Optical proximity correction method for one-dimensional pattern, storage medium, electronic device
By establishing a model error table and a compensation table for one-dimensional patterns, the optical proximity correction process was optimized, solving the problem of time-consuming and resource-intensive one-dimensional pattern correction in photolithography and achieving efficient and accurate optical proximity correction.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- CHONGQING XINLIAN MICROELECTRONICS CO LTD
- Filing Date
- 2025-03-04
- Publication Date
- 2026-06-26
AI Technical Summary
In photolithography, the optical proximity correction process for one-dimensional patterns in existing technologies is time-consuming and lacks accuracy. Especially after the feature size of integrated circuits is reduced, model-based optical proximity correction is extremely time-consuming and resource-intensive.
An error table for the model of one-dimensional patterns under various spatial environments is established. Preprocessing corrections are performed using numerical compensation tables and model compensation tables. The optical proximity correction process is optimized by combining rules and model correction parameters.
It improves the accuracy and efficiency of optical proximity correction, reduces correction time and resource consumption, and enhances the production efficiency of photolithography.
Smart Images
Figure CN119987157B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of integrated circuit manufacturing technology, and in particular to an optical proximity correction method for one-dimensional patterns, a storage medium, and an electronic device. Background Technology
[0002] In photolithography, the pattern on a photomask is projected onto photoresist through an exposure system, forming the corresponding pattern. However, due to optical factors (such as diffraction) or chemical reactions in the photoresist, the pattern formed in the photoresist may deviate from the pattern on the photomask. This deviation requires pre-modification of the photomask pattern using OPC (Optical Proximity Correction). When the photomask is exposed using OPC-corrected OPC, the pattern formed in the photoresist will match the designed pattern and meet the process requirements.
[0003] As the feature size of integrated circuits continues to shrink, model-based optical proximity correction (OPC) has become the mainstream method for mask correction. Even for one-dimensional patterns, OPC is an essential step. Therefore, the aforementioned OPC processes are extremely time-consuming and resource-intensive. Thus, reducing the time and improving the accuracy of OPC correction is of paramount importance. Summary of the Invention
[0004] The purpose of this invention is to provide an optical proximity correction method, storage medium, and electronic device for optimizing the optical proximity correction of one-dimensional patterns.
[0005] To solve the above-mentioned technical problems, the present invention provides an optical proximity correction method for one-dimensional patterns, comprising:
[0006] A model error table is established for one-dimensional patterns of various sizes in various spatial environments. The model error table is obtained from a numerical complement table and a model complement table. The numerical complement table is obtained by correcting one-dimensional patterns of various sizes for optical proximity effects based on rules in various spatial environments. The model complement table is obtained by correcting one-dimensional patterns of various sizes for optical proximity effects based on models in various spatial environments.
[0007] A rule-based optical proximity correction is performed on a one-dimensional pattern, followed by a model-based optical proximity correction. The rule includes the numerical complement table, and the model includes the model error table as correction parameters.
[0008] Optionally, the spatial environment of the one-dimensional pattern includes the center-to-center distance between it and adjacent patterns, the number of sub-resolution auxiliary patterns between adjacent patterns, and their arrangement.
[0009] Optionally, multiple dimensions and multiple spatial environments of the one-dimensional pattern are determined according to the design rules, and the multiple dimensions cover all important dimension settings on the photoresist layer, and the multiple spatial environments cover all important spatial settings on the photoresist layer.
[0010] Optionally, the step of obtaining the numerical complement table includes:
[0011] Obtain the first MEEF value of one-dimensional patterns of different sizes based on the rule-based optical proximity effect in various spatial environments. One-dimensional patterns of different sizes in the same spatial environment have the same or similar first MEEF values.
[0012] Based on the various spatial environments and the corresponding first MEEF values, the first mask dimensions of one-dimensional patterns of different sizes in each spatial environment are obtained as the numerical complement table.
[0013] Optionally, the step of obtaining the model complement table includes:
[0014] The second MEEF value of the optical proximity effect based on the model is obtained for one-dimensional patterns of different sizes in various spatial environments. One-dimensional patterns of different sizes in the same spatial environment have the same or similar second MEEF values.
[0015] Based on the various spatial environments and the corresponding second MEEF values, the second mask dimensions of one-dimensional patterns of different sizes in each spatial environment are obtained as the model complement table.
[0016] Optionally, the difference between the numerical compensation table and the model compensation table for the same target size and the same spatial environment can be used as the model error table.
[0017] Optionally, when performing rule-based optical proximity effect correction on a one-dimensional pattern, parameters of the spatial environment and size corresponding to the one-dimensional pattern to be corrected are obtained from the numerical complement table, and the entire edge line of the one-dimensional pattern is used as a correction unit to perform a correction as the preprocessed layout data.
[0018] Optionally, when performing the first correction of the model-based optical proximity correction on the one-dimensional pattern, the corresponding parameters in the model error table are used as correction parameters to correct the layout data based on the preprocessed data, and the regression parameters of the correction are reduced at the same time.
[0019] According to another aspect of the present invention, a storage medium is also provided, the storage medium storing a plurality of instructions adapted for loading by a processor to execute the optical proximity correction method as described above.
[0020] According to another aspect of the present invention, an electronic device is also provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the optical proximity correction method as described above. Attached Figure Description
[0021] Those skilled in the art will understand that the accompanying drawings are provided to better understand the invention and do not constitute any limitation on the scope of the invention.
[0022] Figure 1 This is a flowchart of the optical proximity correction method for a one-dimensional pattern provided in the embodiments of this application;
[0023] Figure 2 A flowchart of the method for obtaining a numerical complement table provided in this application;
[0024] Figure 3 This is a schematic diagram of a numerical complement table;
[0025] Figure 4 A flowchart of the method for obtaining the model complement table provided in this application;
[0026] Figure 5 This is a schematic diagram of a one-dimensional pattern in an embodiment of this application.
[0027] In the attached diagram: 10 - one-dimensional pattern; 11 - middle section; 12 - end section. Detailed Implementation
[0028] As described in the background section, for a single one-dimensional pattern, the corresponding OPC model conforms to the modeling error specifications and meets the design requirements when (or after) it is built. However, when the one-dimensional pattern is placed on the layout, the error range generated by the corresponding OPC model will expand. This not only affects the accuracy of OPC correction but also consumes additional time for OPC correction. The inventors have discovered that this situation is due to the influence of the spatial environment surrounding the one-dimensional pattern on the layout, making the OPC model inaccurate. This spatial environment may include, for example, the spacing between adjacent patterns, the number and arrangement of sub-resolution auxiliary patterns between adjacent patterns, etc.
[0029] To address this, this application provides an optical proximity correction method, storage medium, and electronic device for one-dimensional patterns. The optical proximity correction method includes: establishing model error tables for one-dimensional patterns of various sizes under different spatial environments. These model error tables are obtained from numerical complement tables and model complement tables. The numerical complement tables are obtained through rule-based optical proximity effect correction of one-dimensional patterns of various sizes under different spatial environments, and the model complement tables are obtained through model-based optical proximity effect correction of one-dimensional patterns of various sizes under different spatial environments. The method then performs rule-based optical proximity effect correction on the one-dimensional pattern, followed by model-based optical proximity effect correction. The rules include the numerical complement tables, and the model includes the model error tables as correction parameters. In this application, the rules are obtained through correction simulations of one-dimensional patterns of various sizes under different spatial environments. These rules consider the influence of different spatial environments and sizes on the correction. Before performing model-based correction on the one-dimensional pattern, these rules are used to perform a preprocessing-like correction, improving the accuracy of some areas through a single correction, thus saving time and resources for subsequent model-based optical proximity correction. Similarly, after obtaining the model complement table and the model error table, when performing model-based correction, the parameters of the corresponding size and spatial environment are also obtained from the model error table to correct the corrected data. This allows the regression parameters during correction to be reduced while ensuring accuracy, thereby reducing the execution time of the correction script.
[0030] To make the objectives, advantages, and features of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that the drawings are all in a very simplified form and are not drawn to scale, and are only used to facilitate and clarify the explanation of the embodiments of this invention. Furthermore, the structures shown in the drawings are often part of the actual structures. In particular, different figures may emphasize different aspects and may sometimes use different scales.
[0031] As used in this invention, the singular forms “a,” “an,” and “the” include plural objects; the term “or” is generally used to mean “and / or”; the term “a number” is generally used to mean “at least one”; and the term “at least two” is generally used to mean “two or more”. Furthermore, the terms “first,” “second,” and “third” are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as “first,” “second,” or “third” may explicitly or implicitly include one or at least two of that feature, unless otherwise expressly indicated.
[0032] Figure 1 This is a flowchart of the optical proximity correction method for a one-dimensional pattern provided in the embodiments of this application.
[0033] like Figure 1 As shown, the optical proximity correction method for one-dimensional patterns provided in this embodiment includes the following steps:
[0034] S01: Establish a model error table for one-dimensional patterns of various sizes in various spatial environments. The model error table is obtained from the numerical compensation table and the model compensation table. The numerical compensation table is obtained by correcting one-dimensional patterns of various sizes for optical proximity effects based on rules in various spatial environments. The model compensation table is obtained by correcting one-dimensional patterns of various sizes for optical proximity effects based on models in various spatial environments.
[0035] S02: Perform rule-based optical proximity correction on the one-dimensional pattern, and then perform model-based optical proximity correction. The rule includes the numerical complement table, and the model includes the model error table as correction parameters.
[0036] First, execute step S01 to establish a model error table for one-dimensional patterns of various sizes in various spatial environments. The model error table is obtained from the numerical compensation table and the model compensation table. The numerical compensation table is obtained by correcting one-dimensional patterns of various sizes for optical proximity effects based on rules in various spatial environments. The model compensation table is obtained by correcting one-dimensional patterns of various sizes for optical proximity effects based on models in various spatial environments.
[0037] A one-dimensional pattern can be a linearly extending strip or the space between adjacent strips. In this application, the one-dimensional pattern can be a linearly extending strip, and the aforementioned dimensions and spatial environments are dimensions on the photoresist, i.e., the dimensions used as design targets (i.e., target dimensions). Furthermore, multiple dimensions and spatial environments of the one-dimensional pattern can be formulated according to design rules to establish a model error table, ensuring that the multiple dimensions cover all important dimension settings on the photoresist layer, and the multiple spatial environments cover all important spatial settings on the photoresist layer. In other words, after establishing the model error table, data corresponding to common target dimensions and spatial environments can be obtained by consulting the model error table. The spatial environment of a one-dimensional pattern includes not only the center-to-center distance between it and its adjacent patterns, but also the number and arrangement of sub-resolution auxiliary patterns disposed between adjacent patterns. For one-dimensional patterns of the same size and the same spacing, changes in the number, size, or arrangement (distribution method) of the sub-resolution auxiliary patterns around the one-dimensional pattern are also considered different spatial environments. Of course, on the other hand, in the same spatial environment, the spacing between one-dimensional patterns of different sizes is different, and the parameters of the one-dimensional pattern are also different.
[0038] Figure 2 A flowchart illustrating the method for obtaining a numerical complement table provided in this application. Figure 2 As shown, the steps to obtain the numerical complement table include:
[0039] S011: Obtain the first MEEF value of one-dimensional patterns of different sizes based on the rule-based optical proximity effect in various spatial environments. The steps for obtaining the first MEEF value may include, for example, defining the range space of the data to be collected, including multiple target sizes covering all important size settings on the photoresist and multiple spatial environments covering all important spatial settings. Then, performing a rule-based optical proximity correction simulation according to the aforementioned range space, obtaining the mask size required to form one-dimensional patterns of each target size in each spatial environment, and the MEEF value of forming one-dimensional patterns of each target size in each spatial environment as the first MEEF value. The MEEF value (i.e., Mask Error Enhancement Factor) can be calculated by dividing the size error on the wafer by the size error on the corresponding mask. Since there are many target sizes and multiple spatial environments involved, and the first MEEF values of one-dimensional patterns of different sizes in the same spatial environment are relatively close, in practice, at least one target size simulation can be performed for each spatial environment, and the first MEEF value can be applied to the simulation of multiple target sizes in its spatial environment. Of course, for particularly important space environments and target dimensions, the MEEF value can also be calculated by simulating multiple target dimensions in that space environment.
[0040] S012: Based on each spatial environment and the corresponding first MEEF value, the first mask size of one-dimensional patterns of different sizes in each spatial environment is obtained as a numerical complement table. The established numerical complement table is based on the aforementioned range of data to be collected. According to the first MEEF value corresponding to each spatial environment, and considering that one-dimensional patterns of different sizes in the same spatial environment have the same or similar first MEEF values, the mask size required to form one-dimensional patterns of each target size is derived. That is, the numerical complement table uses the target size of the one-dimensional pattern as one of the horizontal or vertical axes, and the spatial environment of the one-dimensional pattern as the other. The table content corresponding to (intersecting) the horizontal and vertical axes represents the mask size on the mask used to form the one-dimensional pattern of the target size. Figure 3This is a schematic diagram of the numerical complement table. The vertical axis represents the target dimensions of the one-dimensional pattern, and the horizontal axis represents the spatial environment of the one-dimensional pattern. The target dimensions include, for example, 60nm, 70nm, 80nm, 90nm, 100nm, and 120nm. The center-to-center spacing of the spatial environments includes, for example, 120nm, 130nm, 140nm, 150nm, 160nm, 150nm, and 200nm. For a one-dimensional pattern with a size of 60nm, there is one sub-resolution auxiliary pattern in the center-to-center spacing between 200nm and 310nm, two sub-resolution auxiliary patterns in the center-to-center spacing between 310nm and 460nm, three sub-resolution auxiliary patterns in the spacing between 460nm and 560nm, and four sub-resolution auxiliary patterns in the spacing above 560nm. Of course, due to the actual situation, the number of target dimensions varies in different spatial environments.
[0041] Figure 4 A flowchart illustrating the method for obtaining the model complement table provided in this application. Figure 4 As shown, the steps for obtaining the model complement table include: S013: obtaining the second MEEF values of the optical proximity effect based on the model for one-dimensional patterns of different sizes in various spatial environments; S014: obtaining the second mask dimensions of one-dimensional patterns of different sizes in various spatial environments based on each spatial environment and the corresponding second MEEF values, as the model complement table. The range space of the model complement table is the same as that of the numerical complement table, and the steps for obtaining the model complement table are the same as those for obtaining the numerical complement table. The difference is that when obtaining the model complement table, simulation based on the optical proximity effect based on the model is used to obtain the second MEEF values. Moreover, these second MEEF values are only for the dimensions of the middle segment of the one-dimensional pattern, not the dimensions of the end segment. Similarly, when obtaining each second MEEF value to establish the model complement table, based on the second MEEF values corresponding to each spatial environment, and considering that one-dimensional patterns of different sizes in the same spatial environment have the same or similar second MEEF values, the mask dimensions required to form one-dimensional patterns of each target size are derived. Therefore, the table contents corresponding to the horizontal and vertical axes in the model complement table are also the mask dimensions used to form the one-dimensional pattern (middle section) of the target size on the mask, but these mask dimensions are obtained by model-based optical proximity correction simulation.
[0042] After obtaining the numerical compensation table and model compensation table of one-dimensional patterns of various sizes in various spatial environments, the difference between the numerical compensation table and the model compensation table of the same target size and the same spatial environment can be used as the model error table.
[0043] Next, step S02 is executed, which performs rule-based optical proximity correction on the one-dimensional pattern, and then performs model-based optical proximity correction. The rules include a numerical complement table, and the model includes a model error table as correction parameters.
[0044] For the layout to be corrected, an initial graphic analysis can be performed first to identify the one-dimensional pattern, and then the optical proximity correction method of this application can be applied to the one-dimensional pattern. The steps for performing the optical proximity correction method of this application may include:
[0045] First, rule-based optical proximity correction can be performed on a one-dimensional pattern to obtain preprocessed layout data. The rule is the aforementioned numerical complement table. The one-dimensional pattern to be corrected is identical to the one-dimensional pattern for which the numerical complement table was established, except for the target size and spatial environment. In other words, when the numerical complement table is applied to the one-dimensional pattern to be corrected, both have the same or similar first MEEF values under the same target size and spatial environment. Therefore, the one-dimensional pattern can be conveniently corrected based on the aforementioned rules using the numerical complement table. Moreover, the numerical complement table considers the influence of different spatial environments and can also make the correction more accurate. This allows the accuracy of some areas of the preprocessed layout data to be improved after a single correction, saving time and resources for subsequent model-based optical proximity correction. Figure 5 This is a schematic diagram of a one-dimensional pattern. It's important to understand that in reality, a one-dimensional pattern is not truly one-dimensional, such as... Figure 5 As shown, the one-dimensional pattern 10 can be divided, for example, into a middle segment 11 and end segments 12 (segments near the corners) located at both ends of the middle segment 11. The above correction can be performed as a correction unit using the entire edge line of the one-dimensional pattern 10, that is, optical proximity correction based on the above rules is used to correct the size (e.g., line width) of the middle segment 11.
[0046] Next, a model-based optical proximity correction is performed on the one-dimensional pattern after the above processing. This model includes the previously established model error table as correction parameters. That is, model-based optical proximity correction is performed on the preprocessed layout data. This model-based correction includes not only conventional model correction but also correction of conventional model correction using parameters corresponding to the size and spatial environment obtained from the model error table. By correcting the preprocessed layout data using both conventional model correction and the model error table correction, the regression parameters during correction can be reduced while ensuring accuracy, thereby reducing the execution time of the correction script. Figure 5For example, when performing model-based optical proximity correction, after the aforementioned rule-based correction, the middle segment 11 of the one-dimensional pattern 10 can be corrected again in the first model-based correction by applying the relevant data in the model error table. This accelerates the correction process and improves model accuracy. Of course, the above correction parameters cannot directly correct the end segment 12 of the one-dimensional pattern 10, but the end segment 12 can be corrected based on the pre-processed middle segment 11 (or the corrected middle segment 11), which also helps to accelerate the correction process.
[0047] It should be noted that since this application is based on the same spatial environment (same center interval and auxiliary graphics) with the same and similar MEEF values, when applying the above numerical compensation table, model compensation table and model error table, the interval distance between one-dimensional patterns needs to be converted into the center interval distance of the one-dimensional pattern in combination with its size, and then the table should be looked up and corrected on this basis.
[0048] This application also provides a computer-readable storage medium storing at least one instruction, at least one program, code set, or instruction set. The at least one instruction, at least one program, code set, or instruction set is loaded and executed by the processor to implement the optical proximity correction method for one-dimensional patterns provided in the above embodiments. Since the instructions stored in this storage medium can execute the steps of any method provided in the embodiments of this application, the beneficial effects achievable by any method provided in the embodiments of this application can be realized. Details can be found in the preceding embodiments and will not be repeated here.
[0049] This application also provides an electronic device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the optical proximity correction method as described above.
[0050] In this application, the aforementioned rules are obtained through simulations of one-dimensional patterns of various sizes under different spatial environments. These rules consider the influence of different spatial environments and sizes on the correction. Before performing model-based correction on the one-dimensional patterns, these rules are used to perform a preprocessing-like correction, improving the accuracy of certain regions in a single correction, thus saving time and resources for subsequent model-based optical proximity correction. Similarly, after obtaining the model complement table and model error table, during model-based correction, parameters corresponding to the size and spatial environment are obtained from the model error table to correct the corrected data. This reduces the regression parameters during correction while ensuring accuracy, thereby reducing the script execution time for correction.
[0051] The above description is merely a description of preferred embodiments of the present invention and is not intended to limit the scope of the present invention in any way. Any changes or modifications made by those skilled in the art based on the above disclosure shall fall within the protection scope of the claims.
Claims
1. A method for optical proximity correction of a one-dimensional pattern, characterized in that, include: A model error table for one-dimensional patterns of various sizes under various spatial environments is established. The model error table is obtained from the numerical compensation table and the model compensation table. The numerical compensation table is obtained by rule-based optical proximity effect correction of one-dimensional patterns of various sizes under various spatial environments. The model compensation table is obtained by model-based optical proximity effect correction of one-dimensional patterns of various sizes under various spatial environments. The rule is obtained by correction simulation of one-dimensional patterns of various sizes under various spatial environments. Before performing model-based correction on the one-dimensional patterns, the one-dimensional patterns are preprocessed and corrected using this rule. A rule-based optical proximity correction is performed on a one-dimensional pattern, followed by a model-based optical proximity correction. The rule includes the numerical complement table, and the model includes the model error table as correction parameters. The spatial environment of the one-dimensional pattern includes the center-to-center distance between it and adjacent patterns, the number of sub-resolution auxiliary patterns placed between adjacent patterns, and their arrangement.
2. The optical proximity correction method for one-dimensional patterns according to claim 1, characterized in that, According to the design rules, multiple dimensions and multiple spatial environments of the one-dimensional pattern are determined, and the multiple dimensions cover all important dimension settings on the photoresist layer, and the multiple spatial environments cover all important spatial settings on the photoresist layer.
3. The optical proximity correction method for one-dimensional patterns according to claim 1, characterized in that, The steps for obtaining the numerical complement table include: Obtain the first MEEF value of one-dimensional patterns of different sizes based on the rule-based optical proximity effect in various spatial environments. One-dimensional patterns of different sizes in the same spatial environment have the same or similar first MEEF values. Based on the various spatial environments and the corresponding first MEEF values, the first mask dimensions of one-dimensional patterns of different sizes in each spatial environment are obtained as the numerical complement table.
4. The optical proximity correction method for one-dimensional patterns according to claim 1, characterized in that, The steps for obtaining the model complement table include: The second MEEF value of the optical proximity effect based on the model is obtained for one-dimensional patterns of different sizes in various spatial environments. One-dimensional patterns of different sizes in the same spatial environment have the same or similar second MEEF values. Based on the various spatial environments and the corresponding second MEEF values, the second mask dimensions of one-dimensional patterns of different sizes in each spatial environment are obtained as the model complement table.
5. The optical proximity correction method for one-dimensional patterns according to claim 1, characterized in that, The difference between the numerical compensation table and the model compensation table for the same target size and the same spatial environment is used as the model error table.
6. The optical proximity correction method for one-dimensional patterns according to claim 1, characterized in that, When performing rule-based optical proximity effect correction on a one-dimensional pattern, the parameters of the spatial environment and size corresponding to the one-dimensional pattern to be corrected are obtained from the numerical complement table, and the entire edge line of the one-dimensional pattern is used as a correction unit to perform a correction as the preprocessed layout data.
7. The optical proximity correction method for one-dimensional patterns according to claim 6, characterized in that, When performing the first correction of the model-based optical proximity correction on a one-dimensional pattern, the parameters corresponding to the model error table are used as correction parameters to correct the layout data based on the preprocessed data, and the regression parameters of the correction are reduced at the same time.
8. A storage medium, characterized in that, The storage medium stores a plurality of instructions adapted for loading by a processor to execute the optical proximity correction method as described in any one of claims 1-7.
9. An electronic device, characterized in that, It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the optical proximity correction method as described in any one of claims 1-7.