Detection model after OPC, establishment method thereof and method for optimizing OPC verification

Abstract

The invention provides a post-OPC detection model and an establishment method thereof, and a method for optimizing OPC verification, the post-OPC detection model establishment method comprises the following steps: obtaining a first sample pattern after OPC, the first sample pattern being easy to have photoresist top morphology distortion after photoetching; acquiring an optical model of the first sample pattern and a corresponding distortion level; carrying out photoetching simulation on the optical model by adopting different exposure parameters to obtain measurement data and measurement images with different distortion levels, wherein the measurement data and the measurement images comprise line widths and images reflecting the top morphology of the exposed photoresist; and inputting the distortion levels, the measurement data and the measurement images corresponding to the optical model under different exposure parameters into a sample graphic library to establish a detection model for judging whether a graph with abnormal top morphology of the photoresist exists in layout data after OPC. The method is used for optimizing the detection effect and the detection efficiency of part of hot spot defects.

Description

Technical Field

[0001] The present invention relates to the technical field of integrated circuit manufacturing, and in particular to a post-OPC detection model and an establishment method thereof, and a method for optimizing OPC verification. Background Art

[0002] In the photolithography process, the graphic structure corresponding to the layout on the mask will be projected into the photoresist through the exposure system and form the corresponding graphic structure in the photoresist. However, due to optical reasons in the exposure process (such as diffraction effect) or chemical reactions of the photoresist, there is a deviation between the graphic structure formed in the photoresist and the graphic structure on the mask. This deviation requires the layout on the mask to be modified in advance through OPC (Optical Proximity Correction). When the mask corrected by OPC is used for exposure, the graphic structure formed in the photoresist will be consistent with the designed graphic structure and meet the process production requirements.

[0003] At present, after the OPC correction is performed on the layout, the OPC verification is performed on the entire layout data after OPC, and the hot spot pattern is detected and corrected, and then OPC verification is performed again to meet the requirements. However, in practice, some hot spot defects (such as abnormal morphology of the photoresist pattern after exposure) are not easy to detect in the optical model or the model after exposure (photoresist model) during the above OPC verification process, which seriously affects the effect of OPC verification. If the model after etching is added for simulation verification, the efficiency of OPC verification is seriously affected. Summary of the invention

[0004] The object of the present invention is to provide a post-OPC detection model and a method for establishing the model, and a method for optimizing OPC verification, so as to optimize the detection effect and efficiency of some hot spot defects.

[0005] In order to solve the above technical problems, the present invention provides a method for establishing a detection model after OPC, comprising:

[0006] Obtaining a first sample pattern after OPC, which has preset size parameters and exposure parameters, and the first sample pattern is prone to photoresist top morphology distortion after photolithography;

[0007] Obtaining an optical model and a corresponding distortion level of the first sample pattern;

[0008] Performing photolithography simulation on the optical model using different exposure parameters to obtain measurement data and measurement images with different distortion levels, wherein the measurement data and the measurement image include a line width and an image reflecting the top morphology of the photoresist after exposure;

[0009] The distortion level, measurement data and measurement image corresponding to the optical model under different exposure parameters are put into the sample graphic library to establish a detection model, which is used to detect whether there is a graphic that matches the optical model under the same or similar exposure parameters in the layout data after OPC, and thereby determine whether there is a graphic with abnormal top morphology of the photoresist in the layout data after OPC.

[0010] Optionally, the size parameters of the first sample pattern are adjusted to obtain multiple second sample patterns based on the first sample pattern, the optical models and corresponding distortion indicators of the first sample pattern and each of the second sample patterns are obtained, and the first sample pattern and each of the second sample patterns are divided into distortion levels from severe distortion to slight distortion according to the distortion indicators, and the size parameters of the multiple second sample patterns are arranged at equal intervals with the size parameters of the first sample pattern as the center.

[0011] Optionally, a restoration process is performed on the severely distorted sample pattern to obtain a third sample pattern, and then an optical model and a distortion index of the third sample pattern are obtained.

[0012] Optionally, the step of obtaining the optical model and the distortion index includes:

[0013] The optical model is derived according to the light source distribution of the exposure machine and the corresponding target line diameter size;

[0014] The maximum light intensity and the minimum light intensity of the cross-sections at different positions of the photoresist in the optical model are obtained, and the distortion index is the difference between the maximum light intensity and the minimum light intensity on all cross-sections divided by the sum of the maximum light intensity and the minimum light intensity.

[0015] Optionally, the step of performing lithography simulation on each of the optical models using different exposure parameters includes:

[0016] According to each of the optical models, finding the exposure condition that has the greatest impact on the photoresist within the normal process window as the key exposure condition;

[0017] Taking the key exposure conditions as variables, multiple exposure parameter combinations are constructed within a normal process window to perform lithography simulation on each of the optical models to obtain corresponding measurement data and measurement images.

[0018] Optionally, when establishing the detection model, the patterns input into the sample graphic library include normal patterns and patterns with distorted photoresist top morphology, and the patterns with distorted photoresist top morphology are composed of cases with different distortion levels.

[0019] Optionally, when obtaining the measurement data after lithography simulation,

[0020] Measuring the depth height of the photoresist to determine whether the depth height is less than a preset height,

[0021] If not, measure the minimum line width of the photoresist in the cross section as the line width,

[0022] If so, the depth height is used as the measurement data.

[0023] Optionally, when it is difficult to accurately measure or determine the line width of some sample graphics, the line width of the sample graphics is roughly estimated based on the actual line width variation trend of a sample graphics with a size close to the sample graphics, and is made to conform to the actual line width variation trend.

[0024] Based on another aspect of the present invention, a post-OPC detection model is also provided, which is established using the above-mentioned post-OPC detection model establishment method.

[0025] According to another aspect of the present invention, a method for optimizing OPC verification is also provided, comprising:

[0026] Perform OPC processing on the layout to obtain layout data after OPC;

[0027] Performing detection processing on the layout data after OPC using the detection model after OPC described above to determine whether there is a distorted pattern therein, and if so, performing correction processing on the distorted pattern and updating the layout data after OPC;

[0028] OPC verification is performed on the OPC-processed layout data.

[0029] In summary, after OPC correction and before OPC verification, the present invention sets a post-OPC detection model for the post-OPC layout data to detect hot spot defects that are difficult to detect in the related art. Different from the related art that uses normal patterns to establish models, the post-OPC detection model of the present invention includes cases formed under various exposure conditions of the above-mentioned graphics that are prone to hot spot defects, that is, distortion cases with different distortion levels. Moreover, the measurement data and measurement images in the above-mentioned distortion cases directly reflect the line width and image of the top morphology after the photoresist is exposed, so that the above-mentioned difficult-to-detect hot spot defects can be specifically detected before the overall verification of the post-OPC layout data, thereby improving the effect and efficiency of OPC correction and OPC verification. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Those skilled in the art should understand that the drawings are provided for a better understanding of the present invention, but do not constitute any limitation on the scope of the present invention.

[0031] Figure 1 is a flow chart of a method for establishing a detection model after OPC provided by an embodiment of the present invention;

[0032] Figure 2a is a schematic diagram of a first sample pattern;

[0033] Figure 2b For Figure 2a Schematic diagram of the corresponding quantization distortion index;

[0034] Figure 3a A schematic diagram of measuring line width;

[0035] Figure 3b A schematic diagram for measuring the top missing photoresist pattern;

[0036] Figure 4 A flowchart of a method for optimizing OPC verification provided by an embodiment of the present invention.

[0037] In the attached drawings: 11 - opaque area; 12 - translucent area; 13 - risk area; 14 - center line; 15 - cross section of photoresist. DETAILED DESCRIPTION

[0038] As described in the background technology, the models (verification) established in the relevant technology are all based on normal patterns and normal cases (patterns that are not expected to be distorted). Therefore, when performing OPC correction and OPC verification, statistics, corrections and verifications are performed according to these undisputed data. However, for some graphics that are not friendly to the light source setting (light source distribution), if the normal pattern (ordinary model) is used, it cannot reflect the actual situation, such as the abnormal morphology of the photoresist graphic after exposure.

[0039] Therefore, the post-OPC detection model and its establishment method, and the method for optimizing OPC verification provided by the present invention, after OPC correction and before OPC verification, set the post-OPC detection model to detect the above-mentioned difficult-to-detect hot spot defects on the post-OPC layout data. Different from the use of normal patterns to establish models in the related art, the post-OPC detection model provided by the present invention includes cases formed under various exposure conditions of the above-mentioned graphics that are prone to hot spot defects, that is, distortion cases with different distortion levels. Moreover, the measurement data and measurement images in the above-mentioned distortion cases directly reflect the line width and image of the top morphology after the photoresist is exposed, so that the above-mentioned difficult-to-detect hot spot defects can be specifically detected before the overall verification of the post-OPC layout data, thereby improving the effect and efficiency of OPC correction and OPC verification.

[0040] In order to make the purpose, advantages and features of the present invention clearer, the present invention is further described in detail below in conjunction with 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 conveniently and clearly assist in explaining the purpose of the embodiments of the present invention. In addition, the structure shown in the drawings is often a part of the actual structure. In particular, the emphasis of each drawing is different, and sometimes different scales are used.

[0041] As used in the present invention, the singular forms "one", "an", and "the" include plural objects, the term "or" is usually used to include the meaning of "and / or", the term "several" is usually used to include the meaning of "at least one", and the term "at least two" is usually used to include the meaning of "two or more". In addition, the terms "first", "second", and "third" are used only for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features. Therefore, the features defined as "first", "second", and "third" may explicitly or implicitly include one or at least two of the features, unless the content clearly indicates otherwise.

[0042] Figure 1 It is a flow chart of a method for establishing a detection model after OPC provided by an embodiment of the present invention.

[0043] like Figure 1 As shown, the method for establishing the detection model after OPC provided in this embodiment includes the following steps:

[0044] S01: Obtaining a first sample pattern after OPC, which has preset size parameters and exposure parameters,

[0045] The first sample pattern is prone to photoresist top morphology distortion after photolithography;

[0046] S02: Obtaining an optical model of the first sample pattern and a corresponding distortion level;

[0047] S03: performing photolithography simulation on the optical model using different exposure parameters to obtain measurement data and measurement images with different distortion levels, wherein the measurement data and the measurement image include a line width and an image reflecting the top morphology of the photoresist after exposure;

[0048] S04: The distortion level, measurement data and measurement image corresponding to the optical model under different exposure parameters are put into the sample graphic library to establish a detection model, which is used to detect whether there is a graphic matching the optical model under the same or similar exposure parameters in the layout data after OPC, and thereby determine whether there is a graphic with abnormal top morphology of the photoresist in the layout data after OPC.

[0049] First, step S01 is executed to obtain a first sample pattern after OPC, which has preset size parameters and exposure parameters. The first sample pattern is prone to photoresist top morphology distortion after photolithography.

[0050] Among them, the first sample pattern can be a hot spot pattern obtained from an actual product line, and these hot spot patterns are prone to abnormal photoresist morphology (distortion of photoresist top morphology) after photolithography, that is, abnormal line width of photoresist and / or abnormal top morphology of photoresist. Different from other types of distortion (such as proximity effect, rounding of square corners, nonlinear changes, etc.), the distortion that may be involved in the first sample pattern is not obvious in the top view of the photoresist pattern (line width in the top view), but it is very easy to form hot spot defects after etching using the above-mentioned photoresist pattern. Therefore, the first sample pattern can be selected from the hot spot database of the actual product line according to the above-mentioned hot spot defects. The present embodiment has no restriction on the number of the first sample patterns. When a plurality of first sample patterns with similar patterns are regarded as one class, the present embodiment may include a plurality of different types of sample patterns that are prone to distortion of photoresist top morphology, that is, a plurality of first sample patterns, and each first sample pattern can be a typical pattern selected from the same class. The following takes one (one class) of the first sample patterns as an example to establish a detection model.

[0051] It should be noted that the first sample pattern is a pattern after OPC, which has preset size parameters (after OPC) and exposure parameters, which are parameters for forming the above-mentioned hot spot defects. The area in the first sample pattern where the top morphology of the photoresist is easily distorted can be a risk area, which is usually a narrow line width area.

[0052] Next, step S02 is executed to obtain the optical model of the first sample pattern and the corresponding distortion level.

[0053] The light source distribution and the corresponding target line diameter size in the exposure conditions for executing the first sample pattern lithography process (exposure machine) can be obtained first, and then the optical model of the first sample pattern can be derived in combination with the first sample pattern. Among them, the target line diameter size is related to the pattern size before OPC, and the light source distribution is related to the exposure machine. It can be understood that the detection model established in this embodiment is for the pattern after OPC under the same exposure machine and the same light source distribution.

[0054] Using the optical model of the first sample pattern, the distortion of the optical model in the risk area is estimated as the distortion index of the first sample pattern, and the specific steps include: making a center line of the opaque area along the extension direction of the photoresist in the risk area, and then making a plurality of tangents perpendicular to the center line at preset intervals, each tangent being tangent to the opaque area of ​​the photoresist to form a photoresist cross section; obtaining the maximum value I of the light intensity of all the above photoresist cross sections by the optical model. maxWith minimum value I min , and the quantitative distortion index of the optical model is obtained: the difference between the maximum light intensity and the minimum light intensity is divided by the sum of the maximum light intensity and the minimum light intensity, that is, (I max -I min ) / (I max +I min ) as the distortion index of the optical model. It is understandable that the above tangent line, except for the tangent line with the opaque area of ​​the photoresist to form the cross section of the photoresist to obtain the maximum value of the light intensity I max With minimum value I min In addition to being used to calculate the distortion index, the above tangent line can also be tangent to the light-transmitting area of ​​the photoresist to form a cross-section of the photoresist to obtain the maximum value of the light intensity I max With minimum value I min Used to calculate distortion metrics.

[0055] Here, it is also preferred to extend the first sample pattern to a class of similar or related hot spot patterns to expand the coverage of the established detection model. Specifically, the size parameter of the first sample pattern can be increased and decreased at equal intervals in sequence with the size parameter of the first sample pattern as the center, so as to form a plurality of sample patterns with different size parameters as the second sample pattern. Of course, the size parameter of the first sample pattern can be more than one, for example, including the width (line width) of the opaque area and the width (line width) of the adjacent transparent area on the same photoresist cross section. Therefore, the width of the opaque area and the width of the adjacent transparent area can be increased or decreased at equal intervals in sequence to construct a plurality of sample patterns with different size parameters (second sample patterns). Then, similar to the first sample pattern, the optical model and the corresponding distortion index of each second sample pattern are obtained. Next, the distortion indexes of the first sample pattern and each second sample pattern are arranged in ascending or descending order, and at least three sample patterns and their optical models from severe distortion to slight distortion are selected for subsequent photolithography simulation (exposure simulation). Among them, the range of distortion indicators corresponding to severe distortion, general distortion and slight distortion can be defined according to actual process requirements, or it is also feasible to select more sample graphics and their optical models for subsequent simulation.

[0056] In addition, sample patterns with excessive distortion (for example, severe distortion) can be selected from the first sample pattern and each second sample pattern, and OPC correction can be performed on them again as third sample patterns. Similar operations as those for the first sample patterns can be performed on the third sample patterns, that is, the optical model and corresponding distortion index of each third sample pattern can be obtained. Similar to obtaining the second sample pattern from the first sample pattern, the various dimensional parameters of the third sample pattern can be increased or decreased to obtain a corresponding fourth sample pattern, thereby obtaining the optical model and distortion index of the first sample pattern.

[0057] Figure 2ais a schematic diagram of a first sample graph, Figure 2b For Figure 2a Schematic diagram of the corresponding quantization distortion index. Figure 2a As shown, in the risk area 13 of the first sample pattern, the line width of the opaque area 11 (first line width) is d, and the line width of the transparent areas 12 on both sides of the opaque area (second line width) is w, d and w are the minimum design rule line diameter sizes, the first line width is expanded to d-2, d-1, d, d+1, d+2, and the second line width is expanded to w-2, w-1, w, w+1, w+2. The above first line width and second line width are combined and part of them are removed as the size parameters of the second sample pattern, wherein the size parameters of the removed part include the parameters of the first sample pattern composed of d and w and other size parameter combinations that do not meet the design rules. Figure 2b As shown, the center line is 14 and the cross-sections of the photoresist arranged at equal intervals are 15.

[0058] It should be noted that, in practice, multiple second sample patterns can be obtained from the first sample pattern (the size parameters of the first sample pattern are increased or decreased), and then the respective optical models and distortion indicators (distortion levels) can be obtained from the first sample pattern and each second sample pattern at the same time.

[0059] Next, step S03 is executed to perform photolithography simulation on the optical model using different exposure parameters to obtain measurement data and measurement images with different distortion levels. The measurement data and measurement images include line width and image reflecting the top morphology of the photoresist after exposure.

[0060] Before the lithography simulation, according to each optical model, the exposure condition that has the greatest impact on the photoresist morphology in the risk area within the normal process window (lithography process window) of the optical model is found as the key exposure condition, such as the exposure dose or defocus range. When performing lithography simulation on each optical model, in addition to performing lithography simulation according to preset exposure parameters, lithography simulation is also performed according to multiple exposure parameter combinations within the normal process window range. Among them, multiple exposure parameter combinations can be obtained by sequentially increasing or decreasing the parameters corresponding to the key exposure conditions within the normal process window. In other words, some exposure parameters are close to the upper limit and / or lower limit of the key exposure conditions in the normal process window range, which is equivalent to changing (or even worsening) the exposure parameters corresponding to the key exposure conditions.

[0061] After the photolithography simulation, the photoresist in the risk area is measured to obtain corresponding measurement data and measurement images, wherein the measurement data and measurement images must be able to effectively reflect the morphology of the photoresist, especially the top morphology of the photoresist. Specifically, when obtaining the measurement data after the photolithography simulation, the depth height of the photoresist can be measured first to determine whether the depth height is less than the preset height. If not, it means that the depth height meets expectations, and the minimum line width of the photoresist in the cross section is measured as line width data and the corresponding measurement image is obtained. If so, it means that the depth height does not meet expectations and there is an abnormal top morphology of the photoresist (missing the top of the photoresist), then the depth height is used as the measurement data to reflect the top morphology of the photoresist, and the corresponding measurement image is obtained. Then, according to the above-mentioned measurement data and measurement images, the optical model after the exposure simulation and the corresponding exposure conditions can be classified by distortion degree (distortion level) so as to directly identify the top morphology of the photoresist and the corresponding line width data. Of course, the distortion level of the aforementioned optical model under different exposure conditions may be different from the distortion level before the original exposure simulation, but the distortion level measured after the exposure simulation is used as the subsequent judgment criterion. Moreover, there are also cases where the aforementioned optical model does not show distortion (basically a normal pattern) after the exposure simulation under some exposure conditions.

[0062] It should be noted that if the data (depth height or line width) of some images is difficult to accurately measure or determine when measuring data, a rough estimate (defining its measurement data) can be made based on the change trend of the sample graphics that are close to the size of the sample graphics, so that it conforms to the actual change trend. In one example, the depth height of the photoresist is less than the preset height. In addition to using the depth height of the photoresist to reflect its line width, the line width change trend of several sample graphics whose size parameters are close but whose line width can be measured can be used to estimate a line width that conforms to (fits) the actual change trend. In another example, the depth height of the photoresist conforms to the preset height, but the two side walls of the photoresist are sloped, and the line width at the top is the smallest. In addition to using the minimum line width at the top as its line width, the line width change trend of several sample graphics whose size parameters are close but whose line width is easier to determine can be used to estimate a line width W3 that conforms to (fits) the actual change trend.

[0063] Figure 3a is a schematic diagram of measuring line width, such as Figure 3a As shown, the depth height of the photoresist is in line with expectations. Compared with the related art in which the bottom width of the photoresist is measured as the line width, in this embodiment, the narrowest width W1 between the two side walls is measured as the line width, instead of W2 as in the related art. Figure 3b This is a schematic diagram for measuring the top missing photoresist pattern, such as Figure 3bAs shown, the depth height W1 of the photoresist is lower than the preset height W2 (not as expected). Compared with the related art in which the bottom width of the photoresist is measured as the line width, in this embodiment, the depth height W2 of the photoresist on both sides represents its line width. Of course, in practice, a line width W3 can also be estimated based on the line width change trend as above.

[0064] Next, execute step S04, and input the distortion level, measurement data and measurement image corresponding to the optical model under different exposure parameters into the sample graphic library to establish a detection model, which is used to detect whether there is a graphic that matches the optical model under the same or similar exposure parameters in the layout data after OPC, and thereby determine whether there is a graphic with abnormal top morphology of the photoresist in the layout data after OPC.

[0065] The distortion index, measurement data and measurement image of a sample pattern of a size parameter under one exposure parameter can be used as a case (illustration), and multiple cases consisting of the distortion level, measurement data and measurement image corresponding to each sample pattern and its optical model under different exposure parameters can be used as a sample pattern library for establishing a detection model, so that a certain number of normal cases (no photoresist top distortion) and a certain number of distortion cases can be simultaneously input for establishing a post-OPC detection model. In a preferred example, the ratio of normal cases to distortion cases can be about 1:1, and the distortion cases must also include various types from severe distortion to slight distortion.

[0066] After the detection model is established for the first sample pattern and similar sample patterns, the line width of the normal illustration can be used as a reference, and various other size parameters and cases under exposure conditions can be input to verify the distortion (distortion level), and define the line width specification that matches the distortion level.

[0067] Therefore, after the layout data after OPC to be tested and its exposure conditions are input into the detection model, the above detection model can find out whether there are graphics similar to the cases in the constructed model, and distinguish whether the graphics under its exposure conditions are normal patterns or distorted patterns after exposure simulation, and the distortion level (distortion situation) when it is a distorted pattern. It should be noted that the above detection model is not used to accurately calculate the line width of the sample graphics after exposure simulation, but to detect whether there are distorted graphics similar to those in the detection model and their distortion levels.

[0068] This embodiment also provides a post-OPC detection model, which is established using the above-mentioned post-OPC detection model establishment method.

[0069] This embodiment also provides a method for optimizing OPC verification.

[0070] Figure 4A flow chart of the method for optimizing OPC verification provided in this embodiment.

[0071] like Figure 4 As shown, the method for optimizing OPC verification provided by this embodiment includes:

[0072] S11: Perform OPC processing on the layout to obtain layout data after OPC;

[0073] S12: performing detection processing on the post-OPC layout data using the aforementioned post-OPC detection model to determine whether there is a distorted pattern therein, and if so, performing correction processing on the distorted pattern and updating the post-OPC layout data;

[0074] S13: Perform OPC verification on the OPC-posted layout data.

[0075] In step S11, OPC processing is performed on the OPC layout to obtain layout data after OPC. In addition, its preset exposure conditions and corresponding photolithography process windows and other related process conditions also need to be obtained.

[0076] In step S12, the OPC layout data and the corresponding process conditions are input into the aforementioned post-OPC detection model, and detection processing is performed to determine whether there is distortion related to the abnormal morphology of the top of the photoresist and the corresponding distortion level. If so, the detected distorted pattern is repaired until it is verified to be qualified, and then the repaired pattern is replaced with the distorted pattern in the post-OPC layout data, that is, the post-OPC layout data is updated. If not, no additional processing is performed.

[0077] In step S13, the layout data after OPC inspection is verified as a whole.

[0078] The verification items after OPC usually include CD error, EPE, pinch-off error and bridging error, etc., but do not include the distortion of the top morphology of the photoresist. Therefore, the verification items after OPC are difficult to detect the above-mentioned distortion of the top morphology of the photoresist. In some related technologies, the exposure model simulation verification in the verification project is superimposed with the etching model simulation verification to detect the hot spot defects caused by the distortion of the top morphology of the photoresist, which makes the verification process of OPC lengthy and inefficient, and the etching model simulation is also accompanied by the etching load effect, resulting in the capture of false hot spot defects (not caused by the distortion of the top morphology of the photoresist) in the simulation verification. In the present embodiment, after the OPC process and before the OPC verification, the above-mentioned detection model is used to detect the distortion of the top morphology of the photoresist alone, and the above-mentioned detection model is derived according to the physical parameters of the actual distortion of the top morphology of the photoresist, and the above-mentioned distortion can be detected quickly and accurately.

[0079] In summary, after OPC correction and before OPC verification, the present invention sets a post-OPC detection model for the post-OPC layout data to detect hot spot defects that are difficult to detect in the related art. Different from the related art that uses normal patterns to establish models, the post-OPC detection model of the present invention includes cases formed under various exposure conditions of the above-mentioned graphics that are prone to hot spot defects, that is, distortion cases with different distortion levels. Moreover, the measurement data and measurement images in the above-mentioned distortion cases directly reflect the line width and image of the top morphology after the photoresist is exposed, so that the above-mentioned difficult-to-detect hot spot defects can be specifically detected before the overall verification of the post-OPC layout data, thereby improving the effect and efficiency of OPC correction and OPC verification.

[0080] The above description is only a description of the preferred embodiments of the present invention, and is not intended to limit the scope of the present invention. Any changes or modifications made by a person skilled in the art in the field of the present invention based on the above disclosure shall fall within the scope of protection of the claims.

Claims

1. A method for establishing a detection model after OPC, characterized in that: include: Obtaining a first sample pattern after OPC, which has preset size parameters and exposure parameters, and the first sample pattern is prone to photoresist top morphology distortion after photolithography; Obtaining an optical model and a corresponding distortion level of the first sample pattern; Performing photolithography simulation on the optical model using different exposure parameters to obtain measurement data and measurement images with different distortion levels, wherein the measurement data and the measurement image include a line width and an image reflecting the top morphology of the photoresist after exposure; The distortion level, measurement data and measurement image corresponding to the optical model under different exposure parameters are put into the sample graphic library to establish a detection model, which is used to detect whether there is a graphic that matches the optical model under the same or similar exposure parameters in the layout data after OPC, and thereby determine whether there is a graphic with abnormal top morphology of the photoresist in the layout data after OPC.

2. The method for establishing a detection model after OPC according to claim 1, characterized in that: Adjust the size parameters of the first sample pattern to obtain multiple second sample patterns based on the first sample pattern, obtain the optical models and corresponding distortion indicators of the first sample pattern and each of the second sample patterns, and divide the first sample pattern and each of the second sample patterns into distortion levels from severe distortion to slight distortion according to the distortion indicators. The size parameters of the multiple second sample patterns are arranged at equal intervals with the size parameter of the first sample pattern as the center.

3. The method for establishing a detection model after OPC according to claim 2, characterized in that: A repair process is performed on the severely distorted sample pattern to obtain a third sample pattern, and then an optical model and a distortion index of the third sample pattern are obtained.

4. The method for establishing a detection model after OPC according to claim 2 or 3, characterized in that: The steps of obtaining the optical model and the distortion index include: The optical model is derived according to the light source distribution of the exposure machine and the corresponding target line diameter size; The maximum light intensity and the minimum light intensity of the cross-sections at different positions of the photoresist in the optical model are obtained, and the distortion index is the difference between the maximum light intensity and the minimum light intensity on all cross-sections divided by the sum of the maximum light intensity and the minimum light intensity.

5. The method for establishing a detection model after OPC according to claim 1, characterized in that: The steps of performing lithography simulation on each of the optical models using different exposure parameters include: According to each of the optical models, finding the exposure condition that has the greatest impact on the photoresist within the normal process window as the key exposure condition; Taking the key exposure conditions as variables, multiple exposure parameter combinations are constructed within a normal process window to perform lithography simulation on each of the optical models to obtain corresponding measurement data and measurement images.

6. The method for establishing a detection model after OPC according to claim 1, characterized in that: When establishing the detection model, the patterns input into the sample graphic library include normal patterns and patterns with distorted photoresist top morphology, and the patterns with distorted photoresist top morphology are composed of cases with different distortion levels.

7. The method for establishing a detection model after OPC according to claim 1, characterized in that: When obtaining the measurement data after lithography simulation, Measuring the depth height of the photoresist to determine whether the depth height is less than a preset height, If not, measure the minimum line width of the photoresist in the cross section as the line width, If so, the depth height is used as the measurement data.

8. The method for establishing a detection model after OPC according to claim 1, characterized in that: When it is difficult to accurately measure or determine the line width of a portion of a sample pattern, the line width of the sample pattern is roughly estimated based on the actual line width variation trend of a sample pattern with a size close to that of the sample pattern, and is made to conform to the actual line width variation trend.

9. A detection model after OPC, characterized in that: The detection model after OPC is established by adopting the method for establishing the detection model after OPC as described in any one of claims 1 to 8.

10. A method for optimizing OPC verification, characterized in that: include: Perform OPC processing on the layout to obtain layout data after OPC; Performing detection processing on the post-OPC layout data using the post-OPC detection model as claimed in claim 9 to determine whether there is a distorted pattern therein, and if so, performing correction processing on the distorted pattern and updating the post-OPC layout data; OPC verification is performed on the OPC-processed layout data.

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