A method and apparatus for verifying photolithographic shrinkage defects

Abstract

This invention relates to the field of semiconductor manufacturing, and in particular to a method and apparatus for verifying photolithographic shrinkage defects. The method involves receiving a target curve image and a simulated curve image to be inspected obtained by OPC processing of the target curve image; determining sampling points on the target curve image; acquiring the deviation distance from the normal direction of the corresponding tangent of each sampling point to the simulated curve image to be inspected, the curvature corresponding to each sampling point, and the measured linewidth at the intersection of the normal of each sampling point and the simulated curve image to be inspected; determining the curve position error corresponding to each sampling point; determining the linewidth reduction coefficient of the corresponding sampling point; calculating the shrinkage defect risk value of each sampling point; and when the shrinkage defect risk value exceeds the tolerance threshold, identifying the corresponding sampling point as a shrinkage defect risk point. This invention improves the detection accuracy of shrinkage defects, reduces the probability of missed defects, and enhances the versatility of the verification method.

Description

Technical Field

[0001] This invention relates to the field of semiconductor manufacturing, and in particular to a method and apparatus for verifying photolithographic shrinkage defects. Background Technology

[0002] In semiconductor manufacturing, OPC (Optical Proximity Correction) correction verification, which compares the differences between the simulated profile and the target pattern, is an essential step. However, with the advancement of technology, the target pattern is no longer limited to Manhattan patterns with mutually perpendicular edges, but has also begun to include patterns with curved edges. However, both the target pattern and the simulated profile of curved OPC are curved, which greatly increases the complexity of OPC correction verification.

[0003] Pinch defects refer to electrical performance failures caused by excessively narrow or broken local linewidths in photolithographic patterns. Traditional OPC verification methods typically discretize the target pattern at the curved edge into Manhattan patterns for detection. However, this traditional method has many problems, such as geometric approximation errors. Multiple Manhattan patterns cannot accurately describe the continuous edges of high-curvature regions (such as rounded corners), leading to linewidth measurement errors and decreased accuracy. In addition, there are fixed threshold methods (such as judging a linewidth <90% of the design value as a defect), but these do not consider the amplification effect of curvature on process fluctuations, resulting in poor sensitivity. Furthermore, existing technologies rely on simulation of a single process angle, which is difficult to cover the effects of dose / focal length fluctuations, resulting in poor compatibility. All of the above-mentioned solutions have loopholes, leading to serious omissions in the detection of shrinkage defects in existing photolithography shrinkage defect verification methods, which severely restricts yield improvement.

[0004] Therefore, how to improve the accuracy of shrinkage defect detection, reduce the probability of missed defects, and increase the compatibility and versatility of photolithography shrinkage defect verification methods is a problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0005] The purpose of this invention is to provide a method and apparatus for verifying lithographic shrinkage defects, so as to solve the problems of poor detection accuracy, high probability of missed defects, and poor compatibility and versatility of existing technologies for shrinkage defect detection.

[0006] To solve the above technical problems, the present invention provides a method for verifying photolithographic shrinkage defects, comprising:

[0007] Receive the target curve graph and the simulated curve graph to be checked obtained by OPC processing of the target curve graph;

[0008] The sampling points on the target curve are determined, and the deviation distance from the normal direction of the corresponding tangent of each sampling point to the simulated curve to be checked, the curvature of each sampling point, and the measured line width at the intersection of the normal of each sampling point and the simulated curve to be checked are obtained.

[0009] Based on the deviation distance and curvature of each sampling point, the curve position error corresponding to each sampling point is determined;

[0010] Based on the measured line width and the preset design line width, determine the line width reduction factor for the corresponding sampling point;

[0011] Based on the linewidth reduction factor and the curve position error, calculate the shrinkage defect risk value for each sampling point;

[0012] Determine whether the shrinkage defect risk value exceeds a preset tolerance threshold;

[0013] When the shrinkage defect risk value exceeds the tolerance threshold, the corresponding sampling point is determined as a shrinkage defect risk point.

[0014] Optionally, in the photolithography shrinkage defect verification method, the shrinkage defect risk value of each sampling point is calculated based on the linewidth reduction factor and the curve position error, including:

[0015] The shrinkage defect risk value for each sampling point is calculated using the following formula:

[0016] ;

[0017] Wherein, CW-PR(s) is the shrinkage defect risk value corresponding to sampling point s, CEPE(s) is the curve position error at sampling point s, and LW(s) is the line width reduction coefficient at sampling point s.

[0018] Optionally, in the photolithographic shrinkage defect verification method, determining the curve position error corresponding to each sampling point based on the deviation distance and curvature of each sampling point includes:

[0019] The curve position error corresponding to each sampling point is determined by the following formula:

[0020] ;

[0021] Where CEPE(s) is the curve position error at sampling point s, and EPE(s) is the deviation distance at sampling point s. Let be the curvature at sampling point s, and α be the curvature sensitivity coefficient.

[0022] Optionally, in the photolithographic shrinkage defect verification method, before determining the curve position error corresponding to each sampling point, the method further includes:

[0023] The curvature sensitivity coefficient is determined based on the curvature of each sampling point; wherein the curvature sensitivity coefficient corresponding to the sampling point with smaller curvature is smaller than the curvature sensitivity coefficient corresponding to the sampling point with larger curvature.

[0024] Optionally, in the photolithography shrinkage defect verification method, the linewidth reduction factor of the corresponding sampling point is determined based on the measured linewidth and the preset design linewidth, including:

[0025] The linewidth reduction factor corresponding to each sampling point is determined by the following formula:

[0026] ;

[0027] Where LW(s) is the linewidth reduction factor at sampling point s, and w(s) is the measured linewidth at sampling point s. design The design line width is given.

[0028] Optionally, in the photolithography shrinkage defect verification method, before calculating the shrinkage defect risk value of each sampling point based on the linewidth reduction factor and the curve position error, the method further includes:

[0029] Based on the measured linewidth, the preset design linewidth, and the preset exposure dose, determine the exposure dose influence coefficient of the corresponding sampling point;

[0030] Accordingly, based on the linewidth reduction factor and the curve position error, the shrinkage defect risk value of each sampling point is calculated, including:

[0031] The shrinkage defect risk value of each sampling point is calculated based on the linewidth reduction factor, the curve position error, and the exposure dose influence factor.

[0032] Optionally, in the photolithography shrinkage defect verification method, the shrinkage defect risk value of each sampling point is calculated based on the linewidth reduction factor, the curve position error, and the exposure dose influence factor, including:

[0033] The shrinkage defect risk value for each sampling point is calculated using the following formula:

[0034] ;

[0035] ;

[0036] Wherein, CW-PR(s) is the shrinkage defect risk value corresponding to sampling point s, CEPE(s) is the curve position error at sampling point s, LW(s) is the linewidth reduction coefficient at sampling point s, D(s) is the exposure dose influence coefficient at sampling point s, w(s) is the measured linewidth at sampling point s, D is the exposure dose, and β is the process coupling coefficient.

[0037] Optionally, in the photolithography shrinkage defect verification method, the shrinkage defect risk value of each sampling point is calculated based on the linewidth reduction factor, the curve position error, and the exposure dose influence factor, including:

[0038] The shrinkage defect risk value for each sampling point is calculated using the following formula:

[0039] ;

[0040] ;

[0041] Wherein, CW-PR(s) is the shrinkage defect risk value corresponding to sampling point s, CEPE(s) is the curve position error at sampling point s, LW(s) is the linewidth reduction coefficient at sampling point s, D(s) is the exposure dose influence coefficient at sampling point s, w(s) is the measured linewidth at sampling point s, D is the exposure dose, and β is the process coupling coefficient.

[0042] Optionally, in the photolithographic shrinkage defect verification method, after obtaining the curvature corresponding to each sampling point, the method further includes:

[0043] Determine whether there is a mutation point pair, wherein the mutation point pair is two adjacent sampling points, and the difference in curvature corresponding to the two adjacent sampling points exceeds a preset mutation threshold.

[0044] When the mutation point pair exists, additional sampling points are added between the two sampling points of the mutation point pair;

[0045] Obtain the deviation distance from the normal direction of the corresponding tangent of each of the additional sampling points to the simulated curve to be checked, the curvature of each sampling point, and the measured line width at the intersection of the normal of each sampling point and the simulated curve to be checked.

[0046] A photolithography shrinkage defect inspection device, comprising:

[0047] The receiving module is used to receive the target curve graph and the simulated curve graph to be checked obtained by OPC processing of the target curve graph;

[0048] The sampling point module is used to determine the sampling points on the target curve graph, and to obtain the deviation distance of each sampling point from the normal direction of the corresponding tangent to the simulated curve graph to be checked, the curvature corresponding to each sampling point, and the measured line width at the intersection of the normal of each sampling point and the simulated curve graph to be checked.

[0049] The curve position error module is used to determine the curve position error corresponding to each sampling point based on the deviation distance and curvature of each sampling point.

[0050] The line width reduction module is used to determine the line width reduction coefficient of the corresponding sampling point based on the measured line width and the preset design line width.

[0051] The risk calculation module is used to calculate the shrinkage defect risk value of each sampling point based on the line width reduction coefficient and the curve position error;

[0052] The judgment module is used to determine whether the shrinkage defect risk value exceeds a preset tolerance threshold;

[0053] The risk determination module is used to determine the corresponding sampling point as a shrinkage defect risk point when the shrinkage defect risk value exceeds the tolerance threshold.

[0054] The photolithography shrinkage defect verification method provided by this invention involves receiving a target curve graphic and a simulated curve graphic to be checked obtained by OPC processing of the target curve graphic; determining sampling points on the target curve graphic and acquiring the deviation distance from the normal direction of the corresponding tangent of each sampling point to the simulated curve graphic to be checked, the curvature of each sampling point, and the measured linewidth at the intersection of the normal of each sampling point and the simulated curve graphic to be checked; determining the curve position error corresponding to each sampling point based on the deviation distance and curvature of each sampling point; determining the linewidth reduction factor of the corresponding sampling point based on the measured linewidth and the preset design linewidth; calculating the shrinkage defect risk value of each sampling point based on the linewidth reduction factor and the curve position error; determining whether the shrinkage defect risk value exceeds a preset tolerance threshold; and identifying the corresponding sampling point as a shrinkage defect risk point when the shrinkage defect risk value exceeds the tolerance threshold.

[0055] This invention sets multiple sampling points on the target curve graphic and assesses the risk of shrinkage defects at each sampling point from two aspects: the deviation between the simulated curve to be checked obtained from OPC simulation and the target curve graphic (i.e., the curve position error), and the deviation between the linewidth at the sampling point and the designed linewidth (i.e., the linewidth reduction factor). (The greater the deviation in both aspects, the higher the risk of shrinkage defects at the corresponding position). This identifies potential hidden risk areas with shrinkage defects, thereby greatly improving the detection accuracy of shrinkage defects, reducing the probability of missed defects, and is applicable to graphics with various curvature edges, greatly improving the versatility of the verification method. It provides a quantitative, dynamic, and traceable evaluation index for the photolithographic verification of complex patterns in advanced processes. This invention also provides a photolithographic shrinkage defect verification device with the above-mentioned beneficial effects. Attached Figure Description

[0056] To more clearly illustrate the technical solutions of the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0057] Figure 1 A flowchart illustrating a specific implementation of the photolithography shrinkage defect verification method provided by the present invention;

[0058] Figure 2 A flowchart illustrating another specific embodiment of the photolithographic shrinkage defect verification method provided by the present invention;

[0059] Figure 3 A flowchart illustrating another specific embodiment of the photolithographic shrinkage defect verification method provided by the present invention;

[0060] Figure 4 This is a schematic diagram of a specific embodiment of the photolithography shrinkage defect inspection device provided by the present invention.

[0061] Figure label:

[0062] 100 - Receiver module; 200 - Sampling point module; 300 - Curve position error module; 400 - Line width reduction module; 500 - Risk calculation module; 600 - Judgment module; 700 - Risk determination module. Detailed Implementation

[0063] To enable those skilled in the art to better understand the present invention, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. Obviously, the described embodiments are merely some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0064] The core of this invention is to provide a method for verifying photolithographic shrinkage defects, and a flowchart of one specific implementation is shown below. Figure 1 As shown, this is referred to as Specific Implementation Method One, which includes:

[0065] S101: Receive the target curve graph and the simulated curve graph to be checked obtained by OPC processing of the target curve graph.

[0066] The target curve in this step is the desired curve, while the simulated curve to be checked is the curve generated by simulating the target curve after OPC processing. Ideally, the simulated curve to be checked should be as close as possible to the target curve; ideally, their edge shapes should be identical.

[0067] S102: Determine the sampling points on the target curve graph, and obtain the deviation distance of each sampling point from the normal direction of the corresponding tangent to the simulated curve graph to be checked, the curvature corresponding to each sampling point, and the measured line width at the intersection of the normal of each sampling point and the simulated curve graph to be checked.

[0068] The sampling points can be points set at fixed preset distances on the target curve. It should be noted that the curvature corresponding to the sampling point is the sampling point itself, that is, the curvature of the target curve at that position; while the measured line width is the line width at the intersection of the normal line passing through the sampling point and the simulated curve to be checked, that is, the line width on the simulated curve to be checked.

[0069] S103: Determine the curve position error corresponding to each sampling point based on the deviation distance and curvature of each sampling point.

[0070] The curve position error in this step is a parameter used to characterize the degree of deviation between the simulated curve to be checked and the target curve at that point, obtained by comprehensively considering the deviation distance and curvature of the sampling point.

[0071] Therefore, the larger the curve position error, the greater the deviation between the simulated curve to be investigated and the target curve at that sampling point. Considering the deviation distance and the curvature, it can be understood that for the same deviation distance, the curve position error at a point with greater curvature is greater than the curve position error at a point with less curvature. This is because the deviation distance at a point with greater curvature has a greater impact on the overall shape of the graph.

[0072] As one specific implementation, the curve position error corresponding to each sampling point is determined based on the deviation distance and curvature of each sampling point, including:

[0073] The curve position error corresponding to each sampling point is determined by the following formula (1):

[0074] ; (1)

[0075] Where CEPE(s) is the curve position error at sampling point s, and EPE(s) is the deviation distance at sampling point s. Let be the curvature at sampling point s, and α be the curvature sensitivity coefficient.

[0076] In this specific embodiment, a relatively direct two-term multiplication is adopted. The first term is the curve position error, and the second term is the curvature multiplied by the curvature sensitivity coefficient plus one. The addition of one ensures that the second term is always greater than one and increases with the curvature itself. The curvature sensitivity coefficient can be adjusted according to the actual situation, such as setting it to a fixed value, such as α=1, or setting multiple different curvature value ranges, taking different values ​​according to the different curvatures of the sampling point s; for example, the larger the curvature, the larger the value of α, or when the curvature exceeds a certain preset threshold, the curvature sensitivity coefficient increases rapidly, thereby increasing the weight of sensitive positions with high curvature.

[0077] Preferably, before determining the curve position error corresponding to each sampling point, the method further includes:

[0078] The curvature sensitivity coefficient is determined based on the curvature of each sampling point; wherein the curvature sensitivity coefficient corresponding to the sampling point with smaller curvature is smaller than the curvature sensitivity coefficient corresponding to the sampling point with larger curvature.

[0079] As mentioned above, for curved graphs, the greater the curvature, the greater the impact of deviations at certain points on the overall similarity of the graph, and the more it increases errors in the production process. Therefore, deviations at points with greater curvature should be given more attention. In this preferred embodiment, a technical solution is adopted in which the curvature sensitivity coefficient increases with the curvature, which can further enhance the weight of the curve position error at large curvature sampling points, better reflect the difference between the simulated curve graph to be checked and the target curve graph, and provide more guidance for subsequent adjustments.

[0080] S104: Determine the line width reduction factor for the corresponding sampling point based on the measured line width and the preset design line width.

[0081] The line widths at various points on the simulated curve obtained through OPC simulation are not necessarily the same as the preset design line widths. The current line width reduction factor can be regarded as the ratio of the measured line width to the design line width.

[0082] Specifically, based on the measured line widths and the preset design line widths, the line width reduction factor for the corresponding sampling points is determined, including:

[0083] The line width reduction factor corresponding to each sampling point is determined by the following formula (2):

[0084] ; (2)

[0085] Where LW(s) is the linewidth reduction factor at sampling point s, and w(s) is the measured linewidth at sampling point s. design The design line width is given.

[0086] In this specific embodiment, the ratio of the measured line width to the designed line width is used by subtracting 1. That is, the closer the measured line width is to the designed line width (the measured line width generally does not exceed the designed line width), the better. design The closer LW(s) is to 1, the smaller LW(s) is, meaning the more similar the target curve is to the simulated curve to be checked, and the smaller the linewidth reduction factor is. This preferred embodiment provides a fast linewidth reduction factor calculation and can directly reflect the deviation between the measured linewidth and the designed linewidth; the greater the deviation, the greater the linewidth reduction factor.

[0087] S105: Calculate the shrinkage defect risk value of each sampling point based on the line width reduction coefficient and the curve position error.

[0088] As one specific implementation method, this step includes:

[0089] The shrinkage defect risk value for each sampling point is calculated using the following formula (3):

[0090] ; (3)

[0091] Wherein, CW-PR(s) is the shrinkage defect risk value corresponding to sampling point s, CEPE(s) is the curve position error at sampling point s, and LW(s) is the line width reduction coefficient at sampling point s.

[0092] In this specific embodiment, the shrinkage defect risk value is the product of the line width reduction coefficient and the curve position error. The magnitudes of the line width reduction coefficient and the curve position error are both proportional to the deviation between the target curve and the simulated curve to be checked. This preferred embodiment requires less computing power to calculate the shrinkage defect risk value and has a fast calculation speed.

[0093] S106: Determine whether the shrinkage defect risk value exceeds a preset tolerance threshold.

[0094] Exceeding the tolerance threshold does not necessarily mean that the sampling point is a shrinkage defect, but it certainly indicates that there is a high probability that the shrinkage defect will occur at that location.

[0095] S107: When the shrinkage defect risk value exceeds the tolerance threshold, the corresponding sampling point is determined as a shrinkage defect risk point.

[0096] After identifying the shrinkage defect risk points, adjustments can be made based on these risk points. For details, please refer to relevant technical documents.

[0097] The photolithography shrinkage defect verification method provided by this invention involves receiving a target curve graphic and a simulated curve graphic to be checked obtained by OPC processing of the target curve graphic; determining sampling points on the target curve graphic and acquiring the deviation distance from the normal direction of the corresponding tangent of each sampling point to the simulated curve graphic to be checked, the curvature of each sampling point, and the measured linewidth at the intersection of the normal of each sampling point and the simulated curve graphic to be checked; determining the curve position error corresponding to each sampling point based on the deviation distance and curvature of each sampling point; determining the linewidth reduction factor of the corresponding sampling point based on the measured linewidth and the preset design linewidth; calculating the shrinkage defect risk value of each sampling point based on the linewidth reduction factor and the curve position error; determining whether the shrinkage defect risk value exceeds a preset tolerance threshold; and identifying the corresponding sampling point as a shrinkage defect risk point when the shrinkage defect risk value exceeds the tolerance threshold. This invention sets multiple sampling points on the target curve graphic and evaluates the risk of shrinkage defects at each sampling point from two aspects: the deviation between the simulated curve to be checked obtained from OPC simulation and the target curve graphic (i.e., the curve position error) and the deviation between the line width at the sampling point and the designed line width (i.e., the line width reduction factor). (The greater the deviation in the above two aspects, the higher the risk of shrinkage defects at the corresponding position). This identifies potential hidden risk areas with shrinkage defects, thereby greatly improving the detection accuracy of shrinkage defects, reducing the probability of missed defects, and being applicable to graphics with various curvature edges. This greatly improves the versatility of the verification method and provides a quantitative, dynamic, and traceable evaluation index for the lithographic verification of complex patterns in advanced processes.

[0098] Based on Implementation Method 1, the method for calculating the shrinkage defect risk value is further improved to obtain Implementation Method 2, the corresponding flowchart of which is shown below. Figure 2 As shown, it includes:

[0099] S201: Receive the target curve graph and the simulated curve graph to be checked obtained by OPC processing of the target curve graph.

[0100] S202: Determine the sampling points on the target curve graph, and obtain the deviation distance of each sampling point from the normal direction of the corresponding tangent to the simulated curve graph to be checked, the curvature corresponding to each sampling point, and the measured line width at the intersection of the normal of each sampling point and the simulated curve graph to be checked.

[0101] S203: Determine the curve position error corresponding to each sampling point based on the deviation distance and curvature of each sampling point.

[0102] S204: Determine the line width reduction factor for the corresponding sampling point based on the measured line width and the preset design line width.

[0103] S205: Determine the exposure dose influence coefficient of the corresponding sampling point based on the measured line width, the preset design line width, and the preset exposure dose.

[0104] S206: Calculate the shrinkage defect risk value of each sampling point based on the linewidth reduction factor, the curve position error, and the exposure dose influence factor.

[0105] S207: Determine whether the shrinkage defect risk value exceeds a preset tolerance threshold.

[0106] S208: When the shrinkage defect risk value exceeds the tolerance threshold, the corresponding sampling point is determined as a shrinkage defect risk point.

[0107] The difference between this specific embodiment and the above specific embodiment is that the exposure dose influence coefficient is also considered when calculating the shrinkage defect risk value in this specific embodiment. The remaining steps are the same as those in the above specific embodiment, and will not be elaborated here.

[0108] In this specific embodiment, the exposure dose influence coefficient is added when calculating the shrinkage defect risk value. This coefficient measures the fluctuation of the measured linewidth due to the influence of the exposure dose; a larger coefficient indicates a greater impact of changes in the exposure dose on the actual linewidth. This embodiment further considers the impact of machine exposure on linewidth during production, thereby improving the accuracy of the shrinkage defect risk value and providing more guidance for subsequent production processes.

[0109] As a preferred embodiment, the shrinkage defect risk value of each sampling point is calculated based on the linewidth reduction factor, the curve position error, and the exposure dose influence factor, including:

[0110] The shrinkage defect risk value of each sampling point is calculated using the following formulas (4) and (5):

[0111] ; (4)

[0112] ; (5)

[0113] Wherein, CW-PR(s) is the shrinkage defect risk value corresponding to sampling point s, CEPE(s) is the curve position error at sampling point s, LW(s) is the linewidth reduction coefficient at sampling point s, D(s) is the exposure dose influence coefficient at sampling point s, w(s) is the measured linewidth at sampling point s, D is the exposure dose, and β is the process coupling coefficient, representing the influence weight of the exposure dose fluctuation on the measured linewidth.

[0114] In this preferred embodiment, a method for calculating the exposure dose influence coefficient is provided. The larger the exposure dose influence coefficient, the greater the influence of the exposure dose on the actual linewidth.

[0115] As another preferred embodiment, the shrinkage defect risk value of each sampling point is calculated based on the linewidth reduction factor, the curve position error, and the exposure dose influence factor, including:

[0116] The shrinkage defect risk value of each sampling point is calculated using the following formulas (6) and (7):

[0117] ; (6)

[0118] ; (7)

[0119] Wherein, CW-PR(s) is the shrinkage defect risk value corresponding to sampling point s, CEPE(s) is the curve position error at sampling point s, LW(s) is the linewidth reduction coefficient at sampling point s, D(s) is the exposure dose influence coefficient at sampling point s, w(s) is the measured linewidth at sampling point s, D is the exposure dose, and β is the process coupling coefficient.

[0120] In this preferred embodiment, the shrinkage defect risk value is obtained by directly multiplying the linewidth reduction factor, the curve position error, and the exposure dose influence factor. In order to ensure that the shrinkage defect risk value increases with the increase of the influence of the exposure dose on the actual linewidth, the exposure dose influence factor is constructed as one plus the measured linewidth and the exposure dose, ensuring that the exposure dose influence factor is greater than one. That is, the shrinkage defect risk value will increase with the increase of the exposure dose influence factor.

[0121] Based on Implementation Method 2, the method for calculating the shrinkage defect risk value is further improved to obtain Implementation Method 3, the corresponding flowchart of which is shown below. Figure 3 As shown, it includes:

[0122] S301: Receive the target curve graph and the simulated curve graph to be checked obtained by OPC processing of the target curve graph.

[0123] S302: Determine the sampling points on the target curve graph, and obtain the deviation distance of each sampling point from the normal direction of the corresponding tangent to the simulated curve graph to be checked, the curvature corresponding to each sampling point, and the measured line width at the intersection of the normal of each sampling point and the simulated curve graph to be checked.

[0124] S303: Determine whether there is a mutation point pair, wherein the mutation point pair is two adjacent sampling points, and the difference in curvature corresponding to the two adjacent sampling points exceeds a preset mutation threshold.

[0125] In the previous step, the curvature of each sampling point was obtained. In this step, the difference between the curvature of each sampling point and its adjacent sampling points can be determined one by one. If the difference exceeds the mutation threshold, the two adjacent sampling points are determined to be the mutation point pair.

[0126] S304: When the mutation point pair exists, add a sampling point between the two sampling points of the mutation point pair.

[0127] In this step, a new sampling point will be added between two sampling points with excessive curvature changes. As a preferred implementation, a new sampling point can be inserted at the midpoint of the abrupt change point pair. Of course, a sampling point can also be inserted at other positions between a pair of abrupt change points, or multiple new sampling points can be inserted at multiple positions.

[0128] S305: Obtain the deviation distance from the normal direction of the corresponding tangent of each of the additional sampling points to the simulated curve to be checked, the curvature of each sampling point, and the measured line width at the intersection of the normal of each sampling point and the simulated curve to be checked.

[0129] This step can be seen as repeating the acquisition operation in step S302 for the newly added sampling points in step S304, and will not be described in detail here.

[0130] S306: Determine the curve position error corresponding to each sampling point based on the deviation distance and curvature of each sampling point.

[0131] S307: Determine the line width reduction factor for the corresponding sampling point based on the measured line width and the preset design line width.

[0132] S308: Determine the exposure dose influence coefficient of the corresponding sampling point based on the measured line width, the preset design line width, and the preset exposure dose.

[0133] S309: Calculate the shrinkage defect risk value of each sampling point based on the linewidth reduction factor, the curve position error, and the exposure dose influence factor.

[0134] S310: Determine whether the shrinkage defect risk value exceeds a preset tolerance threshold.

[0135] S311: When the shrinkage defect risk value exceeds the tolerance threshold, the corresponding sampling point is determined as a shrinkage defect risk point.

[0136] The difference between this specific implementation and the above specific implementation is that in this specific implementation, new sampling points are inserted based on the curvature changes of adjacent sampling points. The remaining steps are the same as those in the above specific implementation and will not be elaborated here.

[0137] The accuracy of sampling results at different positions on the curve is mainly related to the density of sampling points on the curve profile. If the curvature of the curve segment is consistent or changes uniformly, the sampling points can be uniformly set on the curve segment for sampling to measure the corresponding shrinkage defect risk value. However, if the curvature of two adjacent sampling points changes drastically, that is, the difference in curvature between two adjacent sampling points exceeds the preset abrupt change threshold, it is necessary to further increase the sampling points at the corresponding positions, that is, dynamically adjust the number of sampling points inserted into the curve segment to ensure a higher sampling density in the high curvature area, so as to improve the accuracy of detection.

[0138] Furthermore, sampling points can be added in the middle of the mutation point pair using a bisection method until the curve change rate is less than a threshold. That is, a new sampling point is added at the midpoint of the mutation point pair. Then, the curvature difference between the two sampling points in the mutation point pair and the newly added sampling point is calculated. If there is a curvature difference greater than the mutation threshold, new sampling points are added at the key positions of the two sampling points with curvature differences exceeding the mutation threshold until there are no adjacent sampling points with curvature differences exceeding the mutation threshold.

[0139] The following describes the photolithography shrinkage defect verification device provided in the embodiments of the present invention. The photolithography shrinkage defect verification device described below and the photolithography shrinkage defect verification method described above can be referred to each other.

[0140] Figure 4 The structural block diagram of the photolithography shrinkage defect inspection device provided in the embodiment of the present invention is shown below. Figure 4 The photolithography shrinkage defect inspection device may include:

[0141] The receiving module 100 is used to receive the target curve graph and the simulated curve graph to be checked obtained by OPC processing of the target curve graph;

[0142] The sampling point module 200 is used to determine the sampling points on the target curve graph, and to obtain the deviation distance of each sampling point from the normal direction of the corresponding tangent to the simulated curve graph to be checked, the curvature corresponding to each sampling point, and the measured line width at the intersection of the normal of each sampling point and the simulated curve graph to be checked.

[0143] The curve position error module 300 is used to determine the curve position error corresponding to each sampling point based on the deviation distance and curvature of each sampling point.

[0144] The line width reduction module 400 is used to determine the line width reduction coefficient of the corresponding sampling point based on each measured line width and the preset design line width.

[0145] The risk calculation module 500 is used to calculate the shrinkage defect risk value of each sampling point based on the line width reduction coefficient and the curve position error.

[0146] The judgment module 600 is used to determine whether the shrinkage defect risk value exceeds a preset tolerance threshold;

[0147] The risk determination module 700 is used to determine the corresponding sampling point as a shrinkage defect risk point when the shrinkage defect risk value exceeds the tolerance threshold.

[0148] In a preferred embodiment, the risk calculation module 500 includes:

[0149] The shrinkage defect calculation unit is used to calculate the shrinkage defect risk value for each sampling point using the following formula:

[0150] ;

[0151] Wherein, CW-PR(s) is the shrinkage defect risk value corresponding to sampling point s, CEPE(s) is the curve position error at sampling point s, and LW(s) is the line width reduction coefficient at sampling point s.

[0152] In a preferred embodiment, the curve position error module 300 includes:

[0153] The position error calculation unit is used to determine the curve position error corresponding to each of the sampling points using the following formula:

[0154] ;

[0155] Where CEPE(s) is the curve position error at sampling point s, and EPE(s) is the deviation distance at sampling point s. Let be the curvature at sampling point s, and α be the curvature sensitivity coefficient.

[0156] In a preferred embodiment, the curve position error module 300 further includes:

[0157] The curvature coefficient calculation unit is used to determine the corresponding curvature sensitivity coefficient based on the curvature of each sampling point; wherein, the curvature sensitivity coefficient corresponding to the sampling point with smaller curvature is smaller than the curvature sensitivity coefficient corresponding to the sampling point with larger curvature.

[0158] In a preferred embodiment, the linewidth reduction module 400 includes:

[0159] The linewidth reduction factor calculation unit is used to determine the linewidth reduction factor corresponding to each sampling point using the following formula:

[0160] ;

[0161] Where LW(s) is the linewidth reduction factor at sampling point s, and w(s) is the measured linewidth at sampling point s. design The design line width is given.

[0162] In a preferred embodiment, the risk calculation module 500 further includes:

[0163] The exposure dose influence coefficient unit is used to determine the exposure dose influence coefficient of the corresponding sampling point based on the measured line width, the preset design line width and the preset exposure dose.

[0164] Accordingly, the risk calculation module 500 includes:

[0165] The comprehensive risk calculation unit is used to calculate the shrinkage defect risk value of each sampling point based on the linewidth reduction factor, the curve position error, and the exposure dose influence factor.

[0166] In a preferred embodiment, the risk calculation module 500 includes:

[0167] The integrated risk calculation unit is used to calculate the shrinkage defect risk value for each sampling point using the following formula:

[0168] ;

[0169] ;

[0170] Wherein, CW-PR(s) is the shrinkage defect risk value corresponding to sampling point s, CEPE(s) is the curve position error at sampling point s, LW(s) is the linewidth reduction coefficient at sampling point s, D(s) is the exposure dose influence coefficient at sampling point s, w(s) is the measured linewidth at sampling point s, D is the exposure dose, and β is the process coupling coefficient.

[0171] In a preferred embodiment, the risk calculation module 500 includes:

[0172] The integrated shrinkage defect risk calculation unit is used to calculate the shrinkage defect risk value for each sampling point using the following formula:

[0173] ;

[0174] ;

[0175] Wherein, CW-PR(s) is the shrinkage defect risk value corresponding to sampling point s, CEPE(s) is the curve position error at sampling point s, LW(s) is the linewidth reduction coefficient at sampling point s, D(s) is the exposure dose influence coefficient at sampling point s, w(s) is the measured linewidth at sampling point s, D is the exposure dose, and β is the process coupling coefficient.

[0176] In a preferred embodiment, the sampling point module 200 further includes:

[0177] A mutation determination unit is used to determine whether there is a mutation point pair, wherein the mutation point pair is two adjacent sampling points and the difference in curvature corresponding to the two adjacent sampling points exceeds a preset mutation threshold.

[0178] A sampling point adding unit is used to add a sampling point between two sampling points of the mutation point pair when the mutation point pair exists.

[0179] The acquisition unit is used to acquire the deviation distance of each of the additional sampling points along the normal direction of the corresponding tangent to the simulated curve to be checked, the curvature corresponding to each of the sampling points, and the measured line width at the intersection of the normal of each of the sampling points and the simulated curve to be checked.

[0180] The photolithography shrinkage defect verification device of this embodiment is used to implement the aforementioned photolithography shrinkage defect verification method. Therefore, the specific implementation of the photolithography shrinkage defect verification device can be found in the embodiment section of the photolithography shrinkage defect verification method above. For example, the receiving module 100, sampling point module 200, curve position error module 300, linewidth reduction module 400, risk calculation module 500, judgment module 600, and risk determination module 700 are respectively used to implement steps S101, S102, S103, S104, S105, S106, and S107 in the above-mentioned photolithography shrinkage defect verification method. Therefore, its specific implementation can be referred to the description of the corresponding embodiments, which will not be repeated here.

[0181] The present invention also provides a photolithography shrinkage defect inspection device, comprising:

[0182] Memory, used to store computer programs;

[0183] A processor is configured to execute the computer program to implement the steps of photolithography shrinkage defect verification described above. The photolithography shrinkage defect verification method provided by this invention involves: receiving a target curve graphic and a simulated curve graphic to be checked obtained by OPC processing of the target curve graphic; determining sampling points on the target curve graphic and acquiring the deviation distance from the normal direction of the corresponding tangent of each sampling point to the simulated curve graphic to be checked, the curvature corresponding to each sampling point, and the measured linewidth at the intersection of the normal of each sampling point and the simulated curve graphic to be checked; determining the curve position error corresponding to each sampling point based on the deviation distance and curvature of each sampling point; determining the linewidth reduction factor of the corresponding sampling point based on the measured linewidth and the preset design linewidth; calculating the shrinkage defect risk value of each sampling point based on the linewidth reduction factor and the curve position error; determining whether the shrinkage defect risk value exceeds a preset tolerance threshold; and identifying the corresponding sampling point as a shrinkage defect risk point when the shrinkage defect risk value exceeds the tolerance threshold. This invention sets multiple sampling points on the target curve graphic and evaluates the risk of shrinkage defects at each sampling point from two aspects: the deviation between the simulated curve to be checked obtained from OPC simulation and the target curve graphic (i.e., the curve position error) and the deviation between the line width at the sampling point and the designed line width (i.e., the line width reduction factor). (The greater the deviation in the above two aspects, the higher the risk of shrinkage defects at the corresponding position). This identifies potential hidden risk areas with shrinkage defects, thereby greatly improving the detection accuracy of shrinkage defects, reducing the probability of missed defects, and being applicable to graphics with various curvature edges. This greatly improves the versatility of the verification method and provides a quantitative, dynamic, and traceable evaluation index for the lithographic verification of complex patterns in advanced processes.

[0184] This invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of any of the above-described photolithography shrinkage defect verification methods. The photolithography shrinkage defect verification method provided by this invention involves: receiving a target curve graphic and a simulated curve graphic to be checked obtained by OPC processing of the target curve graphic; determining sampling points on the target curve graphic and acquiring the deviation distance from the normal direction of the corresponding tangent of each sampling point to the simulated curve graphic to be checked, the curvature corresponding to each sampling point, and the measured linewidth at the intersection of the normal of each sampling point and the simulated curve graphic to be checked; determining the curve position error corresponding to each sampling point based on the deviation distance and curvature of each sampling point; determining the linewidth reduction factor of the corresponding sampling point based on the measured linewidth and the preset design linewidth; calculating the shrinkage defect risk value of each sampling point based on the linewidth reduction factor and the curve position error; determining whether the shrinkage defect risk value exceeds a preset tolerance threshold; and identifying the corresponding sampling point as a shrinkage defect risk point when the shrinkage defect risk value exceeds the tolerance threshold.

[0185] This invention sets multiple sampling points on the target curve graphic and evaluates the risk of shrinkage defects at each sampling point from two aspects: the deviation between the simulated curve to be checked obtained from OPC simulation and the target curve graphic (i.e., the curve position error) and the deviation between the line width at the sampling point and the designed line width (i.e., the line width reduction factor). (The greater the deviation in the above two aspects, the higher the risk of shrinkage defects at the corresponding position). This identifies potential hidden risk areas with shrinkage defects, thereby greatly improving the detection accuracy of shrinkage defects, reducing the probability of missed defects, and being applicable to graphics with various curvature edges. This greatly improves the versatility of the verification method and provides a quantitative, dynamic, and traceable evaluation index for the lithographic verification of complex patterns in advanced processes.

[0186] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to in the method section.

[0187] It should be noted that, in this specification, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0188] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0189] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0190] The above provides a detailed description of the photolithographic shrinkage defect verification method, apparatus, device, and storage medium provided by this invention. Specific examples have been used to illustrate the principles and implementation methods of this invention. The descriptions of the embodiments above are merely for the purpose of helping to understand the method and core ideas of this invention. It should be noted that those skilled in the art can make various improvements and modifications to this invention without departing from its principles, and these improvements and modifications also fall within the protection scope of this invention.

Claims

1. A method for verifying photolithographic shrinkage defects, characterized in that, include: Receive the target curve graph and the simulated curve graph to be checked obtained by OPC processing of the target curve graph; The sampling points on the target curve are determined, and the deviation distance from the normal direction of the corresponding tangent of each sampling point to the simulated curve to be checked, the curvature of each sampling point, and the measured line width at the intersection of the normal of each sampling point and the simulated curve to be checked are obtained. Based on the deviation distance and curvature of each sampling point, the curve position error corresponding to each sampling point is determined; Based on the measured line width and the preset design line width, determine the line width reduction factor for the corresponding sampling point; Based on the linewidth reduction factor and the curve position error, calculate the shrinkage defect risk value for each sampling point; Determine whether the shrinkage defect risk value exceeds a preset tolerance threshold; When the shrinkage defect risk value exceeds the tolerance threshold, the corresponding sampling point is determined as a shrinkage defect risk point.

2. The photolithographic shrinkage defect verification method as described in claim 1, characterized in that, Based on the linewidth reduction factor and the curve position error, the shrinkage defect risk value of each sampling point is calculated, including: The shrinkage defect risk value for each sampling point is calculated using the following formula: ； Where CW-PR(s) is the shrinkage defect risk value corresponding to sampling point s, CEPE(s) is the curve position error at sampling point s, and LW(s) is the line width reduction coefficient at sampling point s. Based on the deviation distance and curvature of each sampling point, the curve position error corresponding to each sampling point is determined, including: The curve position error corresponding to each sampling point is determined by the following formula: ； Where CEPE(s) is the curve position error at sampling point s, and EPE(s) is the deviation distance at sampling point s. Let be the curvature at sampling point s, and α be the curvature sensitivity coefficient; Based on the measured linewidths and the preset design linewidths, determine the linewidth reduction factor for the corresponding sampling points, including: The linewidth reduction factor corresponding to each sampling point is determined by the following formula: ； Where LW(s) is the linewidth reduction factor at sampling point s, and w(s) is the measured linewidth at sampling point s. design The design line width is given.

3. The photolithographic shrinkage defect verification method as described in claim 2, characterized in that, Before determining the curve position error corresponding to each of the sampling points, the method further includes: The curvature sensitivity coefficient is determined based on the curvature of each sampling point; wherein the curvature sensitivity coefficient corresponding to the sampling point with smaller curvature is smaller than the curvature sensitivity coefficient corresponding to the sampling point with larger curvature.

4. The photolithographic shrinkage defect verification method as described in claim 1, characterized in that, Before calculating the shrinkage defect risk value of each sampling point based on the linewidth reduction factor and the curve position error, the method further includes: Based on the measured linewidth, the preset design linewidth, and the preset exposure dose, determine the exposure dose influence coefficient of the corresponding sampling point; Accordingly, based on the linewidth reduction factor and the curve position error, the shrinkage defect risk value of each sampling point is calculated, including: The shrinkage defect risk value of each sampling point is calculated based on the linewidth reduction factor, the curve position error, and the exposure dose influence factor.

5. The photolithographic shrinkage defect verification method as described in claim 4, characterized in that, Based on the linewidth reduction factor, the curve position error, and the exposure dose influence factor, the shrinkage defect risk value for each sampling point is calculated, including: The shrinkage defect risk value for each sampling point is calculated using the following formula: ； ； Wherein, CW-PR(s) is the shrinkage defect risk value corresponding to sampling point s, CEPE(s) is the curve position error at sampling point s, LW(s) is the linewidth reduction coefficient at sampling point s, D(s) is the exposure dose influence coefficient at sampling point s, w(s) is the measured linewidth at sampling point s, D is the exposure dose, and β is the process coupling coefficient. Based on the deviation distance and curvature of each sampling point, the curve position error corresponding to each sampling point is determined, including: The curve position error corresponding to each sampling point is determined by the following formula: ； Where CEPE(s) is the curve position error at sampling point s, and EPE(s) is the deviation distance at sampling point s. Let be the curvature at sampling point s, and α be the curvature sensitivity coefficient; Based on the measured linewidths and the preset design linewidths, determine the linewidth reduction factor for the corresponding sampling points, including: The linewidth reduction factor corresponding to each sampling point is determined by the following formula: ； Where LW(s) is the linewidth reduction factor at sampling point s, and w(s) is the measured linewidth at sampling point s. design The design line width is given.

6. The photolithographic shrinkage defect verification method as described in claim 4, characterized in that, Based on the linewidth reduction factor, the curve position error, and the exposure dose influence factor, the shrinkage defect risk value for each sampling point is calculated, including: The shrinkage defect risk value for each sampling point is calculated using the following formula: ； ； Wherein, CW-PR(s) is the shrinkage defect risk value corresponding to sampling point s, CEPE(s) is the curve position error at sampling point s, LW(s) is the linewidth reduction coefficient at sampling point s, D(s) is the exposure dose influence coefficient at sampling point s, w(s) is the measured linewidth at sampling point s, D is the exposure dose, and β is the process coupling coefficient. Based on the deviation distance and curvature of each sampling point, the curve position error corresponding to each sampling point is determined, including: The curve position error corresponding to each sampling point is determined by the following formula: ； Where CEPE(s) is the curve position error at sampling point s, and EPE(s) is the deviation distance at sampling point s. Let be the curvature at sampling point s, and α be the curvature sensitivity coefficient; Based on the measured linewidths and the preset design linewidths, determine the linewidth reduction factor for the corresponding sampling points, including: The linewidth reduction factor corresponding to each sampling point is determined by the following formula: ； Where LW(s) is the linewidth reduction factor at sampling point s, and w(s) is the measured linewidth at sampling point s. design The design line width is given.

7. The method for verifying photolithographic shrinkage defects as described in any one of claims 1 to 6, characterized in that, After obtaining the curvature corresponding to each of the sampling points, the method further includes: Determine whether there is a mutation point pair, wherein the mutation point pair is two adjacent sampling points, and the difference in curvature corresponding to the two adjacent sampling points exceeds a preset mutation threshold. When the mutation point pair exists, additional sampling points are added between the two sampling points of the mutation point pair; Obtain the deviation distance from the normal direction of the corresponding tangent of each of the additional sampling points to the simulated curve to be checked, the curvature of each sampling point, and the measured line width at the intersection of the normal of each sampling point and the simulated curve to be checked.

8. A photolithographic shrinkage defect inspection device, characterized in that, include: The receiving module is used to receive the target curve graph and the simulated curve graph to be checked obtained by OPC processing of the target curve graph; The sampling point module is used to determine the sampling points on the target curve graph, and to obtain the deviation distance of each sampling point from the normal direction of the corresponding tangent to the simulated curve graph to be checked, the curvature corresponding to each sampling point, and the measured line width at the intersection of the normal of each sampling point and the simulated curve graph to be checked. The curve position error module is used to determine the curve position error corresponding to each sampling point based on the deviation distance and curvature of each sampling point. The line width reduction module is used to determine the line width reduction coefficient of the corresponding sampling point based on the measured line width and the preset design line width. The risk calculation module is used to calculate the shrinkage defect risk value of each sampling point based on the line width reduction coefficient and the curve position error; The judgment module is used to determine whether the shrinkage defect risk value exceeds a preset tolerance threshold; The risk determination module is used to determine the corresponding sampling point as a shrinkage defect risk point when the shrinkage defect risk value exceeds the tolerance threshold.

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