Optionally, in order to save the communication cost of mask pattern optimization, step 302, according to a preset pixel value inversion rule, inverting the pixel value of the pixel point at each position in the first preset number to obtain a plurality of element combinations may include the following steps 3021 to 3022:
in step 3021, based on the plurality of candidate pixel values corresponding to each pixel in the first preset number, the first preset number of pixels are combined to obtain a plurality of pixel combinations.
The mask pattern is a pattern on the holographic binary mask, and each pixel point combination consists of a first preset number of pixel points. Each pixel point in the mask pattern corresponds to 2 candidate pixel values. If the pattern on the holographic binary amplitude reticle is masked with a pattern, the 2 candidate pixel values may be an amplitude value (e.g., 0) for light transmission indicating where the pixel is located, and an amplitude value (e.g., 1) for light non-transmission indicating where the pixel is located; if the pattern is on a holographic binary phase reticle when the pattern is masked, the 2 candidate pixel values would be 2 different phase values (e.g., 0 and pi), respectively.
It should be noted that, besides 0 and pi, the 2 candidate pixel values of the pixel points in the holographic binary phase mask may be other self-set candidate pixel values, for example, 0 and pi/2, or pi/2 and pi, etc. The 2 candidate pixel values of the pixel point in the holographic binary amplitude mask plate can be other candidate pixel values which are set by themselves besides indicating the light transmission and the light non-transmission of the position of the pixel point, for example, indicating the semi-light transmission and the light non-transmission of the position of the pixel point.
The main node combines the N pixel points according to a rule that the pixel value of one pixel point is taken as one candidate pixel value based on selecting a plurality of candidate pixel values corresponding to each of the N pixel points, so as to traverse all possible values of the pixel values of the N pixel points, thereby obtaining 2 N And combining the pixel points. For example, when the pattern is a holographic binary phase mask, and N is 2,the 2 candidate pixel values corresponding to the 2 selected pixel points are respectively 0 and pi, and the main node combines the 2 pixel points according to the rule that the pixel value of one pixel point takes 0 or pi, so that 2 can be obtained 2 The combination of 4 pixels is (0, 0), (0, pi), (pi, 0), and (pi, pi), respectively.
Step 3022, determining a change in the state of the position of each pixel in each pixel combination according to the pixel value of each pixel in each pixel combination and the initial pixel value of each pixel in the first preset number, and representing the change in a binary form to obtain an element combination corresponding to each pixel combination.
The initial pixel value is the pixel value of the pixel point in the mask pattern before updating. In the current iteration period, the main node respectively obtains initial pixel values of N pixel points when N pixel points are selected from the mask pattern, and then the main node compares whether the candidate pixel value obtained by each pixel point in each pixel point combination is consistent with the initial pixel value of the pixel point, if so, the state of the position of the pixel point is unchanged, if not, the state of the position of the pixel point is changed, and if so, the state of the position of the pixel point is changed. The main node will not change the state of the pixel point (i.e. the pixel value of the pixel point is not changed) with a binary 0, and change the state of the pixel point (i.e. the pixel value of the pixel point is changed to another state) with a binary 1, and change the state to opaque (or pi) if the original state is transparent (or pi), and change the state to transparent (or 0) if the original state is opaque (or pi). And combining binary representations corresponding to state changes of all the positions of the pixels in one pixel combination according to the arrangement sequence of the pixels in the pixel combination to obtain an N-bit binary number, namely an element combination corresponding to the pixel combination, wherein each bit binary number is only an element in one element combination.
For example, the master node randomly selects N pixels on the maskThe pixel value of the dot is 2 N Possibility, if represented by binary numbers, is 0-2 N-1 I.e., 000.000, 000.001, 111.111, wherein 0 indicates that the pixel value of a pixel at a position in the mask pattern is unchanged, 1 indicates that the pixel value of a pixel at a certain position in the mask pattern becomes another state.
Based on a plurality of candidate pixel values corresponding to each pixel point in the first preset number, combining the pixel points in the first preset number to obtain a plurality of pixel point combinations, and traversing all possible values of the pixel points after the plurality of pixel points are selected. And then, according to the pixel value of each pixel in each pixel combination and the initial pixel value of each pixel in the first preset number, the state change of the position of each pixel in each pixel combination is respectively determined, and the change is expressed in a binary form, so that the element combination corresponding to each pixel combination is obtained, and the element combination in the binary form is obtained, so that only one or more binary numbers can be conveniently transmitted when data are transmitted to different slave nodes in the subsequent process, the transmission of the pixel values of a plurality of pixels is avoided, the communication pressure is reduced, and the communication cost is saved.
Step 303, distributing part of element combinations in the element combinations to at least one slave node, so that different slave nodes respectively determine the slave node difference degree between a new imaging pattern and a target pattern according to the received element in each element combination and the mask pattern.
Please refer to step 203 in the embodiment shown in fig. 2 in detail, which is not described herein.
Step 304, determining a degree of difference between the new imaging pattern and the target pattern according to the elements in each element combination stored in the master node and the mask pattern.
Please refer to step 204 in the embodiment shown in fig. 2 in detail, which is not described herein.
Optionally, step 304, determining a difference degree of the main node between a new imaging pattern and the target pattern according to the elements in each element combination stored in the main node and the mask pattern, respectively, may further include:
respectively modifying the pixel values of the first preset number of pixel points in the mask pattern according to the elements in each element combination stored in the main node and the initial pixel values of each pixel point in the first preset number to obtain an updated mask pattern;
According to the pixel value of each pixel point in each updated mask pattern and the diffraction rule of light, respectively determining a new imaging pattern corresponding to each updated mask pattern;
and respectively determining the difference degree of the main node between each new imaging pattern and the target pattern according to the pixel value of each pixel point in each new imaging pattern and the pixel value of each pixel point in the target pattern.
The master node determines whether the state of the pixel point corresponding to each element is changed according to whether each element in each stored element combination is 0 or 1, if so, the initial pixel value of the pixel point in the mask pattern is modified to be a pixel value which can indicate another state of the pixel point, and if not, the initial pixel value of the pixel point is kept unchanged. Thereby obtaining an updated mask pattern. Then using the same mask imaging calculation method as the slave node, determining a new imaging pattern corresponding to each updated mask pattern according to the pixel value of each pixel point in each updated mask pattern and the diffraction rule of light. And substituting the pixel value of each pixel point in each new imaging pattern and the pixel value of each pixel point in the target pattern into the formula A master node differential between each new imaged pattern and the target pattern is calculated. Wherein loss is i Representing the degree of difference corresponding to the ith element combination,/->Representation ofAnd the pixel value of the jth pixel point in the new imaging pattern, i represents the ith element combination in the multiple element combinations, the value of i is 0 to N-1, and N is a first preset number.
The pixel values of the first preset number of pixel points in the mask pattern are modified based on the stored elements in each element combination and the initial pixel values of each pixel point in the first preset number, so that updated mask patterns corresponding to different element combinations are obtained, a new imaging pattern corresponding to each updated mask pattern is determined, the difference degree of a main node between each new imaging pattern and a target pattern is calculated, and the possible evaluation of different values of the pixel points stored by the mask pattern is realized.
Optionally, when each of the master node and the slave node calculates the difference between a new imaging pattern and the target pattern, the element combination related in the calculation is associated with the difference obtained in the calculation, so as to facilitate the subsequent acquisition of the element combination corresponding to the minimum difference.
Optionally, when the total number of element combinations is consistent with the number of all nodes in the exposure device, the master node may store one element combination and respectively distribute a remaining element combination to each slave node, so that all nodes may independently calculate the difference degree corresponding to one element combination in parallel, thereby further accelerating the efficiency of mask optimization.
Alternatively, the master node may distribute the plurality of element combinations to at least two slave nodes instead of storing the element combinations, so that the slave nodes perform subsequent computation of the degree of difference, and it will be understood that at this time, the exposure apparatus should further include at least two slave nodes, and the master node performs steps consistent with the steps when the master node needs to store the element combinations except that the master node does not perform computation of the degree of difference. When the number of all the slave nodes is consistent with the total number of the element combinations, the master node can respectively distribute one element combination to each slave node.
For example, when the exposure apparatus includes 2, taking the loss between the imaging pattern and the target pattern as the slave node difference degree N Slave nodesWhen the master node selects N pixel points, 2 is obtained N After the elements are combined, 2 can be obtained N The element combinations are respectively distributed to 2 N The slave nodes, after receiving the element combination, are independently responsible for calculating the pixel values of the pixel points in the mask pattern corresponding to the element combination received by the slave nodes, so as to obtain a new imaging pattern E after the pixel values of the corresponding pixel points are changed i (m, n) by E i (m, n) calculating loss i The slave nodes calculate the loss i Sent back to the master node, where s represents 2 N An s-th slave node among the slave nodes.
Through the steps, the evaluation of N pixel points on the mask pattern can be realized at the same time, compared with the traditional direct search algorithm, N pixel points are selected at one time, and different values of N pixel points are evaluated on different nodes, so that the search space of the algorithm is changed from original 1 to 2 N Further accelerating convergence and improving the quality of knowledge. In principle, if there are enough compute nodes, a globally optimal solution for a given problem can be found in one step.
Step 305, obtaining the slave node difference degree fed back by all the slave nodes.
Please refer to step 205 in the embodiment shown in fig. 2 in detail, which is not described herein.
Step 306, determining the optimization result of the mask pattern in the current iteration period according to the difference degrees of all the master nodes, the difference degrees of all the slave nodes and the initial difference degrees.
Please refer to step 206 in the embodiment shown in fig. 2 in detail, which is not described herein.
Optionally, in step 306, determining the optimization result of the mask pattern in the current iteration period according to the difference degrees of all the master nodes, the difference degrees of all the slave nodes and the initial difference degrees may include:
selecting the minimum difference degree with the smallest numerical value from all the master node difference degrees, all the slave node difference degrees and the initial difference degrees, and determining the value of the initial difference degree as the value of the minimum difference degree;
acquiring an element combination corresponding to the minimum difference degree, modifying the pixel values of the first preset number of pixel points in the mask pattern according to the element in the element combination corresponding to the minimum difference degree and the initial pixel value of each pixel point in the first preset number, and determining the modified mask pattern as an optimization result.
The difference degree of the master node and the difference degree of the slave node can be recorded as loss i The master node compares each loss i And loss of 0 The size of the two when compared to less than loss 0 Is of (1) i When it is, make loss 0 =loss i Up to all loss i After the comparison is completed, the minimum difference degree loss with the minimum value can be found min And obtain loss of 0 =loss min Is used for the initial degree of difference of (a). The master node compares the minimum difference with each difference calculated by itself to determine whether the minimum difference is the difference calculated by the master node itself, and if so, reads the element combination corresponding to the minimum difference, and further modifies the pixel values of the first preset number of pixels in the mask pattern based on the process similar to step 304, and determines the modified mask pattern as an optimization result.
If the minimum difference degree calculated by the master node is not the minimum difference degree calculated by the master node, the master node sends the minimum difference degree to all the slave nodes so that all the slave nodes can determine whether the minimum difference degree is the loss of self calculation or not, and if so, the master node returns the element combination corresponding to the minimum difference degree.
It can be understood that when the master node does not have a storage element combination and does not perform the difference calculation, the master node directly sends the minimum difference to all the slave nodes after receiving the difference fed back by all the slave nodes and determining the minimum difference.
And selecting the minimum difference degree with the minimum numerical value from all the node difference degrees and the initial difference degrees, wherein the minimum difference degree means that the new imaging pattern is closer to the target pattern, so that the mask pattern corresponding to the new imaging pattern can be used as an optimization result.
Step 307, distributing the element combination corresponding to the minimum difference degree to different slave nodes, so that the different slave nodes update the mask patterns stored by themselves according to the element in the element combination corresponding to the minimum difference degree and the initial pixel value of each pixel point in the first preset number.
After the master node determines the optimization result of the current iteration period, the element combination corresponding to the minimum difference degree is distributed to all the slave nodes in the exposure equipment, so that each slave node can timely update the mask pattern stored by itself according to the element in the element combination corresponding to the minimum difference degree, and when the master node continues to perform the optimization operation, the mask pattern can be operated aiming at the latest updated mask pattern, and the mask pattern optimization accuracy is ensured.
Step 308, when it is determined that the optimization result does not meet the preset iterative optimization condition, taking the optimization result as a mask pattern of the next iterative period, and entering the next iterative period;
or stopping the optimization operation when the optimization result is determined to meet the preset iterative optimization condition.
Please refer to step 207 in the embodiment shown in fig. 2 in detail, which is not described herein.
In the embodiment of the application, the master node instructs the slave nodes to independently initialize the mask patterns and the target patterns stored by the master node, and the initialized mask patterns and target patterns are not transmitted to different slave nodes through a communication network, so that the transmission of high-dimensional pattern data is avoided, and the communication cost can be saved. When the mask pattern is optimized, the pixel values of at least two pixel points are changed at one time by utilizing a direct search algorithm, and the calculation of the difference degree is independently carried out by a plurality of nodes in parallel, so that the defect that the evaluation is carried out after only changing the pixel value of one pixel point at a time can be avoided, the search space can be increased, the quality of the solution is improved, and a better solution can be found while the time consumption of evaluating all the pixel points on the mask pattern at one time is greatly reduced. And when the difference degree is calculated, the main node combines the first preset number of pixel points based on a plurality of candidate pixel values corresponding to each pixel point in the first preset number, so as to obtain a plurality of pixel point combinations, and the traversal of all possible values of the pixel points after the plurality of pixel points are selected is realized. And then, according to the pixel value of each pixel in each pixel combination and the initial pixel value of each pixel in the first preset number, the state change of the position of each pixel in each pixel combination is respectively determined, and the change is expressed in a binary form, so that the element combination corresponding to each pixel combination is obtained, and the element combination in the binary form is obtained, so that only one or more binary numbers can be conveniently transmitted when data are transmitted to different slave nodes in the subsequent process, the transmission of the pixel values of a plurality of pixels is avoided, the communication pressure is reduced, and the communication cost is saved.
In an application scenario, taking a master node not participating in difference degree calculation, the difference degree is taken as a loss, a mask pattern is taken as a holographic binary amplitude mask plate as an example, one master node and 8 slave nodes are arranged in exposure equipment, and each slave node can call an independent graphics processor. The optimization procedure of the mask pattern may be as follows:
step 1, initializing a mask pattern, so that certain areas on the mask transmit light and certain areas do not transmit light, and obtaining the initial mask pattern. Setting a target light fieldWherein A represents amplitude, < >>Indicate phase, & gt>Representing the imaginary unit, thereby completing the patterning of the object;
step 2, calculating an imaging pattern corresponding to the initial mask pattern according to the diffraction rule of the light by using the pixel values H (i, j) of all the pixel points in the initialized mask pattern to obtain the pixel value E of all the pixel points in the imaging pattern 0 (m, n), and calculating an initial loss between the imaging pattern corresponding to the initialized mask pattern and the target pattern；
Step 3, randomly selecting 3 pixel points on the mask pattern by the main node based on a direct search algorithm: p (i) p ，j p )，Q(i q ，j q ) R (i) r ，j r ) Then the 3 pixel points correspond to 8 element combinations, see table 1:
table 1, pixel point corresponding element combinations and losses determined from each slave node
Step 4, the master node distributes the 8 element combinations to be evaluated to the slave nodes 0 to 7 respectively, each slave node calculates a new imaging pattern corresponding to the received element combination respectively, and calculates loss between the new imaging pattern and the target pattern 0 To loss of 7 After the calculation is finished, the slave nodes send the losses obtained by the slave nodes to the master node;
step 5, the master node receives loss sent by each slave node 0 To loss of 7 Comparing the magnitude of the losses, taking the minimum loss min The corresponding element combination and coordinate value of the mask pattern is (i) p ，j p )，(i q ，j q ) (i) r ，j r ) The pixel value of the pixel point of (2) is changed and loss is reduced min Assigning a value to loss 0 ，loss 0 =loss min ；
Step 6, returning to the step 3, and selecting three pixel points to be evaluated in the next round until loss 0 The final optimized mask pattern data (i.e., the final optimization result) is output without any degradation or image quality meeting the requirements.
Through the steps, the evaluation of N pixel points on the mask can be realized at the same time, and the total number of pixels of the mask is M, so that the calculation times required by the completion of one-time evaluation of all pixel points on the mask is about M/N, the calculation speed can be accelerated by N times, and meanwhile, compared with the traditional direct search method, the search space is changed from 1 to 1 Is 2 N Further accelerating convergence and improving the quality of knowledge. In principle, if there are enough compute nodes, a globally optimal solution for a given problem can be found in one step.
Fig. 4 is a flowchart of a method of optimizing a mask pattern in an embodiment of the present application, which is used for an exposure apparatus, which may be the exposure apparatus shown in fig. 1, and which is performed by a slave node in the exposure apparatus, which may be any of the slave nodes 120 shown in fig. 1. The method may comprise the steps of:
in step 401, each element combination sent by the master node is received in the current iteration period, and a first preset number of pixel points selected by the master node in the mask pattern are determined.
When the master node transmits the element combination, the coordinate value of the pixel point corresponding to each element in the element combination is also transmitted to the slave node, and the slave node can determine N pixel points selected by the master node in the mask pattern according to the coordinate values.
Optionally, before each element combination sent by the master node is received and a first preset number of pixel points selected by the master node in the mask pattern are determined, the slave node also uses an initializing method identical to that of the master node to initialize the mask pattern and the target pattern stored by the slave node respectively, and the specific initializing process is similar to that of the master node and will not be described herein.
Step 402, determining a slave node difference degree between a new imaging pattern and the target pattern according to the elements in each element combination and the mask pattern, and feeding back the determined slave node difference degree to the master node.
The process of determining the degree of difference between a new imaging pattern and the target pattern from the node is similar to step 304 in the embodiment shown in fig. 3, and will not be described in detail herein.
Step 403, receiving an element combination corresponding to the minimum difference sent by the master node, and updating the mask pattern stored by the master node according to the element in the element combination corresponding to the minimum difference and the initial pixel value of each pixel in the first preset number.
The process of updating the mask pattern stored by the slave node according to the element combination corresponding to the minimum difference is similar to the process of modifying the pixel values of the first preset number of pixel points in the mask pattern by the master node in step 304 in the embodiment shown in fig. 3, and will not be described in detail herein.
In the embodiment of the application, the slave node respectively determines the difference degree between a new imaging pattern and the target pattern after receiving the element combination sent by the master node, and feeds the determined difference degree back to the master node, and after receiving the element combination corresponding to the minimum difference degree sent by the master node, the slave node can independently update the mask pattern stored by itself, thereby realizing the independent data processing of the slave node and the master node, and improving the optimization efficiency of the mask pattern.
Fig. 5 is a block diagram showing the structure of an optimizing apparatus for mask patterns according to an embodiment of the present application. The mask pattern optimizing apparatus is applied to an exposure device, the system includes a master node and at least one slave node, each node stores a target pattern and a mask pattern, the apparatus is executed by the master node, the mask pattern optimizing apparatus includes:
a selecting module 510, configured to select a first preset number of pixel points from the mask pattern in a current iteration period;
the overturning module 520 is configured to overturn the pixel values of the pixel points at each position in the first preset number according to a preset pixel value overturning rule, so as to obtain a plurality of element combinations, where the elements in each element combination correspond to the states of the positions of the different pixel points in the first preset number;
a distribution module 530 for distributing a part of the element combinations among the plurality of element combinations to at least one slave node, so that different slave nodes respectively determine slave node differences between a new imaging pattern and the target pattern according to the received element and mask pattern in each element combination, each new imaging pattern being generated based on the element and mask pattern in one element combination;
A first determining module 540, configured to determine a degree of difference between a new imaging pattern and the target pattern according to the mask pattern and the elements in each element combination stored in the master node;
an obtaining module 550, configured to obtain slave node differences fed back by all slave nodes;
a second determining module 560, configured to determine an optimization result of the mask pattern in the current iteration period according to all the master node differences, all the slave node differences, and an initial difference, where the initial difference is a difference between an imaging pattern generated by the mask pattern before updating under irradiation of the target light source and the target pattern;
a third determining module 570, configured to, when it is determined that the optimization result does not meet the preset iterative optimization condition, take the optimization result as a mask pattern of a next iteration cycle, and enter the next iteration cycle;
or stopping the optimization operation when the optimization result is determined to meet the preset iterative optimization condition.
In some alternative embodiments, the flipping module comprises:
the combination unit is used for combining the first preset number of pixel points based on a plurality of candidate pixel values corresponding to each pixel point in the first preset number, so as to obtain a plurality of pixel point combinations, wherein each pixel point combination is composed of the first preset number of pixel points;
The first determining unit is configured to determine, according to a pixel value of each pixel in each pixel combination and an initial pixel value of each pixel in a first preset number, a change in a state of a position where each pixel in each pixel combination is located, and represent the change in a binary form, so as to obtain an element combination corresponding to each pixel combination, where the initial pixel value is a pixel value of a pixel in the mask pattern before updating.
In some alternative embodiments, the first determining module includes:
the modification unit is used for respectively modifying the pixel values of the first preset number of pixel points in the mask pattern according to the elements in each element combination stored in the main node and the initial pixel values of each pixel point in the first preset number to obtain an updated mask pattern;
a second determining unit, configured to determine a new imaging pattern corresponding to each updated mask pattern according to a pixel value of each pixel point in each updated mask pattern and a diffraction rule of light;
the second determining unit is further configured to determine a degree of difference of the main node between each new imaging pattern and the target pattern according to the pixel value of each pixel point in each new imaging pattern and the pixel value of each pixel point in the target pattern.
In some alternative embodiments, the second determining module includes:
the selection unit is used for selecting the minimum difference degree with the smallest numerical value from all the master node difference degrees, all the slave node difference degrees and the initial difference degrees, and determining the value of the initial difference degree as the value of the minimum difference degree;
the obtaining unit is used for obtaining the element combination corresponding to the minimum difference degree, modifying the pixel values of the first preset number of pixel points in the mask pattern according to the element in the element combination corresponding to the minimum difference degree and the initial pixel value of each pixel point in the first preset number, and determining the modified mask pattern as an optimization result.
In some optional embodiments, the distributing module is further configured to distribute the element combination corresponding to the minimum difference to different slave nodes, so that the different slave nodes update the mask pattern stored by themselves according to the element in the element combination corresponding to the minimum difference and the initial pixel value of each pixel point in the first preset number.
In some alternative embodiments, the optimizing means of the mask pattern further comprises:
the initialization module is used for initializing the phase and the amplitude of each pixel point in the mask pattern and the target pattern respectively;
The initialization module is further used for determining the phase and the amplitude corresponding to each pixel point in the mask pattern and the target pattern stored by the slave node respectively.
In some alternative embodiments, the selection module includes:
and a selection unit for selecting a first preset number of pixel points from the mask pattern based on a direct search algorithm, the first preset number being a positive integer greater than or equal to 2.
Further functional descriptions of the above respective modules and units are the same as those of the above corresponding embodiments, and are not repeated here.
The mask pattern optimizing means in this embodiment is presented in the form of functional units, here referred to as ASIC (Application Specific Integrated Circuit ) circuits, processors and memories executing one or more software or fixed programs, and/or other devices that can provide the above described functions.
The embodiment of the application also provides another exposure device, which is provided with the optimization device of the mask pattern shown in the figure 5.
Referring to fig. 6, fig. 6 is a schematic structural diagram of another exposure apparatus according to an alternative embodiment of the present application, as shown in fig. 6, the exposure apparatus includes: one or more processors 10, memory 20, and interfaces for connecting the various components, including high-speed interfaces and low-speed interfaces. The various components are communicatively coupled to each other using different buses and may be mounted on a common motherboard or in other manners as desired. The processor may process instructions executed within the exposure apparatus, including instructions stored in or on memory to display graphical information of the GUI on an external input/output device, such as a display apparatus coupled to the interface. In some alternative embodiments, multiple processors and/or multiple buses may be used, if desired, along with multiple memories and multiple memories. Also, multiple exposure apparatuses may be connected, each providing a portion of the necessary operations (e.g., as a server array, a set of blade servers, or a multiprocessor system). One processor 10 is illustrated in fig. 6.
The processor 10 may be a central processor, a network processor, or a combination thereof. The processor 10 may further include a hardware chip, among others. The hardware chip may be an application specific integrated circuit, a programmable logic device, or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general-purpose array logic, or any combination thereof.
Wherein the memory 20 stores instructions executable by the at least one processor 10 to cause the at least one processor 10 to perform the methods shown in implementing the above embodiments.
The memory 20 may include a storage program area that may store an operating system, at least one application program required for functions, and a storage data area; the storage data area may store data created according to the use of the exposure apparatus, and the like. In addition, the memory 20 may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, memory 20 may optionally include memory located remotely from processor 10, which may be connected to the exposure apparatus via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
Memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk, or solid state disk; the memory 20 may also comprise a combination of the above types of memories.
The exposure apparatus further comprises a communication interface 30 for the exposure apparatus to communicate with other apparatuses or communication networks.
The embodiments of the present application also provide a computer readable storage medium, and the method according to the embodiments of the present application described above may be implemented in hardware, firmware, or as a computer code which may be recorded on a storage medium, or as original stored in a remote storage medium or a non-transitory machine readable storage medium downloaded through a network and to be stored in a local storage medium, so that the method described herein may be stored on such software process on a storage medium using a general purpose computer, a special purpose processor, or programmable or special purpose hardware. The storage medium can be a magnetic disk, an optical disk, a read-only memory, a random access memory, a flash memory, a hard disk, a solid state disk or the like; further, the storage medium may also comprise a combination of memories of the kind described above. It will be appreciated that a computer, processor, microprocessor controller or programmable hardware includes a storage element that can store or receive software or computer code that, when accessed and executed by the computer, processor or hardware, implements the methods illustrated by the above embodiments.
Although embodiments of the present application have been described in connection with the accompanying drawings, various modifications and variations may be made by those skilled in the art without departing from the spirit and scope of the application, and such modifications and variations fall within the scope of the application as defined by the appended claims.

Claims (10)

1. An optimization method of a mask pattern, applied to an exposure apparatus of a chip preparation process, characterized in that the exposure apparatus includes a master node and at least one slave node, each node storing therein a target pattern and a mask pattern, the method being performed by the master node, the method comprising:
selecting a first preset number of pixel points from the mask pattern in the current iteration period;
according to a preset pixel value overturning rule, overturning the pixel value of each pixel point in the first preset number to obtain a plurality of element combinations, wherein elements in each element combination correspond to the states of the positions of different pixel points in the first preset number;
distributing part of element combinations in a plurality of the element combinations to at least one slave node so that different slave nodes respectively determine slave node difference degrees between a new imaging pattern and the target pattern according to the received elements in each element combination and the mask pattern, wherein each new imaging pattern is generated based on the elements in one element combination and the mask pattern;
Determining a master node difference between a new imaging pattern and the target pattern according to the elements in each element combination stored in the master node and the mask pattern;
obtaining slave node difference degrees fed back by all slave nodes;
determining an optimization result of the mask pattern in a current iteration period according to all master node differences, all slave node differences and an initial difference, wherein the initial difference is the difference between an imaging pattern generated by the mask pattern before updating under the irradiation of a target light source and the target pattern;
when the optimization result is determined to be not in accordance with a preset iterative optimization condition, taking the optimization result as a mask pattern of a next iterative period, and entering the next iterative period;
or stopping the optimization operation when the optimization result is determined to be in accordance with the preset iterative optimization condition.
2. The method of claim 1, wherein the mask pattern is a pattern on a holographic binary mask, and wherein flipping the pixel values of the pixel points at each position in the first preset number according to a preset pixel value flipping rule, to obtain a plurality of element combinations, comprises:
Combining the first preset number of pixel points based on a plurality of candidate pixel values corresponding to each pixel point in the first preset number, so as to obtain a plurality of pixel point combinations, wherein each pixel point combination is composed of the first preset number of pixel points;
according to the pixel value of each pixel in each pixel combination and the initial pixel value of each pixel in the first preset number, respectively determining the change of the state of the position of each pixel in each pixel combination, and representing the change in a binary form to obtain the element combination corresponding to each pixel combination, wherein the initial pixel value is the pixel value of the pixel in the mask pattern before updating.
3. The method of claim 2, wherein determining a master node difference between a new imaged pattern and the target pattern based on the mask pattern and the elements in each combination of elements stored in the master node, respectively, comprises:
respectively modifying the pixel values of the first preset number of pixel points in the mask pattern according to the elements in each element combination stored in the main node and the initial pixel values of each pixel point in the first preset number to obtain an updated mask pattern;
Determining a new imaging pattern corresponding to each updated mask pattern according to the pixel value of each pixel point in each updated mask pattern and the diffraction rule of light;
and respectively determining the difference degree of the main node between each new imaging pattern and the target pattern according to the pixel value of each pixel point in each new imaging pattern and the pixel value of each pixel point in the target pattern.
4. A method according to claim 2 or 3, wherein said determining the optimization result of the mask pattern in the current iteration period based on all master node differences, all slave node differences and initial differences comprises:
selecting the minimum difference degree with the smallest numerical value from all the master node difference degrees, all the slave node difference degrees and the initial difference degrees, and determining the value of the initial difference degree as the value of the minimum difference degree;
acquiring an element combination corresponding to the minimum difference degree, modifying the pixel values of the first preset number of pixel points in the mask pattern according to the elements in the element combination corresponding to the minimum difference degree and the initial pixel values of each pixel point in the first preset number, and determining the modified mask pattern as the optimization result.
5. The method of claim 4, wherein when it is determined that the optimization result does not meet a preset iterative optimization condition, taking the optimization result as a mask pattern for a next iteration cycle, and before entering the next iteration cycle, the method further comprises:
and distributing the element combination corresponding to the minimum difference degree to different slave nodes so that the different slave nodes update the mask patterns stored by themselves according to the elements in the element combination corresponding to the minimum difference degree and the initial pixel value of each pixel point in the first preset number.
6. A method according to any one of claims 1 to 3, wherein prior to selecting a first preset number of pixels from the mask pattern, the method further comprises:
respectively initializing the phase and the amplitude of each pixel point in the mask pattern and the target pattern;
and determining the phase and amplitude corresponding to each pixel point in the mask pattern and the target pattern stored by the slave node respectively.
7. The method of claim 6, wherein selecting a first predetermined number of pixels from the mask pattern comprises:
And selecting a first preset number of pixel points from the mask pattern based on a direct search algorithm, wherein the first preset number is a positive integer greater than or equal to 2.
8. An optimization apparatus of a mask pattern applied to an exposure apparatus of a chip preparation process, the exposure apparatus including a master node and at least one slave node, each node having a target pattern and a mask pattern stored therein, the apparatus being executed by the master node, the apparatus comprising:
a selecting module, configured to select a first preset number of pixel points from the mask pattern in a current iteration period;
the overturning module is used for overturning the pixel value of the pixel point of each position in the first preset number according to a preset pixel value overturning rule to obtain a plurality of element combinations, and the elements in each element combination correspond to the states of the positions of different pixel points in the first preset number;
a distribution module for distributing a part of element combinations in a plurality of the element combinations to at least one slave node, so that different slave nodes respectively determine slave node difference degrees between a new imaging pattern and the target pattern according to the received elements in each element combination and the mask pattern, wherein each new imaging pattern is generated based on the elements in one element combination and the mask pattern;
A first determining module, configured to determine a difference degree of a main node between a new imaging pattern and the target pattern according to the mask pattern and elements in each element combination stored in the main node;
the acquisition module is used for acquiring the slave node difference degree fed back by all the slave nodes;
the second determining module is used for determining an optimization result of the mask pattern in the current iteration period according to all master node difference degrees, all slave node difference degrees and initial difference degrees, wherein the initial difference degrees are difference degrees between an imaging pattern generated by the mask pattern before updating under the irradiation of a target light source and the target pattern;
a third determining module, configured to, when it is determined that the optimization result does not meet a preset iterative optimization condition, take the optimization result as a mask pattern of a next iteration period, and enter the next iteration period;
or stopping the optimization operation when the optimization result is determined to be in accordance with the preset iterative optimization condition.
9. An exposure apparatus applied to a chip preparation process, comprising:
a memory and a processor in communication with each other, the memory having stored therein computer instructions, the processor executing the computer instructions to perform the method of optimizing a mask pattern according to any one of claims 1 to 7.
10. A computer-readable storage medium having stored thereon computer instructions for causing a computer to execute the optimization method of a mask pattern according to any one of claims 1 to 7.
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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
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Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
GB9909958D0 (en) * 1998-05-05 1999-06-30 Ims Ionen Mikrofab Syst Lithographic imaging of a structure pattern onto one or more fields on a substrate
US6506544B1 (en) * 1998-11-04 2003-01-14 Nikon Corporation Exposure method and exposure apparatus and mask
CN104914684A (en) * 2015-06-24 2015-09-16 北京理工大学 Extreme ultraviolet lithography light source-mask joint optimization method
CN108369387A (en) * 2015-12-17 2018-08-03 Asml荷兰有限公司 Improve the optical measurement art of the photoetching process measured using asymmetric Subresolution feature
CN108828896A (en) * 2018-05-31 2018-11-16 中国科学院微电子研究所 Add the application of the method and this method of Sub-resolution assist features
WO2019005170A1 (en) * 2017-06-30 2019-01-03 Intel Corporation Systems, methods, and apparatuses for implementing dynamic learning mask correction for resolution enhancement and optical proximity correction (opc) of lithography masks
CN109891319A (en) * 2016-10-24 2019-06-14 Asml荷兰有限公司 Method for optimizing patterning apparatus pattern
CN113568278A (en) * 2021-07-06 2021-10-29 中国科学院上海光学精密机械研究所 Curve type reverse photoetching method based on rapid covariance matrix self-adaptive evolution strategy
CN114002911A (en) * 2021-10-29 2022-02-01 智腾科技股份有限公司 Optical proximity correction mask method based on self-adaptive mixed conjugate gradient descent

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102005005591B3 (en) * 2005-02-07 2006-07-20 Infineon Technologies Ag Integrated circuit design pattern`s structural components geometry optimization method for producing photomask, involves optimizing geometries of structural components and inserting optimized base patterns into circuit design
US11301610B2 (en) * 2017-12-22 2022-04-12 D2S, Inc. Methods for modeling of a design in reticle enhancement technology
US20230037918A1 (en) * 2021-08-06 2023-02-09 D2S, Inc. Method for computational metrology and inspection for patterns to be manufactured on a substrate

Patent Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
GB9909958D0 (en) * 1998-05-05 1999-06-30 Ims Ionen Mikrofab Syst Lithographic imaging of a structure pattern onto one or more fields on a substrate
US6506544B1 (en) * 1998-11-04 2003-01-14 Nikon Corporation Exposure method and exposure apparatus and mask
CN104914684A (en) * 2015-06-24 2015-09-16 北京理工大学 Extreme ultraviolet lithography light source-mask joint optimization method
CN108369387A (en) * 2015-12-17 2018-08-03 Asml荷兰有限公司 Improve the optical measurement art of the photoetching process measured using asymmetric Subresolution feature
CN109891319A (en) * 2016-10-24 2019-06-14 Asml荷兰有限公司 Method for optimizing patterning apparatus pattern
WO2019005170A1 (en) * 2017-06-30 2019-01-03 Intel Corporation Systems, methods, and apparatuses for implementing dynamic learning mask correction for resolution enhancement and optical proximity correction (opc) of lithography masks
CN108828896A (en) * 2018-05-31 2018-11-16 中国科学院微电子研究所 Add the application of the method and this method of Sub-resolution assist features
CN113568278A (en) * 2021-07-06 2021-10-29 中国科学院上海光学精密机械研究所 Curve type reverse photoetching method based on rapid covariance matrix self-adaptive evolution strategy
CN114002911A (en) * 2021-10-29 2022-02-01 智腾科技股份有限公司 Optical proximity correction mask method based on self-adaptive mixed conjugate gradient descent

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