Mask layout method for manufacturing semiconductor device and mask

Abstract

The invention discloses a mask layout method for manufacturing a semiconductor device and a mask. The method comprises the following steps: initializing the speed and position of each scattering strip particle in a scattering strip particle swarm; obtaining the fitness of each scattering strip particle according to the position of each scattering strip particle and the position of the surrounding main graph, and obtaining the global optimal position of the whole scattering strip particle swarm according to the fitness of all scattering strip particles; updating the speed and position of each scattering strip particle; obtaining the updated fitness according to the updated position; screening the scattering strip particles in the scattering strip particle swarm according to the fitness of the individual optimal position of each scattering strip particle; if the end condition is met currently, outputting a layout result, and if the end condition is not met, continuing to update the speed and the position of the scattering strip particles. The layout of the mask is completed according to the particle swarm optimization algorithm and the natural selection mechanism, and the method has good universality, accuracy and ductility.

Description

Technical Field

[0001] The present invention relates to the field of semiconductor technology, and in particular to a mask layout method and a mask for manufacturing semiconductor devices. Background Art

[0002] Scattering Bar (SBAR) is a widely used Optical Proximity Correction (OPC) method, including Sub Resolution Assist Feature (SRAF) and Sub Resolution Inverse Feature (SRIF). This method improves the light intensity distribution and imaging quality during the exposure process by adding sub-resolution graphics around or inside the position corresponding to the main graphics on the mask. Since the line width of the scattering bar is small, the intensity of the diffracted light there is less than the photosensitivity threshold of the photoresist, so the scattering bar cannot be imaged. Correcting the mask through SBAR technology can effectively improve the graphic resolution of the lithography process, increase the process window, and improve the product yield.

[0003] As the size of advanced node graphics approaches the capacity limit of lithography machines and the process window becomes smaller and smaller, the parameter selection and position placement of exposure auxiliary graphics become more and more important. Especially for integrated circuits with multiple types and sizes of graphics, scattering strips generated based on a set of rules are difficult to adapt. Summary of the invention

[0004] A series of simplified concepts are introduced in the Summary of the Invention, which will be further described in detail in the Detailed Description of the Invention. The Summary of the Invention does not mean to attempt to define the key features and essential technical features of the claimed technical solution, nor does it mean to attempt to determine the scope of protection of the claimed technical solution.

[0005] In view of the existing problems, an embodiment of the present invention provides a mask layout method for manufacturing a semiconductor device, comprising:

[0006] Step S1: Initialize the speed and position of each scattering bar particle in the scattering bar particle group;

[0007] Step S2: according to the position of each scattering bar particle and the position of the surrounding main graphics, the fitness of each scattering bar particle is obtained, and according to the fitness of all scattering bar particles, the global optimal position of the entire scattering bar particle group is obtained;

[0008] Step S3: updating the speed and position of each scattering bar particle according to the individual optimal position of each scattering bar particle and the global optimal position of the entire scattering bar particle group;

[0009] Step S4: obtaining the updated fitness of each scattering bar particle according to the updated position of each scattering bar particle, comparing the updated fitness of each scattering bar particle with the fitness of the individual optimal position, and if the updated fitness is better, updating the individual optimal position of each scattering bar particle and the global optimal position of the entire scattering bar particle group according to the updated position;

[0010] Step S5: screening the scattering bar particles in the scattering bar particle group according to the fitness of the individual optimal position of each scattering bar particle;

[0011] Step S6: Determine whether the current end condition is met, if the end condition is met, output the layout result, if not, return to step S3.

[0012] Exemplarily, the fitness of each scattering strip particle is obtained according to the position of each scattering strip particle and the position of the surrounding main graphics, including:

[0013] Determining a plurality of evaluation points on the edge of the main pattern around each scattering bar particle;

[0014] The single-point fitness is obtained based on the distance and angle of each scattering bar particle relative to a single evaluation point;

[0015] The single-point fitness of each scattering bar particle relative to all evaluation points is summed to obtain the fitness of each scattering bar particle.

[0016] Exemplarily, the velocity of the scattering strip particles is updated using the following formula:

[0017] v i k+1 =wv i k +c1r1(p i k -x i k )+c2r2(g k -x i k )

[0018] Among them, v i k+1 is the velocity of the i-th scattering particle at the k+1th iteration; v i k is the velocity of the i-th scattering strip particle at the k-th iteration;

[0019] xi k is the position of the i-th scattering strip particle at the k-th iteration;

[0020] w is the inertia weight;

[0021] c1 and c2 are non-negative constants;

[0022] r1 and r2 are random numbers in the interval (0,1);

[0023] p i k is the individual optimal position of the i-th scattering particle after the first k iterations;

[0024] g k It is the optimal position of the entire scattering particle group after the first k iterations.

[0025] Exemplarily, the position of the scattering strip particles is updated using the following formula:

[0026] x i k+1 =x i k +rv i k+1 ;

[0027] in, is the position of the i-th scattered particle at the k+1th iteration, x i k is the position of the i-th scattering strip particle at the k-th iteration;

[0028] r is a random number in the interval (0,1);

[0029] v i k+1 is the velocity of the i-th scattering particle at the k+1th iteration.

[0030] Exemplarily, the inertia weight is negatively correlated with the number of iterations.

[0031] Exemplarily, the calculation formula of the inertia weight is:

[0032]

[0033] Among them, w start is the initial inertia weight;

[0034] w end is the inertia weight at the maximum number of iterations;

[0035] k is the current iteration number,

[0036] T max is the maximum number of iterations.

[0037] Exemplarily, the screening of the scattering bar particles in the scattering bar particle group according to the fitness of the individual optimal position of each scattering bar particle includes:

[0038] The scattering bar particles in the scattering bar particle group are sorted according to the fitness of all scattering bar particles, and the speeds and positions of half of the scattering bar particles in the front order are used to replace the speeds and positions of half of the scattering bar particles in the back order.

[0039] Exemplarily, the end condition includes at least one of the following:

[0040] The maximum number of iterations is reached, the global optimal fitness reaches the preset fitness threshold, and the difference between the global optimal fitness obtained from two iterations is less than the preset difference.

[0041] Exemplarily, the scattering strips include sub-resolution auxiliary patterns or sub-resolution inverse patterns.

[0042] Another aspect of an embodiment of the present invention provides a mask, wherein the mask uses the above-mentioned method to perform scattering strip layout.

[0043] According to the mask layout method for manufacturing semiconductor devices provided by the present invention, the mask layout is completed according to the particle swarm optimization algorithm and the natural selection mechanism, and has good adaptability to complex film layers, can more effectively adjust the light intensity dispersion, and make the main graphic imaging effect better; can effectively avoid the uneven distribution or position offset problems caused by the rule-based generation of scattering strips; in practical applications, it can adapt to main graphics of various different graphics, different sizes, and different dispersions, and has good versatility, accuracy and ductility. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The following drawings of the present invention are used to understand the present invention as part of the present invention. The embodiments of the present invention are shown in the drawings and the description thereof is used to explain the principle of the present invention.

[0045] In the attached figure:

[0046] Figure 1 A schematic flow chart showing a mask layout method according to a specific embodiment of the present invention;

[0047] Figure 2 A schematic flow chart showing a method for laying out sub-resolution auxiliary graphics according to a specific embodiment of the present invention;

[0048] Figure 3 A schematic diagram showing the fitness of SRAF particles according to an embodiment of the present invention is shown;

[0049] Figure 4A schematic diagram showing the fitness of SRIF particles according to an embodiment of the present invention is shown;

[0050] Figure 5A , Figure 5B and Figure 5C A schematic diagram of a mask obtained by a mask layout method according to an embodiment of the present invention is shown;

[0051] Figure 6 A schematic diagram showing a mask obtained by a rule-based mask layout method;

[0052] Fig. 7A The exposure results of the rule-based mask layout method are shown;

[0053] Figure 7B FIG. 4 shows an exposure result of a mask layout method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0054] In the following description, a large number of specific details are provided to provide a more thorough understanding of the present invention. However, it is apparent to those skilled in the art that the present invention can be implemented without one or more of these details. In other examples, in order to avoid confusion with the present invention, some technical features well known in the art are not described.

[0055] It should be understood that the present invention can be implemented in different forms and should not be construed as being limited to the embodiments presented herein. On the contrary, providing these embodiments will make the disclosure thorough and complete and fully convey the scope of the present invention to those skilled in the art. In the accompanying drawings, the sizes and relative sizes of layers and regions may be exaggerated for clarity. The same reference numerals throughout represent the same elements.

[0056] It should be understood that when an element or layer is referred to as being "on, adjacent to, connected to or coupled to other elements or layers, it may be directly on, adjacent to, connected to or coupled to other elements or layers, or there may be intervening elements or layers. In contrast, when an element is referred to as being "directly on, directly adjacent to, directly connected to or directly coupled to other elements or layers, there may be no intervening elements or layers. It should be understood that, although the terms first, second, third, etc. may be used to describe various elements, components, regions, layers and / or parts, these elements, components, regions, layers and / or parts should not be limited by these terms. These terms are only used to distinguish one element, component, region, layer or part from another element, component, region, layer or part. Therefore, without departing from the teachings of the present invention, the first element, component, region, layer or part discussed below may be represented as a second element, component, region, layer or part.

[0057] Spatially relative terms such as "under," "below," "below," "under," "above," "above," etc., may be used herein for ease of description to describe the relationship of an element or feature shown in the figures to other elements or features. It should be understood that in addition to the orientations shown in the figures, the spatially relative terms are intended to include different orientations of the device in use and operation. For example, if the device in the accompanying drawings is flipped, then the elements or features described as "under other elements" or "under" or "under" will be oriented as "on" the other elements or features. Therefore, the exemplary terms "under" and "under" may include both upper and lower orientations. The device may be oriented otherwise (rotated 90 degrees or other orientations) and the spatial descriptors used herein are interpreted accordingly.

[0058] The purpose of the terms used herein is only to describe specific embodiments and is not intended to be limiting of the present invention. When used herein, the singular forms "one", "an" and "said / the" are also intended to include plural forms, unless the context clearly indicates otherwise. It should also be understood that the terms "consisting of" and / or "comprising", when used in this specification, determine the presence of the features, integers, steps, operations, elements and / or parts, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, parts and / or groups. When used herein, the term "and / or" includes any and all combinations of the relevant listed items.

[0059] Scattering strips include sub-resolution auxiliary patterns (SRAF) and sub-resolution inverse patterns (SRIF). Taking SRAF as an example, its parameters mainly include the following: the distance between the auxiliary pattern and the main pattern, the width of the auxiliary pattern, and the distance between the auxiliary pattern and the auxiliary pattern. How to get the values ​​of these three parameters? The current method adopted in the industry is to design experiments. First, fix the width of the auxiliary pattern and the distance between the auxiliary pattern and the main pattern, then design the range of variation of the distance between the auxiliary pattern and the auxiliary pattern, and simulate the process window after inserting the sub-resolution auxiliary pattern through the lithography model to obtain the distance between the auxiliary patterns corresponding to the maximum process window. Next, fix the distance between the auxiliary patterns, design the range of variation of the auxiliary pattern width and the distance between the auxiliary pattern and the main pattern, and simulate the process window after inserting the sub-resolution auxiliary pattern through the lithography model to determine the optimal auxiliary pattern width and the range of variation of the distance between the auxiliary pattern and the main pattern, and finally obtain the parameters of the sub-resolution auxiliary pattern.

[0060] In the past, when laying out sub-resolution auxiliary graphics, mask parameters were extracted mainly through various optimization algorithms, such as genetic algorithms and annealing algorithms. Engineers needed to manually input measured values ​​and use engineer workstations or personal computers for calculations. By checking and correcting the parameters of the actual measurement results, parameter selection and parameter values ​​were gradually extracted. In this process, engineers compared, confirmed, and corrected the parameters and actual results, repeatedly selecting the necessary parameters and gradually extracting the optimal values, which usually took several weeks or even months.

[0061] In addition, the currently commonly used rule-based sub-resolution auxiliary graphics layout method has a good effect on solving the optimal solution of the single extremum problem, but it may not be ideal for solving the optimal solution of the multi-extremum problem. When the SRAF layout is performed globally based on a set of rules, the modification operation of special and specific parts has certain limitations and complexities because qualitative rules are used. In addition, a large number of simulation calculations are required in the early design experiments. If errors occur and are discovered in the later OPC, it will take a lot of time and cost to trace the problems and re-do the entire process.

[0062] In view of the existence of the above-mentioned technical problems, an embodiment of the present invention provides a mask layout method for a semiconductor device, such as Figure 1 As shown, it mainly includes the following steps:

[0063] Step S1: Initialize the speed and position of each scattering bar particle in the scattering bar particle group;

[0064] Step S2: according to the position of each scattering bar particle and the position of the surrounding main graphics, the fitness of each scattering bar particle is obtained, and according to the fitness of all scattering bar particles, the global optimal position of the entire scattering bar particle group is obtained;

[0065] Step S3: updating the speed and position of each scattering bar particle according to the individual optimal position of each scattering bar particle and the global optimal position of the entire scattering bar particle group;

[0066] Step S4: obtaining the updated fitness of each scattering bar particle according to the updated position of each scattering bar particle, comparing the updated fitness of each scattering bar particle with the fitness of the individual optimal position, and if the updated fitness is better, updating the individual optimal position of each scattering bar particle and the global optimal position of the entire scattering bar particle group according to the updated position;

[0067] Step S5: screening the scattering bar particles in the scattering bar particle group according to the fitness of the individual optimal position of each scattering bar particle;

[0068] Step S6: Determine whether the current end condition is met, if the end condition is met, output the layout result, if not, return to step S3.

[0069] The mask layout method provided by the embodiment of the present invention can avoid errors and defects caused by regular layout of scattering strips, and can produce good optimization effects for film layers of various types and sizes, thereby increasing the process window.

[0070] The scattering strip may include a sub-resolution auxiliary pattern (SRAF) or a sub-resolution inverse image (SRIF), the sub-resolution auxiliary image is a feature outside the edge of the main pattern, and the sub-resolution inverse image is a feature dug out from the inside of the edge of the main pattern. The embodiment of the present invention is applicable to the layout optimization of the SRAF pattern outside the main pattern, and the layout optimization of the SRIF inside the main pattern can also be completed on this basis. The following mainly describes SRAF as an example.

[0071] like Figure 2 As shown in the figure, the SRAF particle swarm is first initialized, including the initialization of the particle swarm size N and the position X and velocity V of each SRAF particle. The physical meaning of SRAF particles is essentially the coordinates on a two-dimensional plane. Among them, N is known information, and the position X and velocity V are randomly assigned values ​​within a certain range. In addition, during initialization, it is also necessary to know the size of the SRAF particle swarm, the number of iterations, the inertia weight, the learning factor, the iteration step size, and the search interval.

[0072] Specifically, each SRAF particle has three properties: speed, position, and fitness. Speed ​​represents the moving distance and direction of the SRAF particle, and position is the solution to the corresponding practical problem. The method of the embodiment of the present invention first needs to initialize a group of SRAF particles, randomly initialize the position and speed of each SRAF particle, and then search for the global optimal solution through continuous iteration. In each iteration, the SRAF particle updates its own speed and position by tracking two "extreme values" (individual optimal position P_best, global optimal position G_best).

[0073] According to the speed and position of each SRAF particle, the fitness of each SRAF particle can be determined. The fitness is calculated by the fitness function and is used to evaluate the quality of a SRAF particle. After initializing the position and speed of each SRAF particle, the initial fitness of each SRAF particle can be obtained according to the initial position of each SRAF particle and the position of the surrounding main graphics.

[0074] See also Figure 3, multiple evaluation points 303 are determined on the edge of the main graph 301 around each SRAF particle 302, and the single-point fitness is obtained according to the distance and angle of each SRAF particle 302 relative to a single evaluation point 303; the fitness of each SRAF particle 302 is obtained by summing the single-point fitness of each SRAF particle 302 and all evaluation points. The evaluation points can be placed according to the set rules, and their number and positions can be modified as needed.

[0075] Specifically, the fitness J of the i-th SRAF particle is i for:

[0076] Among them, slope i is the angle of the i-th SRAF particle relative to a single evaluation point, CD i is the distance of the ith SRAF particle relative to a single evaluation point. That is, the single-point fitness is the ratio of the angle and distance of the ith SRAF particle relative to a single evaluation point, and the sum of all single-point fitness of the ith SRAF particle is the total fitness of the SRAF particle.

[0077] Similarly, see Figure 4 When the scattering strip is a SRIF particle 402, the SRIF particle 402 is inside the main graphic 401, and a plurality of evaluation points 403 can be determined on the edge of the main graphic 401 adjacent to the SRIF particle 402 to calculate the fitness of the SRIF particle.

[0078] After obtaining the fitness of all SRAF particles in the SRAF particle group, the global optimal fitness can also be obtained according to the fitness of all SRAF particles, that is, the optimal fitness of all SRAF particles, and the position corresponding to the global optimal fitness is the global optimal position.

[0079] Next, the speed and position of the SRAF particles are updated, and the global optimal solution is searched through continuous iterations. Specifically, in each iteration, each SRAF particle adjusts its own speed and position according to its current individual extreme value (P_best) and the group extreme value (G_best) shared by the entire SRAF particle group, and finds the optimal solution through collaboration and information sharing between individuals in the group. Among them, the speed V of the i-th SRAF particle in the k-th iteration is i k The expression is: V i k =(v i1 ,v i2 ), where v i1 ,v i2 are the velocities in two dimensions respectively; the position X of the i-th SRAF particle at the k-th iteration i kThe expression is: X i k =(x i1 ,x i2 ), where x i1 ,x i2 are the coordinates in two dimensions respectively.

[0080] The following is an introduction to the SRAF particle velocity and position update process of an embodiment of the present invention:

[0081] Exemplarily, the update formula of SRAF particle velocity is:

[0082] v i k+1 =wv i k +c1r1(p i k -x i k )+c2r2(g k -x i k ) (Formula 1)

[0083] The update formula of SRAF particle position is:

[0084] x i k+1 =x i k +rv i k+1 (Formula 2)

[0085] Among them, v i k+1 is the velocity of the i-th SRAF particle at the k+1th iteration, v i k is the velocity of the i-th SRAF particle at the k-th iteration;

[0086] is the position of the i-th SRAF particle at the k+1th iteration, x i k is the position of the i-th SRAF particle at the k-th iteration;

[0087] w is the inertia weight (w>0);

[0088] c1 and c2 are non-negative constants (acceleration factors);

[0089] r1, r2 and r are random numbers in the interval (0,1) used to increase the randomness of the search;

[0090] p i kis the individual optimal position P of the i-th SRAF particle after the first k iterations best , that is, the position with the best fitness among all the positions experienced by a single SRAF particle. For each SRAF particle, there is P best , P best =(Px i ,Py i );

[0091] g k is the global optimal position G of the entire SRAF particle swarm after the first k iterations best , that is, the position with the best fitness searched by all SRAF particles in the SRAF particle group. There is only one G for the entire SRAF particle group. best , G best =(P1,P2,…P n ) best .

[0092] In Formula 1 and Formula 2, wv i k is the inertial term, reflecting the influence of the last velocity of the SRAF particle; c1r1(p i k -x i k ) is the self-cognition item, which reflects the experience of the SRAF particle itself and depends on the distance and direction between the current position of the SRAF particle and its own historical optimal position; c2r2(g k -x i k ) is the group cognition term, which shares the information between SRAF particles and depends on the distance and direction between the current position of the SRAF particle and the historical optimal position in the SRAF particle group.

[0093] In formula 1, the inertia weight w reflects the ability of the SRAF particle to inherit the previous velocity v. When the inertia weight is large, it is more prominent in the global search, and when it is small, it is more prominent in the local search. Therefore, in order to better adapt to the adaptability of the SRAF layout, a linear decreasing strategy is adopted in the use of the inertia weight. The calculation formula of the inertia weight is:

[0094]

[0095] Among them, w start is the initial inertia weight;

[0096] w end is the inertia weight when the iteration reaches the maximum number;

[0097] k is the current iteration number;

[0098] T maxis the maximum number of iterations.

[0099] Under this strategy, the inertia weight w is negatively correlated with the number of iterations k, and the relationship is linear, with the slope remaining unchanged. This results in the SRAF particles having a larger speed in the initial iteration, thus having a stronger global search capability, and as the number of iterations increases, the speed decreases and the local search capability increases, which is more suitable for SRAF layout optimization of the entire layout.

[0100] After updating the speed and position of each SRAF particle, the fitness of each SRAF particle is calculated again according to the updated speed and position, and the individual optimal position P of each SRAF particle is updated according to the new fitness. best , individual optimal fitness, global optimal position G of all SRAF particles best and the global optimal fitness.

[0101] Next, the particles in the SRAF particle group are screened according to the fitness of the SRAF particles, the poor SRAF particles are eliminated, and the excellent SRAF particles are left (i.e., the natural selection mechanism). For example, the SRAF particles in the SRAF particle group are sorted according to the fitness, and the SRAF particle group is divided into set A and set B according to the sorting result. Set A contains half of the SRAF particles with higher fitness, and set B contains half of the SRAF particles with lower fitness. The speed and position of the SRAF particles in set A are used to replace the speed and position of the SRAF particles in set B, and P is maintained. best and G best constant.

[0102] The embodiment of the present invention simultaneously adds a natural selection operation during the iteration process to solve the problem of local solutions, so that all particles are always updated with a global optimal value, thereby completing the optimization of the layout of the sub-resolution auxiliary graphics.

[0103] After the screening is completed, it is determined whether the end condition is met. If the end condition is met, the layout is completed according to the current position of the SRAF particle and the layout result is output; if the end condition is not met, the speed and position of the SRAF particle are continued to be updated. The end condition includes at least one of the following: reaching the maximum number of iterations, the global optimal fitness reaches the preset fitness threshold, and the difference between the global optimal fitness obtained from two iterations is less than the preset difference.

[0104] Figure 5A , Figure 5B and Figure 5CMasks 100A, 100B and 100C obtained by the mask layout method according to an embodiment of the present invention are shown, wherein the sub-resolution auxiliary graphic 502 outside the main graphic 501 is gradually optimized during the iteration process, for example, the distribution in mask 100A is optimized to the distribution in mask 100B, and further optimized to the distribution in mask 100C. Figure 6 The mask 200 obtained by the layout method of the sub-resolution auxiliary pattern based on the rule is shown. The SRAF layout method based on the rule needs to pre-set a series of restrictions such as the length, width, interval, and distance from the main pattern 601 of the sub-resolution auxiliary pattern 602, and overall layout of the sub-resolution auxiliary pattern 602. However, since only one set of rules can be set, sometimes conflicts occur between the rules themselves, resulting in the inability to set SRAF at certain positions or the inability to set SRAF to the optimal position.

[0105] In comparison, the embodiment of the present invention compares the sub-resolution auxiliary graphics to a massless particle, simulates a bird in a flock of birds, and gives it a speed (moving speed) and a position (moving direction). Each SRAF particle searches for the optimal solution in the search space separately, and records it as the current SRAF individual extreme value, and shares the individual extreme value with other SRAF particles in the entire SRAF particle group, and finds the optimal SRAF individual extreme value as the current global optimal solution of the entire SRAF particle group. All SRAF particles in the SRAF particle group adjust their own speed and position according to the current individual extreme value found by themselves and the current global optimal solution shared by the entire SRAF particle group, and find the optimal solution through cooperation and information sharing between individuals in the group. In the convergence process, natural selection operations are added at the same time to solve the problem of local solutions, so that all particles are always updated with the global optimal value, thereby completing the optimization of the layout of the sub-resolution auxiliary graphics. Compared with the traditional layout method, the performance is better, the results are more accurate, the solution speed is faster, and the scalability is stronger.

[0106] Furthermore, in an embodiment of the present invention, when mask parameters are determined, a sub-resolution graphic is introduced into the optical field to adjust the fitness of the surrounding main graphic, and the layout of the entire sub-resolution auxiliary graphic is optimized by calculating the fitness. The main purpose is to enhance the imaging effect of the lithography main graphic, avoid the main graphic from having necking, bridging, wave, shrinkage and other undesirable imaging, and avoid unpredictable defects caused by the placement of the sub-resolution auxiliary graphic.

[0107] The embodiment of the present invention not only adopts the traditional particle swarm optimization (PSO) algorithm, but also introduces a natural selection mechanism based on the PSO algorithm. By eliminating SRAF particles through the selection mechanism, the optimization speed and accuracy of the algorithm can be better accelerated, and it is more suitable for the correction of the mask.

[0108] Fig. 7A and Figure 7B The comparison diagram of the exposure results of the rule-based mask layout method and the mask layout method of the embodiment of the present invention is shown. The SRAF according to the embodiment of the present invention is placed more reasonably and efficiently, making the light intensity distribution more uniform and the imaging quality of the main pattern higher. The main pattern is a pattern corresponding to the main pattern formed by the photosensitive material after the photosensitive material is exposed and developed using the mask. Fig. 7A Compared with the main pattern 701 in FIG. 1 (formed by exposure and development of the mask 200 obtained by the layout method of the sub-resolution auxiliary pattern based on the rule), Figure 7B The edge of the main pattern 702 (formed by exposure and development of the mask 100C obtained by the mask layout method of the embodiment of the present invention) is more vertical (θ2<θ1), and the biggest role of SRAF itself is to make the edge of the main pattern more vertical. Therefore, the SRAF layout obtained by the method of the embodiment of the present invention makes the imaging of the main pattern more in line with the ideal state, which can provide a solid guarantee for the stability and accuracy of the subsequent patterning etching process.

[0109] So far, the steps of implementing the mask layout method according to an embodiment of the present invention have been completed. It can be understood that the mask layout method of this embodiment not only includes the above steps, but may also include other necessary steps before, during or after the above steps, which are all included in the scope of the layout method of this embodiment.

[0110] In summary, according to the mask layout method provided in the embodiment of the present invention, the scattering strip layout is completed according to the particle swarm optimization algorithm and the natural selection mechanism, and it has good adaptability to complex film layers, can more effectively adjust the light intensity dispersion, and make the main graphic imaging effect better; it can effectively avoid the uneven distribution or position offset problems caused by the rule-based generation of scattering strips; in practical applications, it can adapt to main graphics of various different graphics, different sizes, and different dispersions, and has good versatility, accuracy, and scalability.

[0111] The embodiment of the present invention further provides a mask plate, which uses the mask plate layout method described above to layout scattering strips, thereby having a better imaging effect.

[0112] The present invention has been described by the above embodiments, but it should be understood that the above embodiments are only for the purpose of example and description, and are not intended to limit the present invention to the scope of the described embodiments. In addition, it can be understood by those skilled in the art that the present invention is not limited to the above embodiments, and more variations and modifications can be made according to the teachings of the present invention, and these variations and modifications all fall within the scope of the protection claimed by the present invention. The protection scope of the present invention is defined by the attached claims and their equivalents.

Claims

1. A mask layout method for manufacturing a semiconductor device, characterized in that: The method comprises: Step S1: Initialize the speed and position of each scattering bar particle in the scattering bar particle group; Step S2: according to the position of each scattering bar particle and the position of the surrounding main graphics, the fitness of each scattering bar particle is obtained, and according to the fitness of all scattering bar particles, the global optimal position of the entire scattering bar particle group is obtained; Step S3: updating the speed and position of each scattering bar particle according to the individual optimal position of each scattering bar particle and the global optimal position of the entire scattering bar particle group; Step S4: obtaining the updated fitness of each scattering bar particle according to the updated position of each scattering bar particle, comparing the updated fitness of each scattering bar particle with the fitness of the individual optimal position, and if the updated fitness is better, updating the individual optimal position of each scattering bar particle and the global optimal position of the entire scattering bar particle group according to the updated position; Step S5: screening the scattering bar particles in the scattering bar particle group according to the fitness of the individual optimal position of each scattering bar particle; Step S6: Determine whether the current end condition is met, if the end condition is met, output the layout result, if not, return to step S3.

2. The mask layout method according to claim 1, wherein: According to the position of each scattering bar particle and the position of the surrounding main graphics, the fitness of each scattering bar particle is obtained, including: Determining a plurality of evaluation points on the edge of the main pattern around each scattering bar particle; The single-point fitness is obtained based on the distance and angle of each scattering bar particle relative to a single evaluation point; The single-point fitness of each scattering bar particle relative to all evaluation points is summed to obtain the fitness of each scattering bar particle.

3. The mask layout method according to claim 1, wherein: The velocity of the scattering strip particles is updated using the following formula: v i k+1 =wv i k +c1r1(p i k -x i k )+c2r2(g k -x i k ) Among them, v i k+1 is the velocity of the i-th scattering particle at the k+1th iteration; v i k is the velocity of the i-th scattering strip particle at the k-th iteration; x i k is the position of the i-th scattering strip particle at the k-th iteration; w is the inertia weight; c1 and c2 are non-negative constants; r1 and r2 are random numbers in the interval (0,1); p i k is the individual optimal position of the i-th scattering particle after the first k iterations; g k It is the optimal position of the entire scattering particle group after the first k iterations.

4. The mask layout method according to claim 1 or 3, characterized in that: The position of the scattering strip particles is updated using the following formula: x i k+1 =x i k +rv i k+1 ; Among them, x i k+1 is the position of the i-th scattered particle at the k+1th iteration, x i k is the position of the i-th scattering strip particle at the k-th iteration; r is a random number in the interval (0,1); v i k+1 is the velocity of the i-th scattering particle at the k+1th iteration.

5. The mask layout method according to claim 3, characterized in that: The inertia weight is negatively correlated with the number of iterations.

6. The mask layout method according to claim 5, characterized in that: The calculation formula of the inertia weight is: Among them, w start is the initial inertia weight; w end is the inertia weight at the maximum number of iterations; k is the current iteration number, T max is the maximum number of iterations.

7. The mask layout method according to claim 1, wherein: The step of screening the scattering bar particles in the scattering bar particle group according to the fitness of the individual optimal position of each scattering bar particle comprises: The scattering bar particles in the scattering bar particle group are sorted according to the fitness of all scattering bar particles, and the speeds and positions of half of the scattering bar particles in the front order are used to replace the speeds and positions of half of the scattering bar particles in the back order.

8. The mask layout method according to claim 1, wherein: The termination condition includes at least one of the following: The maximum number of iterations is reached, the global optimal fitness reaches the preset fitness threshold, and the difference between the global optimal fitness obtained from two iterations is less than the preset difference.

9. The mask layout method according to claim 1, wherein: The scattering strips include sub-resolution auxiliary patterns or sub-resolution inverse patterns.

10. A mask, characterized in that: The mask is laid out using the mask method according to any one of claims 1 to 9.

Images