Method and apparatus for detecting wafer defects

Abstract

The present application relates to the semiconductor technical field and provides a method and apparatus for detecting wafer defects, the method including: determining repeating pattern units and non-repeating pattern units in the SEM image based on a target SEM image and pattern units in a design layout; measuring the pattern units, repeating pattern units, and non-repeating pattern units in the design layout to determine difference information; and determining whether the repeating pattern units and non-repeating pattern units have defects based on the difference information. In this way, by measuring the SEM image and the pattern units in the design layout, difference information that can represent the SEM image is obtained, and then defect detection is performed on the SEM image based on the difference information. Since the characteristics of the SEM image and the pattern units in the design layout are fully taken into account in the defect detection process, the determined difference information is more comprehensive and reliable, thereby improving the accuracy and reliability of subsequent wafer defect detection.

Description

Technical Field

[0001] This application relates to the field of semiconductor technology, and particularly to a method and apparatus for detecting wafer defects.

Background Art

[0002] With the development of the semiconductor industry, the application of integrated circuits is also becoming increasingly widespread. The manufacturing process of integrated circuits includes many processes, and in each process, the wafer may be contaminated. Therefore, in the wafer manufacturing process, defect detection of the wafer is essential.

[0003] In related technologies, when defect detection is performed on a wafer, usually, a certain threshold is set. When the difference degree between the wafer to be detected and the reference wafer exceeds the threshold, it is determined that the wafer has a defect. However, since the threshold is a fixed value, when the image to be detected is complex, if detection omission or false detection occurs, it may affect the accuracy of wafer defect detection. Therefore, it is extremely important to improve the accuracy of wafer defect detection.

Summary of the Invention

[0004] This application provides a method and apparatus for detecting wafer defects.

[0005] According to a first aspect of this application, based on a SEM image to be detected and pattern units in a design layout, determining repeating pattern units and non-repeating pattern units in the SEM image; measuring the pattern units in the design layout, the repeating pattern units, and the non-repeating pattern units to determine difference information; and determining whether there are defects in the repeating pattern units and non-repeating pattern units based on the difference information, thereby providing a method for detecting wafer defects.

[0006] In some embodiments, determining repeating and non-repeating pattern units in an SEM image based on the SEM image to be detected and pattern units in the design layout includes processing the SEM image to obtain pattern contours in the SEM image and comparing the pattern contours with pattern units in the design layout to determine repeating and non-repeating pattern units in the SEM image.

[0007] In some embodiments, determining difference information by measuring pattern units, repeating pattern units and non-repeating pattern units in the design layout includes: dividing the non-repeating pattern units to obtain repeating sub-pattern units and isolated sub-pattern units; setting measurement points in the repeating pattern units and repeating sub-pattern units to determine first measurement data; setting measurement points at the same locations in the corresponding target pattern units in the design layout to determine second measurement data; and determining difference information based on the first and second measurement data.

[0008] In some embodiments, determining difference information based on the first measurement data and the second measurement data includes determining difference information corresponding to each measurement type based on the measurement type of the first measurement data and the measurement type of the second measurement data.

[0009] In some embodiments, determining whether the repeating pattern unit and the non-repeating pattern unit are defective based on the difference information includes determining the mean and standard deviation corresponding to the measurement type based on the measurement type of the first and second measurement data corresponding to the difference information, and determining whether the repeating pattern unit or the repeating sub-pattern unit is defective based on each of the first measurement data, the corresponding mean and standard deviation corresponding to the measurement type.

[0010] In some embodiments, determining whether a repeating pattern unit or repeating sub-pattern unit is defective based on each of the first measurement data, corresponding mean and standard deviation, corresponding to the measurement type, includes determining a measurement threshold corresponding to the measurement type based on the mean and standard deviation corresponding to the measurement type; determining that the repeating pattern unit or repeating sub-pattern unit in which any of the first measurement data is located is defective if any of the first measurement data is greater than the measurement threshold of the measurement type; determining the repeating pattern unit or repeating sub-pattern unit in which any of the first measurement data is located as an abnormal pattern unit, and storing the abnormal pattern unit and any of the first measurement data in an abnormal feature library.

[0011] In some embodiments, determining whether the repeating pattern units and non-repeating pattern units are defective based on the difference information includes comparing the isolated sub-pattern units with abnormal pattern units in the abnormal feature library to determine the degree of matching, and determining whether the isolated sub-pattern units are defective based on the degree of matching.

[0012] According to a second aspect of this application, a wafer defect detection apparatus is provided, comprising: a first determination module for determining repeating and non-repeating pattern units in an SEM image based on the SEM image to be detected and pattern units in a design layout; a measurement module for determining difference information by measuring the pattern units in the design layout, the repeating and non-repeating pattern units; and a second determination module for determining whether or not the repeating and non-repeating pattern units have defects based on the difference information.

[0013] In some embodiments, the first determination module is specifically used to process the SEM image to obtain pattern contours within the SEM image, and to compare the pattern contours with pattern units in the design layout to determine repeating and non-repeating pattern units within the SEM image.

[0014] In some embodiments, the measurement module includes: a splitting submodule for splitting the non-repeating pattern unit to obtain repeating sub-pattern units and isolated sub-pattern units; a first determination submodule for setting measurement points in the repeating pattern unit and the repeating sub-pattern units to determine first measurement data; a second determination submodule for setting measurement points at the same locations on a target pattern unit corresponding to the design layout to determine second measurement data; and a third determination submodule for determining difference information based on the first and second measurement data.

[0015] In some embodiments, the third determination submodule is used to determine difference information corresponding to each measurement type, based on the measurement type of the first measurement data and the measurement type of the second measurement data.

[0016] In some embodiments, the second determination module includes a fourth determination submodule for determining the mean and standard deviation corresponding to the measurement type based on the first measurement data and the measurement type of the second measurement data corresponding to the difference information, and a fifth determination submodule for determining whether the repeating pattern unit or repeating subpattern unit is defective based on each of the first measurement data, the corresponding mean and standard deviation corresponding to the measurement type.

[0017] In some embodiments, the fifth determination submodule includes: a first determination unit for determining a measurement threshold corresponding to the measurement type based on the mean and standard deviation corresponding to the measurement type; a second determination unit for determining that if any of the first measurement data is greater than the measurement threshold of the measurement type, the repeating pattern unit or repeating subpattern unit in which any of the first measurement data is located is defective; and a third determination unit for determining the repeating pattern unit or repeating subpattern unit in which any of the first measurement data is located as an abnormal pattern unit and storing the abnormal pattern unit and any of the first measurement data in an abnormal feature library.

[0018] In some embodiments, the second decision module is specifically used to compare the isolated subpattern unit with anomaly pattern units in an anomaly feature library to determine the degree of matching, and to determine whether the isolated subpattern unit is defective based on the degree of matching.

[0019] According to a third aspect of this application, the present invention provides an electronic device comprising a processor and a memory storing computer program instructions, wherein when the processor executes a computer program instruction, a method for detecting any of the above-mentioned wafer defects is realized.

[0020] According to a fourth aspect of this application, a computer-readable storage medium is provided which stores computer program instructions, and which enables a method for detecting any of the above-mentioned wafer defects when the computer program instructions are executed by a processor.

[0021] As described above, the method and apparatus for detecting wafer defects according to this application achieve at least the following beneficial effects. First, based on the SEM image to be detected and the pattern units in the design layout, repeating and non-repeating pattern units in the SEM image are determined. Next, the pattern units, repeating and non-repeating pattern units in the design layout are measured to determine difference information. Then, based on the difference information, it is possible to determine whether or not there are defects in the repeating and non-repeating pattern units. This allows for the acquisition of possible difference information representing the SEM image by measuring the SEM image and the pattern units in the design layout during the wafer defect detection process. Subsequently, defect detection can be performed on the SEM image based on this difference information. Since the characteristics of the SEM image and the pattern units in the design layout are fully considered during the defect detection process, the determined difference information becomes more comprehensive and reliable, improving the accuracy and reliability of subsequent wafer defect detection. [Brief explanation of the drawing]

[0022] The drawings described herein are provided for further understanding of this application and constitute part of this application. The exemplary embodiments and descriptions herein are for interpretive purposes only and do not constitute an inappropriate limitation to this application. The figures are as follows: [Figure 1] This is a flowchart of a method for detecting wafer defects according to an embodiment of this application. [Figure 2] This is a schematic diagram of the design layout and the SEM image to be detected according to an embodiment of this application. [Figure 3] This is a flowchart of a method for detecting wafer defects according to an embodiment of this application. [Figure 4] This is a schematic diagram showing the SEM image, which is the target of detection according to the embodiment of this application, after it has been divided. [Figure 5] This is a structural diagram of a device for detecting wafer defects according to an embodiment of this application. [Figure 6]This is a structural diagram of an electronic device according to an embodiment of the present application.

Embodiments for Carrying Out the Invention

[0023] Hereinafter, in order to make the above and other features and advantages of the present application more clear, the present application will be further described with reference to the accompanying drawings. It should be understood that the specific embodiments provided in this specification are for the purpose of explaining to those skilled in the art and are merely exemplary and not restrictive.

[0024] In the following description, many specific details are set forth in order to provide a thorough understanding of the present application. However, it will be apparent to those skilled in the art that the present application may be practiced without these specific details. In other instances, well-known steps or operations are not described in detail so as not to obscure the present application.

[0025] The method for detecting wafer defects according to an embodiment of the present application can be executed by a device for detecting wafer defects according to an embodiment of the present application that can be equipped in an electronic device.

[0026] Referring to FIG. 1, the present application provides a method for detecting wafer defects. The method includes the following steps.

[0027] In step 101, based on the SEM image to be detected and the pattern units in the design layout, the repeated pattern units and non-repeated pattern units in the SEM image are determined.

[0028] Here, a scanning electron microscope (SEM) image, also called a scanning electron microscope image, is an image collected by secondary electrons, backscattered electrons, etc. generated by the interaction between electrons and a wafer when a finely focused electron beam collides with the surface of the wafer, and the SEM image can be used to perform defect detection and analysis on the wafer.

[0029] What can be understood is that, generally, for a wafer to be detected, first an SEM image of it can be acquired, then a design layout corresponding to that wafer can be acquired, and then by aligning and comparing the SEM image with the pattern units in the corresponding design layout, repeating and non-repeating pattern units in the SEM image can be determined.

[0030] Here, when the SEM image of the wafer to be detected is aligned with the design layout, if a pattern unit 1 in the SEM image of the wafer to be detected matches multiple pattern units in the design layout, then it can be determined that the pattern unit 1 is a repeating pattern unit. Alternatively, if a pattern unit 2 appears multiple times in the design layout, and a pattern unit 3 in the SEM image matches the pattern unit 2 that appears multiple times in the design layout, then it can be determined that the pattern unit 3 is a repeating pattern unit. Alternatively, if a pattern unit 4 appears only once in the design layout, then it can be determined that the pattern unit 5 corresponding to the pattern unit 4 in the SEM image is a non-repeating pattern unit.

[0031] What can be understood is that the number of repeating pattern units in an SEM image may be one, multiple, or zero, and the number of non-repeating pattern units may be zero, one, multiple, etc., and is not limited to these in this application.

[0032] Optionally, the SEM image can be processed to obtain pattern contours within the SEM image, and then the pattern contours can be compared with pattern units in the design layout to determine repeating and non-repeating pattern units within the SEM image.

[0033] Here, the SEM image can be processed by any preferred method, such as image extraction or contour extraction, to obtain pattern contours within the SEM image. Then, each pattern contour in the SEM image can be aligned with each pattern unit in the design layout based on, for example, position coordinates or center points, and a comparison can be performed. Based on the comparison results, repeating and non-repeating pattern units in the SEM image can then be determined.

[0034] For example, the pattern contour obtained by processing the SEM image is shown in Figure 2(a), the pattern units in the design layout are shown in Figure 2(b), and the schematic diagram after aligning the two is shown in Figure 2(c). Since pattern units 1', 2', 3', and 4' in the design layout are the same pattern that appears repeatedly, their corresponding pattern units 1, 2, 3, and 4 in the SEM image are repeating pattern units, and since 5' in the design layout appears only once, 5 in the SEM image is a non-repeating pattern unit.

[0035] The above examples are merely illustrative and do not limit the shape, number, position, etc., of the repeating pattern units and non-repeating pattern units in the embodiments of this application.

[0036] In step 102, the pattern units, repeating pattern units, and non-repeating pattern units within the design layout are measured to determine the difference information.

[0037] Here, the non-repeating pattern unit may be a complex pattern unit, and in the embodiments of this application, the non-repeating pattern unit may be divided to obtain corresponding repeating sub-pattern units and isolated sub-pattern units. Here, the number of repeating sub-pattern units obtained by the division may be one, multiple, or zero, and the number of isolated sub-pattern units may be one, zero, or multiple, but is not limited to these in this application.

[0038] For example, if a non-repeating pattern unit is divided to obtain four identical rectangular patterns and one irregular pattern, the four identical rectangular patterns are repeating sub-pattern units, and the irregular pattern is an isolated sub-pattern unit.

[0039] The above examples are merely illustrative and do not limit the shape, number, and position of the repeating subpattern units and isolated subpattern units in the embodiments of this application.

[0040] Here, after determining the repeating and non-repeating pattern units in the SEM image, the repeating pattern units and the corresponding target pattern units in the design layout can be measured, and difference information corresponding to the repeating pattern units can be determined based on the measurement results. Next, the non-repeating pattern units can be divided to obtain repeating sub-pattern units and isolated sub-pattern units obtained by dividing the non-repeating pattern units, and the repeating sub-pattern units and the target pattern units in the design layout can be measured, and difference information of the repeating sub-pattern units can be determined based on the measurement results.

[0041] Furthermore, difference information may be understood as the difference or percentage between the measurement results of a repeating pattern unit and the corresponding target pattern unit in the design layout, and the difference or percentage between the measurement results of a repeating sub-pattern unit and the corresponding target pattern unit in the design layout. Difference information may also be used to represent the degree of difference between a repeating pattern unit and the target pattern unit in the design layout, and the degree of difference between a non-repeating pattern unit and the target pattern unit in the design layout. Difference information may include one difference data, or multiple difference data, and this application is not limited thereto.

[0042] Thus, in the embodiments of this application, pattern units, repeating pattern units, and non-repeating pattern units within the design layout can be measured, and difference information can be determined based on the measurement results. Since the pattern units within the design layout and the pattern units in the SEM image are fully considered in the process of determining the difference information, the difference information becomes more comprehensive and reliable, and can better reflect the characteristics of the SEM image. This comprehensive and reliable difference information can then be applied to subsequent wafer defect detection.

[0043] In step 103, based on the difference information, it is determined whether or not there are defects in the repeating pattern units and non-repeating pattern units.

[0044] What can be understood is that difference information can be used to represent the degree of difference between repeating pattern units and target pattern units in the design layout, and the degree of difference between non-repeating pattern units and target pattern units in the design layout. Therefore, the larger the difference information, the higher the probability that there are defects in both the repeating and non-repeating pattern units, and the smaller the difference information, the lower the probability that there are defects in both the repeating and non-repeating pattern units.

[0045] For example, if the difference between a repeating pattern unit and its corresponding target pattern unit in the design layout is "0", then the repeating pattern unit is considered to be in agreement with its corresponding target pattern unit in the design layout, and therefore the repeating pattern unit is considered to be free of defects. If the difference between a repeating pattern unit and its corresponding target pattern unit in the design layout is "1", then the repeating pattern unit is considered to be in agreement with its corresponding target pattern unit in the design layout, and therefore the repeating pattern unit is considered to be defective.

[0046] The above examples are merely illustrative and do not limit the methods for determining whether or not the repeating pattern units and non-repeating pattern units in the embodiments of this application are defective.

[0047] Thus, in the embodiments of this application, pattern units, repeating pattern units, and non-repeating pattern units within the design layout are measured to determine difference information, and based on this difference information, it is possible to determine whether or not there are defects in the repeating pattern units and non-repeating pattern units. In other words, by fully considering the SEM image and the pattern units within the design layout in the process of determining the difference information, the determined difference information becomes more comprehensive and reliable, and can better reflect the characteristics of the SEM image. Furthermore, when defect detection is performed on the wafer using this comprehensive and reliable difference information, both the accuracy and reliability are improved.

[0048] In the embodiments of this application, first, repeating and non-repeating pattern units in an SEM image are determined based on the SEM image to be detected and the pattern units in the design layout. Next, the pattern units, repeating and non-repeating pattern units in the design layout are measured to determine difference information. Then, based on the difference information, it is possible to determine whether or not there are defects in the repeating and non-repeating pattern units. This allows for the acquisition of difference information that can represent the SEM image by measuring the SEM image and the pattern units in the design layout during the wafer defect detection process. Subsequently, defect detection can be performed on the SEM image based on this difference information. By fully considering the characteristics of the SEM image and the pattern units in the design layout during the defect detection process, the determined difference information becomes more comprehensive and reliable, improving the accuracy and reliability of subsequent wafer defect detection.

[0049] As shown in Figure 3, the method for detecting the wafer defect may include the following steps.

[0050] In step 301, repeating and non-repeating pattern units in the SEM image are determined based on the SEM image to be detected and the pattern units in the design layout.

[0051] In step 302, the non-repeating pattern units are divided to obtain repeating sub-pattern units and isolated sub-pattern units.

[0052] Here, non-repeating pattern units may be divided using any preferred method to obtain repeating sub-pattern units and isolated sub-pattern units. For example, by dividing a non-repeating pattern unit according to methods such as line width or line end, sub-pattern units such as line width sub-pattern units and line end sub-pattern units may be obtained. If a sub-pattern unit appears multiple times, i.e., there are multiple instances, it may be determined that the sub-pattern unit is a repeating sub-pattern unit. If a sub-pattern unit appears only once, i.e., there is only one instance, it may be determined that the sub-pattern unit is an isolated sub-pattern unit. This application is not limited to these cases.

[0053] In step 303, measurement points are set on the repeating pattern unit and the repeating sub-pattern unit to determine the first measurement data.

[0054] Here, the number of measurement points may be one or multiple, and the type of measurement points may be one or multiple; however, this application is not limited to these.

[0055] Here, for repeating pattern units and repeating sub-pattern units of the same type, measurement points may be set according to the same rules, and the repeating pattern units and repeating sub-pattern units may be measured respectively to obtain first measurement data corresponding to the repeating pattern unit, first measurement data corresponding to the repeating sub-pattern unit, etc., and this application is not limited thereto.

[0056] Optionally, non-repeating pattern units may be divided according to line width, line ends, etc., to obtain repeating sub-pattern units and isolated sub-pattern units, and then detection frames may be placed within each repeating sub-pattern unit. For example, corresponding detection frames may be set according to the position, characteristics, etc., of each repeating sub-pattern unit, and this application is not limited thereto.

[0057] What can be understood is that for each repeating pattern unit and repeating sub-pattern unit, the number of detection frames installed may be one or multiple, and this application is not limited to the number and type of installed detection frames.

[0058] For example, in the schematic diagram shown in Figure 4, pattern units 1, 2, 3, and 4 in Figure 4 are repeating pattern units, and pattern unit 5 is a non-repeating pattern unit. Next, the non-repeating pattern unit is divided to obtain repeating sub-pattern units such as line width sub-pattern units and line end sub-pattern units, and isolated sub-pattern units. Furthermore, for example, a line width region detection frame is provided for the line width sub-pattern unit, and a line end region detection frame is provided for the line end sub-pattern unit. In Figure 4, a line end region detection frame is provided for repeating sub-pattern unit 1, which is the black hatched region A, a line width region detection frame is provided for repeating sub-pattern unit 2, which is the intersecting line region B, and the irregular region C is an isolated sub-pattern unit.

[0059] Next, within the repeating subpattern unit 1, which is the black hatched region A, measurement points are set at intervals of n1 μm. By measuring the repeating subpattern unit corresponding to the black hatched region A, first measurement data corresponding to the line end type can be obtained. Next, within the repeating subpattern unit 2, which is the intersecting line region B, measurement points are set at intervals of n2 μm. By measuring the repeating subpattern unit corresponding to the intersecting line region B, first measurement data corresponding to the line width type can be obtained.

[0060] Here, n1 and n2 may be the same or different, and are not limited to this in this application.

[0061] What can be understood is that the region corresponding to the measurement point may contain the contours of repeating pattern units, the contours of repeating sub-pattern units, or it may not contain the contours of any pattern units, and this application is not limited to this.

[0062] The above examples are merely illustrative and do not limit the repeating subpattern units, isolated subpattern units, and methods for determining the first measurement data in the embodiments of this application.

[0063] In step 304, a measurement point is set at the same location on the corresponding target pattern unit within the design layout to determine the second measurement data.

[0064] Here, after setting measurement points in the repeating pattern units and repeating sub-pattern units, the same measurement points may be set at the same positions in the target pattern units corresponding to the repeating pattern units and the target pattern units corresponding to the repeating sub-pattern units in the design layout, according to the corresponding rules, thereby measuring each target pattern unit and obtaining corresponding second measurement data.

[0065] For example, if measurement points are set at intervals of n1 μm within a repeating sub-pattern unit 1, measurement points can be set at the same positions on the target pattern unit 1 of the design layout corresponding to the repeating sub-pattern unit 1. For example, by setting measurement points at intervals of n1 μm, the target pattern unit 1 can be measured, and second measurement data corresponding to the line end type can be obtained. If measurement points are set at intervals of n2 μm within a repeating sub-pattern unit 2, measurement points can be set at the same positions on the target pattern unit 2 of the design layout corresponding to the repeating sub-pattern unit 2. For example, by setting measurement points at intervals of n2 μm, the target pattern unit 2 can be measured, and second measurement data corresponding to the line width type can be obtained.

[0066] What can be understood is that the region corresponding to the measurement point may contain the contours of repeating pattern units, the contours of repeating sub-pattern units, or it may not contain the contours of any pattern units, and this application is not limited to this.

[0067] Here, n1 and n2 may be the same or different, and target pattern unit 1 and target pattern unit 2 may be the same or different, and are not limited to this in this application.

[0068] In step 305, difference information is determined based on the first measurement data and the second measurement data.

[0069] What can be understood is that, after measuring repeating pattern units and repeating sub-pattern units to obtain corresponding first measurement data, and then measuring the target pattern unit in the design layout using the same measurement method to obtain corresponding second measurement data, it is also possible to determine the difference information of the repeating pattern units where each measurement point is located relative to the target pattern unit in the design layout, the difference information of the repeating sub-pattern units where each measurement point is located relative to the target pattern unit in the design layout, and so on, and this application is not limited thereto.

[0070] Optionally, difference information corresponding to each measurement type may be determined based on the measurement type of the first measurement data and the measurement type of the second measurement data. Here, there may be multiple measurement types, for example, line width type, line end type, etc., or they may be divided into line width type 1, line width type 2, line width type 3, etc., depending on different specific values, and this application is not limited thereto.

[0071] Furthermore, the difference information may be understood as difference data, and may, for example, be difference data such as difference values ​​or percentages between pattern units in an SEM image and pattern units in a design layout, but is not limited to this in this application.

[0072] For example, if line width 1 corresponds to interval n1, measurement points 1, 2, and 3 are set within a repeating sub-pattern unit 1 with an interval of n1 μm, and the same measurement points 1', 2', and 3' are set within a target pattern unit 1' in the design layout corresponding to the repeating sub-pattern unit 1 with an interval of n1 μm, and if there is no pattern contour at measurement point 2, then 1 / 3 may be determined as difference information for contour loss detection corresponding to line width 1. If the first measurement data corresponding to measurement points 1 and 3 are both 5 μm, and the second measurement data corresponding to measurement points 1' and 3' are 4.9 μm and 5 μm, respectively, then the difference values ​​between the first measurement data and the second measurement data corresponding to measurement points 1 and 3 are 0.1 and 0, respectively, and 0.1 and 0 may be determined as difference information for contour change detection corresponding to line width 1.

[0073] The above examples are merely illustrative and do not limit the methods for determining the difference information in the embodiments of this application.

[0074] As an option, the number of detection frames installed in each repeating sub-pattern unit and repeating pattern unit may be one or multiple. Therefore, when determining the difference information for contour loss detection, the difference value corresponding to each detection frame may be determined, or the difference value corresponding to a single repeating sub-pattern unit or repeating pattern unit may be determined. For example, if repeating sub-pattern unit 3 has a total of 3 detection frames, each detection frame has 5 measurement points, and the number of measurement points without pattern contours in each detection frame is 1, 0, and 3 respectively, then the corresponding contour loss detection difference data for each detection frame is 1 / 5, 0, and 3 / 5, respectively, and the corresponding contour loss detection difference data for the repeating sub-pattern unit 3 is 4 / 15.

[0075] The above examples are merely illustrative and do not limit the methods for determining the difference information for which contours are reliably detected in the embodiments of this application.

[0076] What can be understood is that for each measurement type, the difference information for contour loss detection and the difference information for contour change detection in each measurement type can be determined separately, and the relevant implementation methods can be found in the descriptions of each embodiment of this application, which will not be repeated here.

[0077] Optionally, the detection frames installed in each of the repeating pattern unit and the repeating sub-pattern unit may be of one type or multiple types. Next, by setting detection points in each detection frame according to certain rules, the repeating pattern unit and the repeating sub-pattern unit can be measured.

[0078] In step 306, the mean and standard deviation corresponding to the measurement type are determined based on the measurement type of the first and second measurement data corresponding to the difference information.

[0079] For example, if the difference information for contour loss detection corresponding to line width 1 is 1 / 3, 2 / 3, 1 / 3, and 2 / 3, it can be determined that the corresponding mean is 1 / 2 and the standard deviation is 1 / 6. If the difference information for contour change detection corresponding to line width 1 is 0.1, 0, 0, and 0.1, it can be determined that the corresponding mean is 0.05 and the standard deviation is 0.05.

[0080] Accordingly, the same method can be used to determine the mean and standard deviation of contour loss detection and contour change detection corresponding to different line widths, and to determine the mean and standard deviation of contour loss detection and contour change detection corresponding to different line ends, thereby determining the mean and standard deviation corresponding to each measurement type.

[0081] The above examples are merely illustrative and do not limit the methods for determining the mean and standard deviation corresponding to the measurement type in the embodiments of this application.

[0082] In step 307, it is determined whether a repeating pattern unit or repeating sub-pattern unit is defective based on the corresponding mean and standard deviation of each of the first measurement data corresponding to the measurement type.

[0083] Optionally, a measurement threshold corresponding to a measurement type can be determined based on the mean and standard deviation corresponding to the measurement type. If any of the first measurement data is greater than the measurement threshold for the measurement type, it can be determined that there is a defect in the repeating pattern unit or repeating sub-pattern unit where the first measurement data is located. The repeating pattern unit or repeating sub-pattern unit where the first measurement data is located can then be determined to be an abnormal pattern unit, and the abnormal pattern unit and any of the first measurement data can be stored in the abnormal feature library.

[0084] Here, the measurement threshold may not be a predetermined fixed value, but rather, for example, the measurement threshold for each measurement type may be determined based on the relationship that the mean and standard deviation corresponding to each measurement type satisfy.

[0085] Furthermore, the anomaly feature library may include anomaly pattern units, measurement data for each anomaly pattern, or both, and is not limited to these in this application.

[0086] For example, in contour change detection corresponding to line width 1 measurement type, the number of first measurement data is n, and the average value is...

number

number

number

[0087] In contour loss detection corresponding to line width 1 measurement type, the number of first measurement data is m, and the average value is,

number

number

number

[0088] The above examples are merely illustrative and do not limit the method for determining abnormal pattern units in the embodiments of this application.

[0089] In step 308, the degree of matching is determined by comparing the isolated subpattern unit with the anomaly pattern unit in the anomaly feature library.

[0090] In step 309, it is determined whether or not an isolated subpattern unit has a defect based on the degree of matching.

[0091] Here, the anomaly feature library may store a large number of anomaly pattern units and measurement data corresponding to each anomaly pattern unit. This may allow for the acquisition of isolated subpattern units after dividing non-repeating units, and the degree of matching between the isolated subpattern units and anomaly pattern units can be determined. Then, based on the degree of matching, it can be determined whether or not the isolated subpattern units have defects.

[0092] What can be understood is that the degree of matching between isolated sub-pattern units and abnormal pattern units can be determined in various ways. For example, the degree of matching between isolated sub-pattern units and abnormal pattern units can be determined by aligning them and determining the degree of matching between them based on the size, shape, contour, position, etc., of each isolated sub-pattern unit and abnormal pattern unit, but this application is not limited to this.

[0093] Optionally, an isolated subpattern unit may be determined to be defective if its degree of matching exceeds a certain threshold, and this application is not limited thereto.

[0094] Optionally, isolated subpattern units may be measured to obtain third measurement data, which may then be compared with the measurement data for each anomaly pattern in the anomaly feature library to determine whether the isolated subpattern unit is defective.

[0095] The above examples are merely illustrative and do not limit the method for determining abnormal pattern units in the embodiments of this application.

[0096] In the embodiment of this application, first, repeating pattern units and non-repeating pattern units in the SEM image can be determined based on the SEM image to be detected and the pattern units in the design layout. Next, the non-repeating pattern units can be divided to obtain repeating sub-pattern units and isolated sub-pattern units. Measurement points can be set on the repeating pattern units and repeating sub-pattern units to determine first measurement data. Then, measurement points can be set at the same positions on the corresponding target pattern units in the design layout to determine second measurement data. Difference information can be determined based on the first and second measurement data. Subsequently, mean and standard deviations corresponding to the measurement type can be determined based on the measurement type of the first and second measurement data corresponding to the difference information. Then, based on each first measurement data, corresponding mean and standard deviation, it can be determined whether or not there is a defect in the repeating pattern unit or repeating sub-pattern unit. The degree of matching can be determined by comparing the isolated sub-pattern unit with the abnormal pattern unit in the abnormal feature library. Subsequently, it can be determined whether or not there is a defect in the isolated sub-pattern unit based on the degree of matching. This allows for the detection of wafer defects by measuring the SEM image and pattern units within the design layout to obtain difference information representing the SEM image, and then performing defect detection on the SEM image based on this difference information. Since the characteristics of the SEM image and pattern units within the design layout are fully considered during the defect detection process, the determined difference information becomes more comprehensive and reliable, improving the accuracy and reliability of subsequent wafer defect detection.

[0097] According to this application, as shown in Figure 5, an apparatus for detecting wafer defects is provided, which includes a first determination module 510, a measurement module 520, and a second determination module 530.

[0098] Here, the first determination module 510 is used to determine repeating and non-repeating pattern units in the SEM image based on the SEM image to be detected and the pattern units in the design layout; the measurement module 520 is used to measure the pattern units in the design layout, the repeating and non-repeating pattern units and determine difference information; and the second determination module 530 is used to determine whether or not the repeating and non-repeating pattern units have defects based on the difference information.

[0099] In some embodiments, the first determination module 510 is specifically used to process the SEM image to obtain pattern contours in the SEM image, and to compare the pattern contours with pattern units in the design layout to determine repeating and non-repeating pattern units in the SEM image.

[0100] In some embodiments, the measurement module 520 includes: a splitting submodule for splitting the non-repeating pattern unit to obtain repeating sub-pattern units and isolated sub-pattern units; a first determination submodule for setting measurement points on the repeating pattern unit and the repeating sub-pattern units to determine first measurement data; a second determination submodule for setting measurement points at the same locations on corresponding target pattern units in the design layout to determine second measurement data; and a third determination submodule for determining difference information based on the first and second measurement data.

[0101] In some embodiments, the third determination submodule is used to determine difference information corresponding to each measurement type, based on the measurement type of the first measurement data and the measurement type of the second measurement data.

[0102] In some embodiments, the second determination module 530 includes a fourth determination submodule for determining the mean and standard deviation corresponding to the measurement type based on the first measurement data and the measurement type of the second measurement data corresponding to the difference information, and a fifth determination submodule for determining whether the repeating pattern unit or repeating subpattern unit is defective based on each of the first measurement data, the corresponding mean and standard deviation corresponding to the measurement type.

[0103] In some embodiments, the fifth determination submodule includes: a first determination unit for determining a measurement threshold corresponding to the measurement type based on the mean and standard deviation corresponding to the measurement type; a second determination unit for determining that if any of the first measurement data is greater than the measurement threshold of the measurement type, the repeating pattern unit or repeating subpattern unit in which any of the first measurement data is located is defective; and a third determination unit for determining the repeating pattern unit or repeating subpattern unit in which any of the first measurement data is located as an abnormal pattern unit and storing the abnormal pattern unit and any of the first measurement data in an abnormal feature library.

[0104] In some embodiments, the second decision module 530 is specifically used to compare the isolated subpattern unit with anomaly pattern units in the anomaly feature library to determine the degree of matching, and to determine whether the isolated subpattern unit is defective based on the degree of matching.

[0105] The wafer defect detection apparatus according to this application first determines repeating and non-repeating pattern units in an SEM image based on the SEM image and pattern units in the design layout to be detected, then measures the pattern units, repeating and non-repeating pattern units in the design layout to determine difference information, and then determines whether or not there are defects in the repeating and non-repeating pattern units based on the difference information. As a result, in the wafer defect detection process, the SEM image and pattern units in the design layout are measured to obtain difference information that can represent the SEM image, and then defect detection is performed on the SEM image based on the difference information. Since the characteristics of the SEM image and pattern units in the design layout are sufficiently considered in the defect detection process, the determined difference information becomes more comprehensive and reliable, improving the accuracy and reliability of subsequent wafer defect detection.

[0106] It should be understood that the specific features, operations, and details described herein with respect to the method of this application are applicable similarly to the apparatus and system of this application, and vice versa. Furthermore, each step of the method of this application described herein may be performed by the corresponding component or unit of the apparatus or system of this application.

[0107] Each module / unit of the apparatus of this application should be understood to be implemented in whole or in part by software, hardware, firmware, or a combination thereof. Each module / unit may be incorporated into the processor of the electronic device in the form of hardware or firmware, or may be stored in the memory of the electronic device in the form of software and invoked by the processor to perform operations on each module / unit. Each module / unit may be implemented as a separate component or separate module, or two or more modules / units may be implemented as a single component or module.

[0108] As shown in Figure 6, this application provides an electronic device 600 including a processor 601 and a memory 602 in which computer program instructions are stored. Here, the processor 601 executes the computer program instructions to implement each step of the method for detecting wafer defects described above. The electronic device 600 may be a server, a terminal, or any other electronic device having the necessary computing and / or processing functions in a broad sense.

[0109] In one embodiment, the electronic device 600 may include a processor, memory, network interface, communication interface, etc., connected via a system bus. The processor of the electronic device 600 may be used to provide necessary computing, processing, and / or control functions. The memory of the electronic device 600 may include a non-volatile storage medium and internal memory. The non-volatile storage medium may store an operating system, computer programs, etc. The internal memory may provide an environment for the execution of the operating system and computer programs on the non-volatile storage medium. The network interface and communication interface of the electronic device 600 are used to connect and communicate with external devices via a network. Once the computer program is executed by the processor, the steps of the method of this application are performed.

[0110] This application provides a computer-readable storage medium in which computer program instructions are stored, and a method for detecting the above-mentioned wafer defects is realized when the computer program instructions are executed by a processor.

[0111] Those skilled in the art will understand that the method steps of this application can be completed by a computer program instructing, for example, electronic device 600 or related hardware of a processor, the computer program may be stored in a non-temporary computer-readable storage medium, and when the computer program is executed, the steps of this application are performed. In some cases, any use of memory, storage or other media as herein may include non-volatile or volatile memory. Examples of non-volatile memory include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), flash memory, magnetic tape, flexible disk, magneto-optical data storage device, optical data storage device, hard disk, solid-state disk, etc. Examples of volatile memory include RAM (Random Access Memory) and external cache memory.

[0112] The technical features described above can be combined in any way. While not all possible combinations of these technical features are described, any combination of these technical features should be considered included herein if they do not conflict.

[0113] Finally, it should be noted that each of the embodiments described above is used for illustrative purposes only and not to limit this application; although this application is illustrated in detail with reference to each of the embodiments described above, those skilled in the art can still modify the technical solutions described in each of the embodiments described above, or substitute some or all of the technical features with equivalents, and such modifications or substitutions will not cause the essence of the corresponding technical solution to deviate from the scope of the technical solution of the embodiments of this application.

Claims

1. Based on the SEM image to be detected and the pattern units within the design layout, repeating and non-repeating pattern units within the SEM image are determined. The pattern units, repeating pattern units, and non-repeating pattern units within the design layout are measured to determine the difference information. The process includes determining whether the repeating pattern unit and the non-repeating pattern unit are defective based on the difference information. A method for detecting wafer defects.

2. Determining the repeating pattern units and non-repeating pattern units in the SEM image based on the SEM image and the pattern units in the design layout is: The SEM image is processed to obtain the pattern contour within the SEM image, This includes determining the repeating pattern units and the non-repeating pattern units in the SEM image by comparing the pattern contour with the pattern units in the design layout. A method for detecting wafer defects as described in claim 1.

3. Measuring the pattern units, repeating pattern units, and non-repeating pattern units within the design layout to determine difference information is: The non-repeating pattern unit is divided to obtain repeating sub-pattern units and isolated sub-pattern units, Setting measurement points in the repeating pattern unit and the repeating sub-pattern unit to determine the first measurement data, The second set of measurement data is determined by setting a measurement point at the same position on the corresponding target pattern unit within the design layout. This includes determining difference information based on the first measurement data and the second measurement data, A method for detecting wafer defects as described in claim 1.

4. Determining difference information based on the first measurement data and the second measurement data is: This includes determining difference information corresponding to each measurement type based on the measurement type of the first measurement data and the measurement type of the second measurement data. A method for detecting wafer defects according to claim 3.

5. Based on the difference information, determining whether or not there are defects in the repeating pattern unit and the non-repeating pattern unit is: Based on the measurement type of the first and second measurement data corresponding to the difference information, the mean and standard deviation corresponding to the measurement type are determined. The process includes determining whether the repeating pattern unit or the repeating sub-pattern unit is defective based on each of the first measurement data corresponding to the measurement type, the corresponding mean value and standard deviation, A method for detecting wafer defects according to claim 4.

6. Determining whether or not the repeating pattern unit or the repeating sub-pattern unit is defective based on each of the first measurement data corresponding to the measurement type, the corresponding mean value and standard deviation, is: Based on the mean and standard deviation corresponding to the measurement type, a measurement threshold corresponding to the measurement type is determined. If any of the first measurement data is greater than the measurement threshold for the measurement type, it is determined that there is a defect in the repeating pattern unit or the repeating sub-pattern unit where the first measurement data is located. The process includes determining the repeating pattern unit or the repeating sub-pattern unit in which any of the first measurement data described above is located as an abnormal pattern unit, and storing the abnormal pattern unit and any of the first measurement data described above in an abnormal feature library. A method for detecting wafer defects according to claim 5.

7. Based on the difference information, determining whether or not there are defects in the repeating pattern unit and the non-repeating pattern unit is: The degree of matching is determined by comparing the isolated subpattern unit with the abnormal pattern unit in the abnormal feature library. This includes determining whether or not the isolated subpattern unit is defective based on the degree of matching, A method for detecting wafer defects according to claim 3.

8. A first determination module for determining repeating and non-repeating pattern units in an SEM image based on the SEM image to be detected and the pattern units in the design layout, A measurement module for measuring pattern units, repeating pattern units, and non-repeating pattern units within the design layout and determining difference information, A second determination module for determining whether the repeating pattern unit and the non-repeating pattern unit are defective based on the difference information, A device for detecting wafer defects.

9. It includes a processor and memory in which computer program instructions are stored, When the processor executes the computer program instruction, the method for detecting wafer defects according to any one of claims 1 to 7 is realized. electronic equipment.

10. A computer-readable storage medium in which computer program instructions are stored, When the computer program instruction is executed by the processor, the method for detecting wafer defects according to any one of claims 1 to 7 is realized. A computer-readable storage medium.

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