Wafer defect detection method, apparatus, electron beam scanning device and storage medium

Abstract

To provide wafer defect inspection method and apparatus that improve the reliability of a defect detection result for each wafer as a detection target and prevent an erroneous defect detection result from being used in subsequent steps.SOLUTION: A method acquires a wafer image of a wafer as a detection target after starting scanning of an electron beam on a target defect detection area of the wafer as a detection target, calculates an image sharpness degree of the wafer image, acquires a sharpness evaluation value of the wafer image based on the image sharpness degree of the wafer image, when the sharpness evaluation value does not match a preset condition, describing that the quality of the acquired wafer image is poor, marks a defect detection result of the wafer as a detection target as an unreliable detection result, and distinguishes the marked defect detection result from a defect detection result of the wafer as a detection target whose wafer image quality is good. Then, the method stops defect detection of the wafer as a detection target, and timely stops a defect detection program of the wafer as a detection target, thereby avoiding meaningless execution steps.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present application relates to the field of semiconductor technology, and in particular to wafer defect detection methods, apparatus, electron beam scanning devices, and storage media. [Background technology]

[0002] With the development of the semiconductor industry, electron beam scanning devices are widely applied in the semiconductor field to detect wafer nano-scale physical defects and circuit on-off defects. The quality of the wafer image is directly related to the defect detection results, but due to the basic principle of the electron beam scanning device, it cannot achieve precise stability of the wafer image, making it difficult to ensure the quality of the wafer image.

[0003] At present, there are few image quality monitoring systems for electron beam scanning devices in the industry, and the detection of wafer physical defects and circuit on-off defects has poor image quality, resulting in erroneous defect detection results and low reliability of the defect detection results, leading to the use of erroneous defect detection results in subsequent processes. Although some electron beam scanning devices are equipped with image quality monitoring systems, they can obtain good wafer image quality in the defect detection process by acquiring a sample image before scanning and adjusting the lens, electron beam, etc. of the scanning device according to the acquired sample image, which does not guarantee that the actual image quality will not cause erroneous detection of defects, resulting in low reliability of the defect detection results. Summary of the Invention

[0004] In order to solve the above problems, the present application provides a wafer defect detection method, a wafer defect detection apparatus, an electron beam scanning device, and a computer-readable storage medium.

[0005] According to one aspect of an embodiment of the present application, a wafer defect detection method is disclosed, the wafer defect detection method comprising: A target defect detection area of ​​a wafer to be inspected is scanned with an electron beam to detect defects in the target defect detection area, The wafer to be inspected has one or more defect inspection areas; acquiring a wafer image of the wafer to be detected and calculating an image sharpness of the wafer image; acquiring a sharpness evaluation value of the wafer image based on the image sharpness of the wafer image; The method includes determining whether a sharpness evaluation value of the wafer image meets a predetermined condition, and if the sharpness evaluation value of the wafer image does not meet the predetermined condition, marking the defect detection result of the wafer to be detected as an unreliable detection result.

[0006] In some embodiments, obtaining a sharpness evaluation value of the wafer image based on the image sharpness of the wafer image includes calculating a sharpness difference value between the image sharpness of the wafer image and a predetermined standard sharpness of the wafer image, and obtaining the sharpness evaluation value of the wafer image, wherein the sharpness evaluation value of the wafer image not meeting the predetermined condition means that the sharpness evaluation value of the wafer image is equal to or greater than a first sharpness difference threshold.

[0007] In some embodiments, if the sharpness evaluation value of the wafer image does not meet a pre-set condition, defect detection for the target wafer is discontinued.

[0008] In some embodiments, after obtaining the sharpness evaluation value of the wafer image, the method further includes outputting the sharpness evaluation value of the wafer image to the statistical process control system such that if the sharpness evaluation value of the wafer image does not meet a preset condition, the statistical process control system marks a defect detection result of the wafer to be detected as an unreliable detection result.

[0009] In some embodiments, calculating the image sharpness of the wafer image comprises calculating an image sharpness of the wafer image using the relationship

[0010]

number

[0011] where P is the image sharpness of the wafer image, m and n are the length and width of the wafer image, respectively, df is the gradation change width of a pixel dot of the wafer image, dx is an increase in distance between pixel dots of the wafer image, i is a pixel dot of the wafer image, and a is a neighboring point of the pixel dot.

[0012] In some embodiments, the wafer image is an image of a wafer area that is not scanned by the electron beam, outside the target defect detection area on the wafer being detected and within less than a first preset distance from the target defect detection area.

[0013] In some embodiments, before performing electron beam scanning on a target defect detection area of ​​the wafer to be detected, the method further includes acquiring a brightness / contrast image of the wafer to be detected, acquiring a gradation distribution of the brightness / contrast image, acquiring a gradation distribution evaluation value of the brightness / contrast image based on the gradation distribution of the brightness / contrast image, and determining whether the gradation distribution evaluation value matches a preset condition, and if the gradation distribution evaluation value does not match the preset condition, aborting defect detection of the wafer to be detected.

[0014] In some embodiments, obtaining the gradation distribution of the brightness / contrast image includes obtaining a normal distribution of the number of pixel dots corresponding to each gradation in the brightness / contrast image, and calculating the number of pixel dots corresponding to each gradation within a predetermined number of sigmas in the normal distribution to obtain the gradation distribution of the brightness / contrast image; obtaining a gradation distribution evaluation value of the brightness / contrast image based on the gradation distribution of the brightness / contrast image includes judging the pass / fail of the gradation based on the number of pixel dots corresponding to the gradation within a predetermined number of sigmas in the normal distribution and the number of pixel dots corresponding to the same gradation in a predetermined standard gradation distribution, and calculating the pass rate of all gradations within the predetermined number of sigmas in the normal distribution as the gradation distribution evaluation value of the brightness / contrast image.

[0015] In some embodiments, the preset number of sigmas is between 1 and 2 sigmas.

[0016] In some embodiments, the gray level is judged to be acceptable if the ratio between the number of pixel dots corresponding to the gray levels within a predetermined number of sigmas in the normal distribution and the number of pixel dots corresponding to the same gray level in the standard gray level distribution is less than 5% from 100%; and / or The gradation distribution evaluation value does not meet the preset condition when the pass rate of all the gradations is 95% or less, and when the pass rate of all the gradations is greater than 95%, the gradation distribution evaluation value meets the preset condition.

[0017] In some embodiments, when the gradation distribution evaluation value matches a predetermined condition, the method includes acquiring an astigmatism image of the wafer to be detected and calculating an image sharpness of the astigmatism image; acquiring a sharpness evaluation value of the astigmatism image based on the image sharpness of the astigmatism image; and determining whether the sharpness evaluation value of the astigmatism image matches the predetermined condition, wherein if the sharpness evaluation value of the astigmatism image does not match the predetermined condition, canceling defect detection on the wafer to be detected; and if the sharpness evaluation value of the astigmatism image matches the predetermined condition, performing a step of performing electron beam scanning on a target defect detection area of ​​the wafer to be detected.

[0018] In some embodiments, obtaining a sharpness evaluation value of the astigmatism image based on the image sharpness of the astigmatism image includes calculating a sharpness difference value between the image sharpness of the astigmatism image and a predetermined standard sharpness of the astigmatism image to obtain a sharpness evaluation value of the astigmatism image, wherein the sharpness evaluation value of the astigmatism image not meeting the predetermined condition means that the sharpness evaluation value of the astigmatism image is equal to or greater than a second sharpness difference threshold, and the sharpness evaluation value of the astigmatism image meeting the predetermined condition means that the sharpness evaluation value of the astigmatism image is less than the second sharpness difference threshold.

[0019] In some embodiments, before performing electron beam scanning on a target defect detection area of ​​the wafer to be detected, the method further includes acquiring an astigmatism image of the wafer to be detected, calculating an image sharpness of the astigmatism image, acquiring a sharpness evaluation value of the astigmatism image based on the image sharpness of the astigmatism image, and determining whether the sharpness evaluation value of the astigmatism image matches a predetermined condition, and if the sharpness evaluation value of the astigmatism image does not match the predetermined condition, aborting defect detection of the wafer to be detected.

[0020] In some embodiments, before performing electron beam scanning on a target defect detection area of ​​the wafer to be detected, the method further includes acquiring a focused image of the wafer to be detected, calculating an image sharpness of the focused image, acquiring a sharpness evaluation value of the focused image based on the image sharpness of the focused image, and determining whether the sharpness evaluation value of the focused image matches a predetermined condition, and if the sharpness evaluation value of the focused image does not match the predetermined condition, aborting defect detection of the wafer to be detected.

[0021] In some embodiments, obtaining a sharpness evaluation value of the focused image based on the image sharpness of the focused image involves calculating a sharpness difference value between the image sharpness of the focused image and a predetermined standard sharpness of the focused image, and obtaining the sharpness evaluation value of the focused image, and the sharpness evaluation value of the focused image not meeting the predetermined condition means that the sharpness evaluation value of the focused image is equal to or greater than a third sharpness difference threshold.

[0022] In some embodiments, when the sharpness evaluation value of the focused image matches a preset condition, the method includes acquiring a brightness / contrast image of a wafer to be detected, acquiring a gradation distribution of the brightness / contrast image, obtaining a gradation distribution evaluation value of the brightness / contrast image based on the gradation distribution of the brightness / contrast image, determining whether the gradation distribution evaluation value matches a preset condition, and if the gradation distribution evaluation value does not match the preset condition, stopping defect detection of the wafer to be detected, and if the gradation distribution evaluation value matches the preset condition, stopping defect detection of the wafer to be detected. acquiring an astigmatism image of the wafer and calculating an image sharpness of the astigmatism image; acquiring a sharpness evaluation value of the astigmatism image based on the image sharpness of the astigmatism image; determining whether the sharpness evaluation value of the astigmatism image matches a preset condition; if the sharpness evaluation value of the astigmatism image does not match the preset condition, canceling defect detection on the wafer to be detected; and if the sharpness evaluation value of the astigmatism image matches the preset condition, executing a step of performing electron beam scanning on a target defect detection area of ​​the wafer to be detected.

[0023] According to one aspect of an embodiment of the present application, a wafer defect detection apparatus is disclosed, the wafer defect detection apparatus comprising: a detection target wafer scanning module, an image sharpness calculation module, a sharpness evaluation value calculation module, a sharpness evaluation value judgment module, and a detection result mark module, wherein the detection target wafer scanning module is used to perform electron beam scanning on a target defect detection area of ​​the detection target wafer to detect defects in the target defect detection area, wherein the detection target wafer has one or more defect detection areas, and the image sharpness calculation module is used to perform electron beam scanning on the ... and calculating the image sharpness of the wafer image, the sharpness evaluation value calculation module is used to acquire a sharpness evaluation value of the wafer image based on the image sharpness of the wafer image, the sharpness evaluation value judgment module is used to judge whether the sharpness evaluation value of the wafer image matches a preset condition, and the detection result marking module is used to mark the defect detection result of the wafer to be detected as an unreliable detection result if the sharpness evaluation value of the wafer image does not match the preset condition.

[0024] According to one aspect of an embodiment of the present application, an electron beam scanning device is disclosed, the electron beam scanning device including one or more processors and a memory, the memory for storing one or more computer programs that, when executed by the one or more processors, cause the processor to realize the above-mentioned wafer defect detection method.

[0025] According to one aspect of an embodiment of the present application, a computer-readable storage medium is disclosed, the computer-readable storage medium storing computer-readable instructions that, when executed by a processor of a computer, cause the computer to perform the above-mentioned wafer defect detection method.

[0026] The technical solutions provided by the embodiments of the present application include at least the following beneficial effects:

[0027] The technical solution disclosed in the present application begins electron beam scanning of a target defect detection area of ​​a wafer to be detected, then acquires a wafer image of the wafer to be detected, calculates the image sharpness of the wafer image, and acquires a sharpness evaluation value of the wafer image based on the image sharpness of the wafer image. If the sharpness evaluation value does not meet a preset condition, it describes that the quality of the acquired wafer image is poor, and marks the defect detection result of the wafer to be detected as an unreliable detection result, and distinguishes between the defect detection results of the wafer to be detected that have good quality of the wafer image, thereby improving the reliability of the defect detection results of each wafer to be detected, and avoiding the use of erroneous defect detection results in subsequent processes.

[0028] It should be noted that the foregoing general description and the following detailed description are merely exemplary and are not intended to be limiting of the present application. [Brief description of the drawings]

[0029] The drawings herein are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application, and together with the specification serve to explain the principles of the present application. [Figure 1] 5A and 5B are schematic diagrams illustrating detection results corresponding to poor image quality and good image quality, respectively, according to an embodiment. [Diagram 2] 1 shows a flowchart of a wafer defect inspection method according to an embodiment of the present application. [Diagram 3] 1 shows a flowchart of brightness / contrast image quality detection steps according to an embodiment of the present application; [Figure 4] 1 shows a schematic diagram of a gradation distribution obtained by an embodiment of the present application and a standard gradation distribution. [Diagram 5] 1 shows a flowchart of the steps of detecting the quality of an astigmatism image according to an embodiment of the present application. [Figure 6]1 shows a flow chart of the in-focus image quality detection steps according to an embodiment of the present application; [Figure 7] 1 shows an overall flowchart of wafer defect detection according to one embodiment of the present application. [Figure 8] 1 shows a configuration block diagram of a wafer defect inspection device according to an embodiment of the present application; [Figure 9] 1 shows a block diagram of an electron beam scanning device according to an embodiment of the present application; [Figure 10] FIG. 1 shows a block diagram of a computer system for implementing some embodiments of the present application. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0030] Hereinafter, exemplary embodiments will be described in more detail with reference to the drawings. However, the exemplary embodiments may be implemented in various forms and are not limited to the examples set forth herein. On the contrary, these exemplary embodiments are provided to make the description of the present application more complete and complete, and to comprehensively convey the concept of the exemplary embodiments to those skilled in the art.

[0031] Herein, the terms "first", "second", and "third" are for descriptive purposes only and cannot be understood as indicating or implying the relative importance or number of the indicated technical features. Thus, a feature defined as "first", "second", or "third" may explicitly or implicitly include one or more features.

[0032] Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to provide a thorough understanding of the embodiments of the present application. However, one skilled in the art will recognize that the technical means of the present application can actually be implemented without one or more of the specific details, or can employ other methods, components, devices, steps, etc. In other instances, well-known methods, devices, implementations, or operations are not shown or described in detail to avoid obscuring aspects of the present application.

[0033] The flowcharts shown in the drawings are merely illustrative and do not necessarily include all contents and operations / steps, and do not necessarily have to be performed in the order described. For example, some operations / steps may be separated, some operations / steps may be integrated or partially integrated, and the order of actual implementation may vary according to actual circumstances.

[0034] EBI (Electron-Beam Inspection) is a device that uses the information excited when high-energy electrons interact with the material on the wafer surface to form an image, and then detects electrical and physical defects on the wafer through image processing and calculation, making it an important device for improving yield in the chip manufacturing process. The quality of the formed image is directly related to the defect detection results, and poor image quality will reduce the reliability of the defect detection results.

[0035] Some traditional EBIs do not monitor image quality while scanning the wafer with the electron beam. Generally, the recipe has a probability of less than 1% where image quality drift occurs, mainly due to failure in image focus, brightness / contrast, astigmatism capture, as well as sudden death of the hardware of the device itself, which causes the whole image to suddenly drift. The impact is that defects are not detected during the detection process, and currently there is no alarm mechanism, leading to defect detection departments being unable to guarantee the reliability of defect detection results.

[0036] Some conventional EBIs are equipped with an image quality monitoring system, which acquires an image of a microchip previously embedded in the wafer to be detected, i.e., a sample image, by the EBI machine before performing electron beam scanning on the wafer to be detected, and adjusts the lens, electron beam, etc. of the scanning device based on the acquired sample image to acquire better wafer image quality in the defect detection process. However, this better wafer image quality does not guarantee sufficient quality to prevent false detection of defects, and the sample image quality may not accurately represent the image quality of the actual wafer to be detected. In some cases, for example, when the thickness of the wafer to be detected and the thickness of the sample are different, the sample image quality may be good but the actual image quality of the wafer to be detected may be poor. In this case as well, the reliability of the defect detection results will be low, and erroneous detection results will be used in subsequent processes.

[0037] For example, if a defect actually exists in the wafer being detected, but the image quality of the wafer obtained during the defect detection process is poor, the defect is not detected, and the defect detection result of the wafer being detected is 0 defects, as shown in FIG. 1(a); on the other hand, if the image quality of the wafer obtained during the defect detection process is good, the defect detection result of the wafer being detected is that there are defects in multiple crystal grains, marked with x's, as shown in FIG. 1(b).

[0038] As the CD (Critical Dimension) of semiconductor devices is shrinking and the requirements for detection results in the industry are becoming increasingly strict, the reliability of defect detection results is becoming increasingly important. Therefore, the present application provides a wafer defect detection method, which starts scanning of a target defect detection area of ​​a wafer to be detected with an electron beam, acquires a wafer image of the wafer to be detected, analyzes the wafer image, judges the quality of the wafer image, and if it is judged that the quality of the wafer image is poor, marks the defect detection result of the wafer to be detected as an unreliable detection result, and distinguishes the defect detection result of the wafer to be detected whose wafer image quality is good, thereby improving the reliability of the defect detection result of each wafer to be detected, thereby avoiding the use of erroneous defect detection results in subsequent processes.

[0039] Hereinafter, the wafer defect detection method according to the present application will be described in detail with reference to specific embodiments.

[0040] FIG. 2 shows a flowchart of a wafer defect detection method according to one embodiment of the present application. As shown in FIG. 2, the wafer defect detection method includes at least a wafer defect detection step, an image acquisition and sharpness calculation step, a sharpness evaluation value acquisition step, an image quality judgment step, a detection result marking step, etc., which correspond to the following steps S110 to S150, respectively, and will be introduced in detail as follows.

[0041] In step S110, a target defect detection area on the wafer to be inspected is scanned with an electron beam to detect defects in the target defect detection area.

[0042] Here, the wafer to be detected has one or more defect detection areas. When the wafer to be detected has only one defect detection area, the target defect detection area is the defect detection area, and when the wafer to be detected has multiple defect detection areas, the target defect detection area may be one of the multiple defect detection areas, or may be two or more of the multiple defect detection areas. Exemplarily, when the wafer to be detected has multiple defect detection areas, the multiple defect detection areas are located in the upper left corner area, the upper right corner area, the lower left corner area, and the lower right corner area of ​​the wafer to be detected, respectively, and in one embodiment, the target defect detection area includes the upper left corner area and the upper right corner area, and in another embodiment, the target defect detection area includes the lower left corner area and the lower right corner area.

[0043] As can be understood, the target defect detection area is a defect detection area where electron beam scanning is required to detect defects. For a wafer to be detected having a plurality of defect detection areas, electron beam scanning can be performed intermittently on the plurality of defect detection areas. For example, first, electron beam scanning can be performed on the upper left corner area and the upper right corner area as the target defect detection area, and after scanning the upper left corner area and the upper right corner area, electron beam scanning can be performed on the lower left corner area and the lower right corner area as the target defect detection area. In this case, other steps, for example, steps S120 to S140 below, can be inserted between two electron beam scans. Of course, for a wafer to be detected having a plurality of defect detection areas, electron beam scanning can be performed on a plurality of defect detection areas at once, that is, other steps are not allowed to be inserted before electron beam scanning on all defect detection areas of the wafer to be detected is completed.

[0044] In one embodiment, detecting defects in the target defect detection area is performed by performing an electron beam scan on the target defect detection area of ​​the wafer to be detected, performing a two-tone subtraction on every two of three adjacent crystal grains inside the wafer in the scanned image obtained by scanning the target defect detection area of ​​the wafer to be detected, and by comparing the crystal grains two by two, finding a crystal grain among the three crystal grains that is different from the other two crystal grains and regarding it as a crystal grain having a defect. This method provides a high accuracy of the defect detection result.

[0045] In step S120, a wafer image of the wafer to be detected is acquired, and the image sharpness of the wafer image is calculated.

[0046] In one embodiment, after completing the electron beam scan of the target defect detection area of ​​the target wafer, the target wafer is scanned by the electron beam to obtain a wafer image. After completing the scanning of the target defect detection area, further obtaining a wafer image is easy and technically difficult. Optionally, in another embodiment, a real-time wafer image may be obtained during the process of scanning the target defect detection area of ​​the target wafer with the electron beam.

[0047] Here, the wafer image may be a local area image of the wafer to be detected, not an image covering the entire area of ​​the wafer to be detected. In one embodiment, the acquired wafer image is an image of a wafer area that is not scanned by the electron beam, which is outside the target defect detection area on the wafer to be detected and within a range of less than a first preset distance from the target defect detection area. Since traces are left on the wafer area scanned by the electron beam, which affects the image quality, by acquiring an image of a wafer area that is not scanned by the electron beam and is close to the target defect detection area, the image quality of the acquired wafer image can represent the actual image quality of the target defect detection in the scanning process, and the processing results of the subsequent steps can be more accurate.

[0048] Here, the first preset distance is a distance value that is sufficiently close to the preset target defect detection area, and the wafer image is an area image adjacent to the target defect detection area, thereby avoiding the obtained wafer image from being unable to accurately represent the image quality of the target defect detection area during the scanning process due to minute errors between different areas of the wafer to be detected.

[0049] In one embodiment, the relationship

[0050]

number

[0051] where P is the image sharpness of the wafer image, m and n are the length and width of the wafer image, respectively, df is the gradation change width of the pixel dot of the wafer image, dx is the increase in the distance between the pixel dots of the wafer image, i is a pixel dot of the wafer image, and a is a neighboring point of the pixel dot. That is, for each pixel dot in the wafer image, eight neighboring points are taken one by one and subtracted from the corresponding gray scale. The weighted sum of the eight gray scale difference values ​​df obtained by subtracting the corresponding gray scale values ​​from the eight neighboring points is calculated, where the magnitude of the weight depends on the distance dx between the neighboring point and the pixel dot. If the distance between the neighboring point and the pixel dot is short, the weight is large, and if the distance between the neighboring point and the pixel dot is far, the weight is small. For example, the weight of the gray scale difference value in the 45° and 135° directions needs to be multiplied by 1 / √2 to the weight of the gray scale difference value in the 0° and 90° directions. After adding up the values ​​obtained for all the pixel dots, the total number of pixel dots in the wafer image is calculated.

[0052]

number

[0053] Divide by this to obtain the image sharpness P of the wafer image. This relational expression can be regarded as a statistic of the degree of gradation diffusion around each pixel dot of the wafer image, that is, the greater the degree of diffusion, the clearer the image.

[0054] In this embodiment, by reflecting the gradation difference values ​​of the 8 neighboring points of the wafer image and the gradation distribution state of the image, it is possible to obtain an accurate calculation result of the image sharpness without being affected by parameter fluctuations due to factors such as noise. Of course, in other embodiments, the image sharpness of the wafer image may be calculated by other methods.

[0055] In step S130, a sharpness evaluation value of the wafer image is obtained based on the image sharpness of the wafer image.

[0056] Here, the sharpness evaluation value can be used to evaluate the quality of a wafer image, and refers to a parameter related to the image sharpness of the wafer image.

[0057] In one embodiment, a sharpness evaluation value of the wafer image is obtained based on the image sharpness of the wafer image, i.e., a sharpness difference value between the image sharpness of the wafer image and a preset standard sharpness of the wafer image is calculated, and the sharpness evaluation value of the wafer image is obtained, i.e., the sharpness difference value between the image sharpness of the wafer image and the preset standard sharpness of the wafer image is used as the sharpness evaluation value of the wafer image. The method of calculating the sharpness evaluation value of the wafer image is simple, and the image quality of the wafer image can be accurately evaluated.

[0058] In one embodiment, a sharpness evaluation value of the wafer image is obtained based on the image sharpness of the wafer image, i.e., the image sharpness of the wafer image is the sharpness evaluation value of the wafer image. If the sharpness evaluation value of the wafer image is equal to or greater than the sum of a preset standard sharpness of the wafer image and a first sharpness difference value, the sharpness evaluation value of the wafer image does not meet the preset condition.

[0059] Of course, the present application is not limited to using the sharpness evaluation value of the wafer image as the sharpness difference value between the image sharpness of the wafer image and a predetermined standard sharpness of the wafer image or the image sharpness of the wafer image, and in other embodiments, the sharpness evaluation value of the wafer image may be determined by any method.

[0060] In step S140, it is determined whether the sharpness evaluation value of the wafer image matches a preset condition, and if the sharpness evaluation value of the wafer image does not match the preset condition, the process proceeds to step S150.

[0061] Here, in an embodiment in which the sharpness evaluation value of the wafer image is the sharpness difference value between the image sharpness of the wafer image and a preset standard sharpness of the wafer image, if the sharpness evaluation value of the wafer image is equal to or greater than the first sharpness difference threshold, that is, if the sharpness evaluation value of the wafer image does not match the preset condition, proceed to step S150, and if the sharpness evaluation value of the wafer image is smaller than the first sharpness difference threshold, the sharpness evaluation value of the wafer image matches the preset condition.

[0062] In an embodiment in which the image sharpness of a wafer image is used as the sharpness evaluation value of the wafer image, if the sharpness evaluation value of the wafer image is equal to or greater than the sum of a preset standard sharpness of the wafer image and the first sharpness difference threshold, i.e., if the sharpness evaluation value of the wafer image does not match the preset condition, proceed to step S150, and if the sharpness evaluation value of the wafer image is smaller than the sum of the preset standard sharpness of the wafer image and the first sharpness difference threshold, the sharpness evaluation value of the wafer image matches the preset condition.

[0063] In step S150, the defect detection results for the wafer being inspected are marked as unreliable detection results.

[0064] If the sharpness evaluation value of the wafer image does not meet the preset condition, i.e., the image quality of the wafer is determined to be poor, the defect detection result of the wafer to be detected is marked as an unreliable detection result, and the defect detection results of the wafer to be detected having good image quality can be distinguished, so that the defect detection department can know whether the defect detection results of each wafer to be detected are reliable or not, which can improve the reliability of the defect detection results of each wafer to be detected, and avoid using erroneous defect detection results in subsequent processes.

[0065] Optionally, in some embodiments, if it is determined in step S140 that the sharpness evaluation value of the wafer image meets a preset condition, i.e., if the image quality of the wafer is good, a step of marking the defect detection result of the detected wafer as a reliable detection result may be further performed, i.e., in these embodiments, each of the defect detection results corresponding to the detected wafers having poor wafer image quality and excellent wafer image quality is marked, and it is distinguished whether the defect detection result of each detected wafer is reliable or not.

[0066] Here, marking the defect detection result of the wafer to be detected as an unreliable detection result may involve directly marking the wafer to be detected. In this case, the wafer to be detected may be marked by marking the wafer ID of the wafer to be detected, or the wafer to be detected may be indirectly marked by marking the wafer number in the corresponding wafer lot of the wafer to be detected, i.e., the number of the wafer in a certain wafer lot. In this case, there is no need to obtain the wafer ID of the wafer to be detected, and the program is simpler.

[0067] In one embodiment, if the image quality judgment step determines that the sharpness evaluation value of the wafer image does not match a predetermined condition, a defect detection abort step is further executed, which includes aborting defect detection of the wafer being detected.

[0068] When the wafer to be detected has multiple defect detection areas and the target defect detection area does not include all of the defect detection areas of the wafer to be detected, after the image quality judgment step, some defect detection areas may be detected. If the wafer to be detected has a defect detection area to be detected, the defect detection of the wafer to be detected is stopped, and the defect detection program of the wafer to be detected for poor wafer image quality is stopped in a timely manner, so as to avoid meaningless execution steps and improve the effective utilization rate of EBI.

[0069] Stopping the defect detection of the wafer being detected may involve outputting a control command to stop the defect detection program for the wafer being detected, and causing the machine to stop the defect detection of the wafer being detected based on the control command. In this embodiment, if the image quality judgment step determines that the sharpness evaluation value of the wafer image does not match the preset condition, the defect detection stopping step is directly executed, which is highly efficient.

[0070] After the image quality judgment step, there is a possibility that the defect detection area to be detected does not exist on the wafer to be detected, and in some embodiments, if the image quality judgment step determines that the sharpness evaluation value of the wafer image does not match a preset condition, a detection target confirmation step may be executed first, i.e., it is determined whether the defect detection area to be detected exists on the wafer to be detected, and if the defect detection area to be detected exists on the wafer to be detected, a defect detection abort step is further executed to abort the defect detection on the wafer to be detected.

[0071] In one embodiment, the image quality judgment step and the detection result marking step are executed by an SPC (Statistical Process Control) system, and after the sharpness evaluation value acquisition step, a sharpness evaluation value output step is further executed to output the sharpness evaluation value of the wafer image to the SPC system. Then, the SPC system executes the image quality judgment step of judging whether or not the sharpness evaluation value of the wafer image matches a preset condition, and executes the detection result marking step of marking the defect detection result of the wafer to be detected as an unreliable detection result when it is determined that the sharpness evaluation value of the wafer image does not match the preset condition.

[0072] In an embodiment in which the wafer defect detection method includes a defect detection aborting step, the SPC system further executes the defect detection aborting step, i.e., further executes a step of aborting defect detection on the wafer being detected when the sharpness evaluation value of the wafer image does not meet a preset condition.

[0073] As described above, the present application obtains a wafer image of the wafer to be detected after starting the electron beam scan on the target defect detection area of ​​the wafer to be detected, calculates the image sharpness of the wafer image, obtains a sharpness evaluation value of the wafer image based on the image sharpness of the wafer image, and if the sharpness evaluation value does not meet the preset condition, it explains that the image quality of the obtained wafer is poor, and marks the defect detection result of the wafer to be detected as an unreliable detection result, distinguishes the defect detection result of the wafer to be detected that has good wafer image quality, improves the reliability of the defect detection result of each wafer to be detected, and avoids the use of the erroneous defect detection result in the subsequent process. In addition, if the sharpness evaluation value does not meet the preset condition, it stops the defect detection of the wafer to be detected, and stops the defect detection program of the wafer to be detected that has poor image quality of the wafer in a timely manner, thereby avoiding meaningless detection and improving the effective utilization rate of EBI.

[0074] In some embodiments, before performing the wafer defect detection step, a brightness / contrast image quality detection step is first performed. As shown in FIG. 3, the brightness / contrast image quality detection step includes a brightness / contrast image acquisition and gradation distribution calculation step, a gradation distribution evaluation value acquisition step, and a brightness / contrast image quality judgment step, which correspond to the following steps S210 to S230, respectively, and will be introduced in detail as follows:

[0075] In step S210, a brightness / contrast image of the wafer to be detected is obtained, and the gradation distribution of the brightness / contrast image is obtained.

[0076] In one embodiment, acquiring a brightness / contrast image of the wafer to be detected includes scanning a wafer area of ​​a non-defect detection area other than a target defect detection area on the wafer to be detected and within a range of less than a second preset distance from the target defect detection area with an electron beam, and acquiring a brightness / contrast image of the wafer area.

[0077] The second predetermined distance is a distance value sufficiently close to the predetermined target defect detection area, and the brightness / contrast image is an area image adjacent to the target defect detection area, thereby avoiding the obtained brightness / contrast image from being unable to accurately represent the image quality of the target defect detection area due to minute errors between different areas of the wafer to be detected.

[0078] In one embodiment, obtaining the grayscale distribution of the brightness / contrast image includes obtaining a normal distribution of the number of pixel dots corresponding to each grayscale in the brightness / contrast image, and calculating the number of pixel dots corresponding to each grayscale within a preset number of sigmas in the normal distribution to obtain the grayscale distribution of the brightness / contrast image. In statistical theory, a large number of samples will produce a normal distribution, and this embodiment uses statistical theory to calculate the grayscale distribution of the brightness / contrast image, so as to accurately obtain the grayscale distribution of the brightness / contrast image.

[0079] In step S220, a gradation distribution evaluation value of the brightness / contrast image is obtained based on the gradation distribution of the brightness / contrast image.

[0080] Here, the gradation distribution evaluation value can be used to evaluate the quality of a brightness / contrast image, and is a parameter related to the gradation distribution of the brightness / contrast image.

[0081] In one embodiment, obtaining the grayscale distribution of the brightness / contrast image includes obtaining a normal distribution of the number of pixel dots corresponding to each grayscale in the brightness / contrast image, and calculating the number of pixel dots corresponding to each grayscale within a preset number of σ (Sigma) in the normal distribution to obtain the grayscale distribution of the brightness / contrast image. Obtaining the grayscale distribution evaluation value of the brightness / contrast image based on the grayscale distribution of the brightness / contrast image includes judging whether the grayscale is acceptable based on the number of pixel dots corresponding to the grayscale within a preset number of σ in the normal distribution and the number of pixel dots corresponding to the same grayscale in a preset standard grayscale distribution, and calculating the acceptance rate of all grayscales within the preset number of σ in the normal distribution as the grayscale distribution evaluation value of the brightness / contrast image. The grayscale distribution evaluation value obtained in this manner is useful for accurately judging the image quality of the brightness / contrast image in a later step.

[0082] In detail, judging whether a gradation is acceptable based on the number of pixel dots corresponding to the gradation within a predetermined number of σ in the normal distribution and the number of pixel dots corresponding to the same gradation in the predetermined standard gradation distribution includes: calculating the ratio value between the number of pixel dots corresponding to the gradation within a predetermined number of σ in the normal distribution and the number of pixel dots corresponding to the same gradation in the predetermined standard gradation distribution; obtaining a difference value between the obtained ratio value and 100%; comparing the obtained difference value with a predetermined threshold value; if the obtained difference value is smaller than the predetermined threshold value, judging the gradation to be acceptable; if the obtained difference value is equal to or larger than the predetermined threshold value, judging the gradation to be unacceptable. By comparing the actually obtained gradation distribution situation with the standard gradation distribution, it is possible to accurately judge whether each gradation is acceptable.

[0083] For example, the preset threshold is 5%, i.e., if the difference between the ratio of the number of pixel dots corresponding to the gradation within a preset number of σ in the normal distribution to the number of pixel dots corresponding to the same gradation in the preset standard gradation distribution and 100% is less than 5%, the gradation is determined to be pass; if the difference between the ratio of the number of pixel dots corresponding to the gradation within a preset number of σ in the normal distribution to the number of pixel dots corresponding to the same gradation in the preset standard gradation distribution and 100% is 5% or more, the gradation is determined to be fail.

[0084] In one embodiment, the preset number of σ is 1 to 2 σ. 1 to 2 σ already has a sufficiently large number of samples, and can obtain a relatively accurate gradation distribution evaluation value, reduce unnecessary calculations, improve the calculation efficiency of the gradation distribution evaluation value, and thereby improve the detection efficiency of the image quality. In detail, the preset number of σ is, for example, 1 σ, 1.5 σ, 2 σ, etc. Of course, the preset number of σ may be 2 or more σ.

[0085] 4(a) shows a schematic diagram of the gradation distribution of the brightness / contrast image obtained in step S210, and FIG. 4(b) shows a schematic diagram of the standard gradation distribution, and the gradations within the preset number of σ are, for example, 110 gradations to 170 gradations. In step S220, the difference value between the ratio value of the number of pixel dots corresponding to FIG. 4(a) of 110 gradations and the number of pixel dots corresponding to FIG. 4(b) of 110 gradations and 100% is calculated, and if the difference value is less than 5%, the 110 gradations are judged to be pass, otherwise, the 110 gradations are judged to be fail, and the same applies to other gradations. After judging whether all gradations are pass, the total number of pass gradations among the 110 gradations to 170 gradations is divided by the total number of gradations from 110 gradations to 170 gradations, that is, the pass rate of all gradations within the preset number of σ, that is, the gradation distribution evaluation value of the brightness / contrast image can be obtained.

[0086] Note that using the pass rate of all gradations within a preset number of σ in the normal distribution as the gradation distribution evaluation value of the brightness / contrast image is only one embodiment of the present application, and in other embodiments, the gradation distribution evaluation value may be calculated using other methods.

[0087] In step S230, it is determined whether the gradation distribution evaluation value of the brightness / contrast image matches a preset condition, and if the gradation distribution evaluation value of the brightness / contrast image does not match the preset condition, the process proceeds to a defect detection cancellation step, i.e., step S240.

[0088] In one embodiment, determining whether the gradation distribution evaluation value of the brightness / contrast image meets a predetermined condition includes determining whether the gradation distribution evaluation value of the brightness / contrast image is greater than a predetermined threshold, and whether the gradation distribution evaluation value of the brightness / contrast image is greater than the predetermined threshold and the gradation distribution evaluation value meets the predetermined condition, or whether the gradation distribution evaluation value of the brightness / contrast image is less than or equal to the predetermined threshold and the gradation distribution evaluation value does not meet the predetermined condition.

[0089] For example, the preset threshold is 95%, i.e., when the pass rate of all gradations within the preset number of σ is greater than 95%, the gradation distribution evaluation value meets the preset condition, and the image quality of the brightness / contrast image is judged to be good; when the pass rate of all gradations within the preset number of σ is less than 95%, the gradation distribution evaluation value does not meet the preset condition, and the image quality of the brightness / contrast image is judged to be poor, and proceed to step S240.

[0090] In step S240, the defect detection for the target wafer is stopped.

[0091] If it is determined that the image quality of the brightness / contrast image is poor, the defect detection abort step is directly performed, and the defect detection program for the subsequent wafers to be detected is stopped, thereby avoiding meaningless execution steps and improving the effective utilization rate of the EBI.

[0092] In one embodiment, in step S230, it is determined that the gradation distribution evaluation value of the brightness / contrast image meets the preset condition, and then an astigmatism image quality detection step is executed. As shown in FIG. 5, the astigmatism image quality detection step includes an astigmatism image acquisition and sharpness calculation step, a sharpness evaluation value acquisition step, and an astigmatism image quality judgment step, which correspond to the following steps S310 to S330, respectively, and will be introduced in detail as follows.

[0093] In step S310, an astigmatism image of the wafer to be detected is acquired, and the image sharpness of the astigmatism image is calculated.

[0094] In one embodiment, acquiring an astigmatism image of the wafer to be detected involves scanning a wafer area of ​​a non-defect detection area other than a target defect detection area on the wafer to be detected and within a range of less than a third preset distance from the target defect detection area with an electron beam, and acquiring an astigmatism image of the wafer area.

[0095] The third preset distance is a distance value that is sufficiently close to the preset target defect detection area, and the astigmatism image is an area image adjacent to the target defect detection area, thereby avoiding the obtained astigmatism image from being unable to accurately represent the image quality of the target defect detection area due to minute errors between different areas of the wafer to be detected.

[0096] In one embodiment, the relationship

[0097]

number

[0098] where P is the image sharpness of the astigmatism image, m and n are the length and width of the astigmatism image respectively, df is the gradation change width of the pixel dot of the astigmatism image, dx is the increase in the distance between the pixel dots of the astigmatism image, i is a pixel dot of the astigmatism image, and a is a neighboring point of the pixel dot. That is, for each pixel dot in the astigmatism image, take eight neighboring points one by one and subtract the corresponding grayscale from each of them, and obtain a weighted sum of the eight grayscale difference values ​​df obtained by first subtracting the corresponding grayscale from each of the eight neighboring points, where the magnitude of the weight depends on the distance dx between the neighboring point and the pixel dot. If the distance between the neighboring point and the pixel dot is short, the weight is large, and if the distance between the neighboring point and the pixel dot is far, the weight is small. For example, the weight of the grayscale difference value in the 45° and 135° directions needs to be multiplied by 1 / √2 to the weight of the grayscale difference value in the 0° and 90° directions. After adding up the values ​​obtained for all the pixel dots, the total number of pixel dots in the astigmatism image is calculated.

[0099]

number

[0100] and divide by to obtain the image sharpness P of the astigmatic image. This relational expression is a statistic of the degree of gradation diffusion around each pixel dot of the astigmatic image, that is, the greater the degree of diffusion, the clearer the image can be considered to be.

[0101] In this embodiment, by reflecting the gradation difference values ​​of 8 neighboring points of the astigmatism image and the gradation distribution state of the image, it is possible to obtain an accurate calculation result of the image sharpness without being affected by parameter fluctuations due to factors such as noise. Of course, in other embodiments, the image sharpness of the astigmatism image may be calculated by other methods.

[0102] In step S320, a sharpness evaluation value of the astigmatism image is obtained based on the image sharpness of the astigmatism image.

[0103] In one embodiment, a sharpness evaluation value of the astigmatism image is obtained based on the image sharpness of the astigmatism image, i.e., a sharpness difference value between the image sharpness of the astigmatism image and a preset standard sharpness of the astigmatism image is calculated to obtain the sharpness evaluation value of the astigmatism image, i.e., the sharpness difference value between the image sharpness of the astigmatism image and the preset standard sharpness of the astigmatism image is used as the sharpness evaluation value of the astigmatism image. The calculation method of the sharpness evaluation value of the astigmatism image is simple, and the image quality of the astigmatism image can be accurately evaluated.

[0104] In one embodiment, a sharpness evaluation value of the astigmatism image is obtained based on the image sharpness of the astigmatism image, that is, the image sharpness of the astigmatism image is the sharpness evaluation value of the astigmatism image. If the sharpness evaluation value of the astigmatism image is equal to or greater than the sum of a preset standard sharpness of the astigmatism image and a second sharpness difference value, the sharpness evaluation value of the astigmatism image does not meet the preset condition.

[0105] Of course, the present application is not limited to using the sharpness evaluation value of the astigmatism image as the sharpness difference value between the image sharpness of the astigmatism image and a predetermined standard sharpness of the astigmatism image or the image sharpness of the astigmatism image, and in other embodiments, the sharpness evaluation value of the astigmatism image may be determined in any manner.

[0106] In step S330, it is determined whether the sharpness evaluation value of the astigmatism image meets the preset conditions. If the sharpness evaluation value of the astigmatism image does not meet the preset conditions, a defect detection abort step, i.e., step S340, is executed. If the sharpness evaluation value of the astigmatism image meets the preset conditions, a step of scanning the target defect detection area of ​​the wafer to be detected with an electron beam is further executed.

[0107] Here, in an embodiment in which the sharpness evaluation value of the astigmatic image is the sharpness difference value between the image sharpness of the astigmatic image and a predetermined standard sharpness of the astigmatic image, if the sharpness evaluation value of the astigmatic image is equal to or greater than the second sharpness difference threshold, i.e., if the sharpness evaluation value of the astigmatic image does not match the predetermined condition, proceed to step S340, and if the sharpness evaluation value of the astigmatic image is smaller than the second sharpness difference threshold, the sharpness evaluation value of the astigmatic image matches the predetermined condition.

[0108] In an embodiment in which the image sharpness of the astigmatic image is used as the sharpness evaluation value of the astigmatic image, if the sharpness evaluation value of the astigmatic image is equal to or greater than the sum of the predetermined standard sharpness of the astigmatic image and the second sharpness difference threshold, i.e., if the sharpness evaluation value of the astigmatic image does not meet the predetermined condition, proceed to step S340, and if the sharpness evaluation value of the astigmatic image is smaller than the sum of the predetermined standard sharpness of the astigmatic image and the second sharpness difference threshold, the sharpness evaluation value of the astigmatic image meets the predetermined condition.

[0109] In step S340, defect detection for the target wafer is stopped.

[0110] If it is determined that the image quality of the astigmatism image is poor, the defect detection abort step is directly entered, and the defect detection program for the wafer to be subsequently detected is stopped, thereby avoiding meaningless execution steps and improving the effective utilization rate of the EBI.

[0111] In some embodiments, if it is determined in step S230 that the gradation distribution evaluation value of the brightness / contrast image matches a preset condition, the step of directly scanning the target defect detection area of ​​the wafer to be detected with the electron beam and subsequent related steps may be performed without performing the quality detection step of the astigmatism image. In some embodiments, only the quality detection step of the astigmatism image may be performed, and the quality detection step of the brightness / contrast image may not be performed.

[0112] In some embodiments, before performing the wafer defect detection step, a focused image quality detection step is first performed. As shown in FIG. 6, the focused image quality detection step includes a focused image acquisition and sharpness calculation step, a sharpness evaluation value acquisition step, and a focused image quality judgment step, which correspond to the following steps S410 to S430, respectively, and will be introduced in detail as follows.

[0113] In step S410, a focused image of the wafer to be detected is obtained, and the image sharpness of the focused image is calculated.

[0114] In one embodiment, obtaining a focused image of the wafer to be detected includes scanning a wafer area of ​​a non-defect detection area other than a target defect detection area on the wafer to be detected and within a range of less than a fourth preset distance from the target defect detection area with an electron beam, and obtaining a focused image of the wafer area.

[0115] The fourth predetermined distance is a distance value that is sufficiently close to the predetermined target defect detection area, and by making the focused image an area image adjacent to the target defect detection area, it is possible to avoid the obtained focused image being unable to accurately represent the image quality of the target defect detection area due to minute errors between different areas of the wafer to be detected.

[0116] In one embodiment, the relationship

[0117]

number

[0118] where P is the image sharpness of the focused image, m and n are the length and width of the focused image, respectively, df is the gradation change width of the pixel dot of the focused image, dx is the increase in the distance between the pixel dots of the focused image, i is a pixel dot of the focused image, and a is a neighboring point of the pixel dot. That is, for each pixel dot in the focused image, 8 neighboring points are taken one by one, and the corresponding gray scale is subtracted from each of them. Then, the weighted sum of the 8 gray scale difference values ​​df obtained by first subtracting the corresponding gray scale from each of the 8 neighboring points is calculated. Here, the magnitude of the weight depends on the distance dx between the neighboring point and the pixel dot. If the distance between the neighboring point and the pixel dot is short, the weight is large, and if the distance between the neighboring point and the pixel dot is far, the weight is small. For example, the weight of the gray scale difference value in the 45° and 135° directions needs to be multiplied by 1 / √2 to the weight of the gray scale difference value in the 0° and 90° directions. After adding up the values ​​obtained for all the pixel dots, the total number of pixel dots in the focused image is calculated.

[0119]

number

[0120] Then, we obtain the image sharpness P of the focused image by dividing by . This relational expression is a statistic of the degree of gradation diffusion around each pixel dot of the focused image, that is, the greater the degree of diffusion, the clearer the image is.

[0121] In this embodiment, by reflecting the gradation difference values ​​of the 8 neighboring points of the focused image and the gradation distribution state of the image, it is possible to obtain an accurate calculation result of the image sharpness without being affected by parameter fluctuations due to factors such as noise. Of course, in other embodiments, the image sharpness of the focused image may be calculated by other methods.

[0122] In step S420, a sharpness evaluation value of the focused image is obtained based on the image sharpness of the focused image.

[0123] In one embodiment, a sharpness evaluation value of the focused image is obtained based on the image sharpness of the focused image, that is, a sharpness difference value between the image sharpness of the focused image and a standard sharpness value of the focused image set in advance is calculated, and the sharpness evaluation value of the focused image is obtained, that is, the sharpness difference value between the image sharpness of the focused image and the standard sharpness value of the focused image set in advance is used as the sharpness evaluation value of the focused image. The calculation method of the sharpness evaluation value of the focused image is simple, and the image quality of the focused image can be accurately evaluated.

[0124] In one embodiment, a sharpness evaluation value of the focused image is obtained based on the image sharpness of the focused image, that is, the image sharpness of the focused image is the sharpness evaluation value of the focused image. If the sharpness evaluation value of the focused image is equal to or greater than the sum of the preset standard sharpness of the focused image and a third sharpness difference value, the sharpness evaluation value of the focused image does not meet the preset condition.

[0125] Of course, the present application is not limited to using the sharpness evaluation value of the focused image as the sharpness difference value between the image sharpness of the focused image and a predetermined standard sharpness of the focused image or the image sharpness of the focused image, and in other embodiments, the sharpness evaluation value of the focused image may be determined by any method.

[0126] In step S430, it is determined whether the sharpness evaluation value of the focused image meets the preset condition. If the sharpness evaluation value of the focused image does not meet the preset condition, a defect detection abort step, i.e., step S440, is executed. If the sharpness evaluation value of the focused image meets the preset condition, a step of scanning the target defect detection area of ​​the wafer to be detected with an electron beam is further executed.

[0127] Here, in an embodiment in which the sharpness evaluation value of the focused image is the sharpness difference value between the image sharpness of the focused image and a predetermined standard sharpness of the focused image, if the sharpness evaluation value of the focused image is equal to or greater than the third sharpness difference threshold, i.e., if the sharpness evaluation value of the focused image does not meet the predetermined condition, the process proceeds to step S440, and if the sharpness evaluation value of the focused image is smaller than the third sharpness difference threshold, the sharpness evaluation value of the focused image meets the predetermined condition.

[0128] In an embodiment in which the image sharpness of the focused image is used as the sharpness evaluation value of the focused image, if the sharpness evaluation value of the focused image is equal to or greater than the sum of the preset standard sharpness of the focused image and the third sharpness difference threshold, i.e., if the sharpness evaluation value of the focused image does not meet the preset condition, proceed to step S440, and if the sharpness evaluation value of the focused image is smaller than the sum of the preset standard sharpness of the focused image and the third sharpness difference threshold, the sharpness evaluation value of the focused image meets the preset condition.

[0129] In step S440, defect detection for the target wafer is stopped.

[0130] If it is determined that the image quality of the focused image is poor, the process proceeds directly to a defect detection abort step, and the defect detection program for the subsequent wafer to be detected is stopped, thereby avoiding meaningless execution steps and improving the effective utilization rate of the EBI.

[0131] In one embodiment, in step S430, it is determined that the sharpness evaluation value of the focused image matches the preset condition, and further a quality detection step of a brightness / contrast image is executed. Specifically, for the brightness / contrast image quality detection step, see the explanation of steps S210 to S230. If it is determined in step S230 that the gradation distribution evaluation value of the brightness / contrast image matches the preset condition, then a quality detection step of an astigmatism image is executed. Specifically, for the astigmatism image quality detection step, see the explanation of steps S310 to S330. In step S330, it is determined that the sharpness evaluation value of the astigmatism image matches the preset condition, and further a step of performing electron beam scanning on a target defect detection area of ​​the wafer to be detected is executed. If it is determined in step S330 that the sharpness evaluation value of the astigmatism image does not match the preset condition, then a step of canceling defect detection on the wafer to be detected is executed.

[0132] Focus, brightness / contrast, and astigmatism are three important evaluation indexes in electron beam scanning images. The focus image quality, brightness / contrast image quality, and astigmatism image quality are judged in turn. If any of the indexes is poor, the defect detection on the target wafer is stopped. If all three indexes are good, the step of performing electron beam scanning on the target defect detection area on the target wafer is executed, so as to avoid meaningless execution steps to the greatest extent possible and improve the effective utilization rate of EBI.

[0133] In some embodiments, if it is determined in step S430 that the sharpness evaluation value of the focused image matches a preset condition, one or both of the brightness / contrast image quality detection step and the astigmatism image quality detection step may not be executed. In some embodiments, the order of execution of the focused image quality detection step, the brightness / contrast image quality detection step, and the astigmatism image quality detection step may be reversed.

[0134] 7 shows an overall flow chart of wafer defect detection according to an embodiment of the present application, and as shown in FIG 7, wafer defect detection includes a recipe setting step and a wafer detection step. Here, in the recipe setting step, a focused image, a brightness / contrast image, an astigmatism image, and a wafer image are defined in sequence, and a standard sharpness of the focused image corresponding to the focused image, a standard tone distribution corresponding to the brightness / contrast image, a standard sharpness of the astigmatism image corresponding to the astigmatism image, and a standard sharpness of the wafer image corresponding to the wafer image are defined.In the wafer detection stage, first, a focused image of the wafer to be detected is obtained, an image sharpness of the focused image is calculated, a sharpness difference value between the image sharpness of the focused image and the standard sharpness of the focused image is calculated, and the sharpness difference value is sent to the SPC system. The SPC system judges whether the sharpness difference value is smaller than a third sharpness difference threshold value. If NO, the defect detection of the wafer to be detected is stopped. If YES, a brightness / contrast image of the wafer to be detected is further obtained, a gradation distribution of the brightness / contrast image is calculated, a pass rate of all gradations within a preset number of σ in the gradation distribution is calculated, and the pass rate is sent to the SPC system. The SPC system judges whether the pass rate is larger than a preset threshold value. If YES, the defect detection of the wafer to be detected is stopped. If NO, an astigmatism image of the wafer to be detected is further obtained, an image sharpness of the astigmatism image is calculated, and the pass rate of the astigmatism image is sent to the SPC system. A sharpness difference value between the image sharpness and the standard sharpness of the astigmatism image is calculated, the sharpness difference value is sent to an SPC system, the SPC system determines whether the sharpness difference value is smaller than a second sharpness difference threshold, and if NO, the defect detection of the wafer to be detected is stopped, and if YES, the process proceeds to a wafer defect detection step, where an electron beam scan is performed on a target defect detection area of ​​the wafer to be detected, and after the scanning is completed, fixed point sampling is further performed to obtain a wafer image of the wafer to be detected, the image sharpness of the wafer image is calculated, a sharpness difference value between the image sharpness of the wafer image and the standard sharpness of the wafer image is calculated, the sharpness difference value is sent to the SPC system, and the SPC system determines whether the sharpness difference value is smaller than a first sharpness difference threshold, and if NO, the defect detection of the wafer to be detected is stopped, and the defect detection result of the wafer to be detected is marked as an unreliable result.

[0135] In the embodiment shown in FIG. 7, the quality of the focused image, the quality of the brightness / contrast image, and the quality of the astigmatism image are judged in order. If any of the indicators is bad, the defect detection of the target wafer is stopped. Only when all three indicators are good, that is, the EBI is not broken and the target wafer is not defective (for example, the target wafer is not properly placed), can the step of scanning the target defect detection area of ​​the target wafer be performed, so as to avoid the subsequent defect detection result being unreliable due to EBI failure, the target wafer being not properly placed, etc., to avoid meaningless execution steps to the maximum extent, and to improve the effective utilization rate of the EBI. Since the EBI may have problems in the detection stage, the image quality is detected secondarily after the scanning is completed, so as to avoid the defect detection result being inaccurate due to the image quality poor caused by the EBI or wafer problem in the scanning stage, and to improve the reliability of the final defect detection result. In addition, the image quality detection is performed based on the actual target wafer, and the accuracy of image quality monitoring is high.

[0136] Next, as shown in FIG. 8, this embodiment provides a wafer defect detection apparatus 800, which mainly includes: a wafer scanning module 801 for detecting a wafer, an image sharpness calculation module 802, a sharpness evaluation value calculation module 803, a sharpness evaluation value judgment module 804, and a detection result mark module 805.

[0137] Here, the target wafer scanning module 801 is used to perform electron beam scanning on the target defect detection area of ​​the target wafer to detect defects in the target defect detection area, where the target wafer has one or more defect detection areas.

[0138] The image sharpness calculation module 802 is for acquiring a wafer image of a wafer to be detected and calculating the image sharpness of the wafer image.

[0139] In one embodiment, the image sharpness calculation module 802 calculates the image sharpness using the relationship

[0140]

number

[0141] where P is the image sharpness of the wafer image, m and n are the length and width of the wafer image, respectively, df is the gradation change width of the pixel dot of the wafer image, dx is the increase in the distance between the pixel dots of the wafer image, i is a pixel dot of the wafer image, and a is a neighboring point of the pixel dot.

[0142] In one embodiment, the wafer image is an image of a wafer area that is not scanned by the electron beam and is outside a target defect detection area on the wafer being detected and within less than a first preset distance from the target defect detection area.

[0143] The sharpness evaluation value calculation module 803 is for obtaining a sharpness evaluation value of a wafer image based on the image sharpness of the wafer image.

[0144] The sharpness evaluation value determination module 804 is for determining whether the sharpness evaluation value of the wafer image matches a preset condition. The detection result marking module 805 is for marking the defect detection result of the wafer to be detected as an unreliable detection result when the sharpness evaluation value of the wafer image does not match a preset condition.

[0145] In one embodiment, the sharpness evaluation value calculation module 803 is configured to calculate a sharpness difference value between the image sharpness of the wafer image and a preset standard sharpness of the wafer image to obtain a sharpness evaluation value of the wafer image. The sharpness evaluation value of the wafer image does not meet the preset condition when the sharpness evaluation value of the wafer image is equal to or greater than a first sharpness difference threshold.

[0146] In one embodiment, the sharpness evaluation value calculation module 803 outputs the sharpness evaluation value of the wafer image to an SPC system, and the detection result mark module 805 functions as a part of the SPC system.

[0147] In one embodiment, the wafer defect detection apparatus 800 further includes a defect detection abort module 806, which is configured to abort defect detection of the wafer being detected if the sharpness evaluation value of the wafer image does not meet a preset condition.

[0148] In one embodiment, the wafer defect detection apparatus 800 further includes a gradation distribution calculation module 807, a gradation distribution evaluation value calculation module 808, and a gradation distribution evaluation value judgment module 809, where the gradation distribution calculation module 807 is configured to acquire a brightness / contrast image of the wafer to be detected, and acquire the gradation distribution of the brightness / contrast image, the gradation distribution evaluation value calculation module 808 is configured to acquire a gradation distribution evaluation value of the brightness / contrast image based on the gradation distribution of the brightness / contrast image, the gradation distribution evaluation value judgment module 809 is used to judge whether the gradation distribution evaluation value meets a preset condition, and the defect detection abort module 806 is configured to abort defect detection of the wafer to be detected if the gradation distribution evaluation value of the brightness / contrast image does not meet the preset condition.

[0149] In one embodiment, the gradation distribution calculation module 807 is configured to obtain a normal distribution of the number of pixel dots corresponding to each gradation in the brightness / contrast image, calculate the number of pixel dots corresponding to each gradation within a preset number of sigmas in the normal distribution, and obtain the gradation distribution of the brightness / contrast image; the gradation distribution evaluation value calculation module 808 is configured to determine whether a gradation is pass or not based on the number of pixel dots corresponding to the gradation within a preset number of sigmas in the normal distribution and the number of pixel dots corresponding to the same gradation in a preset standard gradation distribution, and calculate the pass rate of all gradations within the preset number of sigmas in the normal distribution as the gradation distribution evaluation value of the brightness / contrast image.

[0150] In one embodiment, the preset number of sigmas is 1-2 sigmas.

[0151] In one embodiment, the gradation distribution evaluation value calculation module 808 is configured to determine that a gradation is acceptable when the ratio of the number of pixel dots corresponding to the gradation within a preset number of sigmas in the normal distribution to the number of pixel dots corresponding to the same gradation in the standard gradation distribution is less than 5% and the difference value is 90%. The gradation distribution evaluation value does not meet the preset condition when the pass rate of all gradations is less than 95%, and the gradation distribution evaluation value meets the preset condition when the pass rate of all gradations is greater than 95%.

[0152] In one embodiment, the image sharpness calculation module 802 is further configured to acquire an astigmatism image of the wafer to be detected and calculate the image sharpness of the astigmatism image, the sharpness evaluation value calculation module 803 is further configured to acquire a sharpness evaluation value of the astigmatism image based on the image sharpness of the astigmatism image, the sharpness evaluation value determination module 804 is configured to determine whether the sharpness evaluation value of the astigmatism image complies with a preset condition, the defect detection abort module 806 is configured to abort defect detection of the wafer to be detected if the sharpness evaluation value of the astigmatism image does not match the preset condition, and the wafer scanning module 801 to be detected is configured to perform a step of performing electron beam scanning on a target defect detection area of ​​the wafer to be detected if the sharpness evaluation value of the astigmatism image complies with the preset condition.

[0153] In one embodiment, the sharpness evaluation value calculation module 803 is configured to calculate a sharpness difference value between the image sharpness of the astigmatism image and a preset standard sharpness of the astigmatism image to obtain a sharpness evaluation value of the astigmatism image. The sharpness evaluation value of the astigmatism image does not meet the preset condition means that the sharpness evaluation value of the astigmatism image is equal to or greater than a second sharpness difference threshold, and the sharpness evaluation value of the astigmatism image meets the preset condition means that the sharpness evaluation value of the astigmatism image is smaller than the second sharpness difference threshold.

[0154] In one embodiment, the image sharpness calculation module 802 is further configured to acquire a focused image of the wafer to be detected and calculate the image sharpness of the focused image, the sharpness evaluation value calculation module 803 is further configured to acquire a sharpness evaluation value of the focused image based on the image sharpness of the focused image, the sharpness evaluation value determination module 804 is configured to determine whether the sharpness evaluation value of the focused image meets a preset condition, and the defect detection abort module 806 is configured to abort defect detection of the wafer to be detected if the sharpness evaluation value of the focused image does not meet the preset condition.

[0155] In one embodiment, the sharpness evaluation value calculation module 803 is configured to calculate a sharpness difference value between the image sharpness of the focused image and a standard sharpness of the focused image set in advance, and obtain a sharpness evaluation value of the focused image. The sharpness evaluation value of the focused image does not meet the preset condition when the sharpness evaluation value of the focused image is equal to or greater than a third sharpness difference threshold.

[0156] The process of implementing the functions and actions of each module in the wafer defect detection apparatus 800 is specifically described with reference to the process of implementing the corresponding step in the wafer defect detection method, and the description thereof will be omitted here.

[0157] As shown in FIG. 9, this embodiment provides an electron beam scanning device 900, which includes one or more processors 901 and a memory 902, where the memory 902 stores one or more programs, which, when executed by the one or more processors 901, cause the electron beam scanning device 900 to realize the wafer defect detection method of the present application.

[0158] The electron beam scanning device 900 may be equipped with the SPC system.

[0159] The present application redesigns the image quality monitoring system of the EBI, detects the image sharpness and gradation distribution in advance, performs secondary detection after the scanning is completed, and marks the defect detection result of the target wafer with poor wafer image quality as an unreliable detection result, thereby distinguishing the defect detection result of the target wafer with good wafer image quality, improving the reliability of the defect detection result of each target wafer, and timely stopping the defect detection program of the target wafer with poor wafer image quality, avoiding meaningless execution steps, and improving the effective utilization rate of the EBI.

[0160] FIG. 10 is a block diagram showing the configuration of a computer system for implementing some embodiments of the present application. Note that the computer system shown in FIG. 10 is merely an example and does not impose any limitations on the functionality and scope of use of the embodiments of the present application.

[0161] As shown in Fig. 10, the computer system 1000 includes a CPU (Central Processing Unit) 1001 and can execute various appropriate operations and processes according to a program stored in a ROM (Read-Only Memory) 1002 or a program loaded from a storage unit 1008 to a RAM (Random Access Memory) 1003, for example, executing the wafer defect detection method in the above embodiment. The RAM 1003 also stores various programs and data necessary for the system operation. The CPU 1001, the ROM 1002, and the RAM 1003 are connected to each other by a bus 1004. An I / O (Input / Output) interface 1005 is also connected to the bus 1004.

[0162] To the I / O interface 1005, an input unit 1006 including a keyboard, a mouse, etc., an output unit 1007 including a CRT (Cathode Ray Tube), an LCD (Liquid Crystal Display), etc., and a speaker, etc., a storage unit 1008 including a hard disk, etc., and a communication unit 1009 including a network interface card such as a LAN (Local Area Network) card and a modem, etc. are connected. The communication unit 1009 performs communication processing via a network such as the Internet. A driver 1010 is also connected to the I / O interface 1005 as necessary. A removable medium 1011 such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory is mounted in the drive 1010 as necessary, and a computer program read from the removable medium 1011 is installed in the storage unit 1008 as necessary.

[0163] In particular, according to an embodiment of the present application, the process described with reference to the above flowchart may be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, the computer program product including a computer program loaded on a computer-readable medium, the computer program including a computer program for executing all or some of the steps shown in the flowchart in the wafer defect detection method. In such an embodiment, the computer program may be downloaded and installed from a network via the communication unit 1009 and / or installed from a removable medium 1011. When the computer program is executed by the central processing unit (CPU) 1001, various functions defined in the system of the present application are executed.

[0164] It should be noted that the computer-readable medium shown in the embodiments of the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above. The computer-readable storage medium may be, for example, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples of the computer-readable storage medium include, but are not limited to, an electrical connection having one or more conductors, a portable computer magnetic disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, the computer-readable storage medium may be any tangible medium that contains or stores a program, and the program may be instructed to execute the use of or in combination with a system, apparatus, or device. In this application, a computer-readable signal medium may include a data signal propagating in baseband or as part of a carrier wave, carrying a computer-readable computer program. Such a propagating data signal may take a variety of forms, including, but not limited to, an electromagnetic signal, an optical signal, or any suitable combination of the above. A computer-readable signal medium may be any computer-readable medium other than a computer-readable storage medium, which may transmit, propagate, or transmit an instruction execution system, apparatus, or device, or a program used in conjunction therewith. A computer program contained in a computer-readable medium may be transmitted in any suitable medium, including, but not limited to, wireless, wired, or the like, or any suitable combination of the above.

[0165] The flowcharts and block diagrams in the drawings show possible system architectures, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. Here, each block in the flowcharts or block diagrams may represent a module, block or part of code, which includes one or more executable instructions for implementing a predetermined logical function. Alternatively, it should be noted that the functions described in the blocks may be generated in a different order from the order described in the drawings. For example, two consecutively shown blocks may actually be essentially executed in parallel, or they may be executed in the reverse order, as determined by such functions. It should be noted that each block in the block diagrams or flowcharts, and combinations of blocks in the block diagrams or flowcharts, may be implemented in a system with dedicated hardware that executes a predetermined function or operation, or may be implemented in a combination of dedicated hardware and computer instructions.

[0166] The units mentioned in the embodiments of the present application may be implemented in a software manner or in a hardware manner, and the described units may be provided in a processor, but the names of these units do not limit the units themselves in some cases.

[0167] In another aspect, the present application further provides a computer-readable storage medium, which may be included in the electron beam scanning device described in the above embodiment, or may exist independently and not be integrated into the electron beam scanning device, the computer-readable storage medium carrying one or more programs, which, when executed by the electron beam scanning device, causes the electron beam scanning device to realize the method in the above embodiment.

[0168] It should be noted that, although the above detailed description refers to several modules or units of an apparatus for performing operations, such division is not necessary. In fact, according to an embodiment of the present application, features and functions of two or more of the above modules or units may be embodied in one module or unit. Conversely, features and functions of one of the above modules or units may be embodied by multiple modules or units.

[0169] The above description of the embodiments is intended to facilitate understanding by those skilled in the art that the exemplary embodiments described herein may be realized by software, or may be realized by combining necessary hardware with software. Therefore, the technical solutions according to the embodiments of the present application may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a U-disk, a portable hard disk, etc.) or on a network, and includes several instructions so that a computing device (which may be a personal computer, a server, a touch terminal, or a network device, etc.) executes the method according to the embodiments of the present application.

[0170] Those skilled in the art can easily conceive of other embodiments of the present application after reading the specification and practicing the invention disclosed herein. This application is intended to cover any modifications, uses or adaptations of the present application, which modifications, uses or adaptations follow the general principles of the present application and include common knowledge or commonly used technical means in the art that are not disclosed herein. It is intended that the specification and examples be considered as merely exemplary, with the true scope and spirit of the present application being indicated by the appended claims. [Explanation of symbols]

[0171] 800, wafer defect detection device, 801, detection target wafer scanning module, 802, image sharpness calculation module, 803, sharpness evaluation value calculation module, 804, sharpness evaluation value judgment module, 805, detection result mark module, 806, defect detection abort module, 807, gradation distribution calculation module, 808, gradation distribution evaluation value calculation module, 809, gradation distribution evaluation value judgment module, 900, electron beam scanning device, 901, processor, 902, memory, 1000, computer system, 1001, CPU, 1002, ROM, 1003, RAM, 1004, bus, 1005, I / O interface, 1006, input section, 1007, output section, 1008, memory section, 1009, communication section, 1010, drive, 1011, removable media.

Claims

1. A method for detecting defects in a target defect detection area of ​​a wafer to be inspected, the method comprising: scanning the target defect detection area of ​​a wafer to be inspected with an electron beam; and detecting defects in the target defect detection area, the wafer to be inspected having one or a plurality of defect detection areas; acquiring a wafer image of the wafer to be detected and calculating an image sharpness of the wafer image; acquiring a sharpness evaluation value of the wafer image based on the image sharpness of the wafer image; determining whether or not a sharpness evaluation value of the wafer image matches a preset condition, and if the sharpness evaluation value of the wafer image does not match the preset condition, marking a defect detection result of the wafer to be detected as an unreliable detection result.

13. A wafer defect detection method comprising:

2. acquiring a sharpness evaluation value of the wafer image based on the image sharpness of the wafer image includes calculating a sharpness difference value between the image sharpness of the wafer image and a preset standard sharpness of the wafer image, and acquiring a sharpness evaluation value of the wafer image; The sharpness evaluation value of the wafer image does not match the preset condition when the sharpness evaluation value of the wafer image is equal to or greater than a first sharpness difference threshold.

2. The method for detecting defects on a wafer according to claim 1,

3. If the sharpness evaluation value of the wafer image does not match a preset condition, the defect detection of the wafer to be detected is stopped.

2. The method for detecting defects on a wafer according to claim 1,

4. After obtaining a sharpness evaluation value of the wafer image, the method further comprises: The sharpness evaluation value of the wafer image is output to the statistical processing control system so that the statistical processing control system marks the defect detection result of the target wafer as an unreliable detection result when the sharpness evaluation value of the wafer image does not match a preset condition.

2. The method for detecting defects on a wafer according to claim 1,

5. Calculating the image sharpness of the wafer image includes: Relational formula [0010] calculating an image sharpness of the wafer image based on P is the image sharpness of the wafer image, m and n are the length and width of the wafer image, respectively, df is the gradation change width of the pixel dot of the wafer image, dx is the increase in the distance between the pixel dots of the wafer image, i is a pixel dot of the wafer image, and a is a neighboring point of the pixel dot.

2. The method for detecting defects on a wafer according to claim 1,

6. The wafer image is an image of a wafer area that is not scanned by the electron beam and is outside the target defect detection area on the wafer to be inspected and within a range of less than a first preset distance from the target defect detection area.

2. The method for detecting defects on a wafer according to claim 1,

7. Prior to performing electron beam scanning on a target defect detection area of ​​the wafer to be inspected, the method includes: Acquiring a brightness / contrast image of a wafer to be detected and acquiring a gradation distribution of the brightness / contrast image; obtaining a gradation distribution evaluation value of the brightness / contrast image based on the gradation distribution of the brightness / contrast image; and determining whether the gradation distribution evaluation value matches a preset condition, and if the gradation distribution evaluation value does not match the preset condition, stopping defect detection of the wafer to be detected.

7. The wafer defect inspection method according to claim 1, wherein the wafer defect inspection method comprises:

8. Obtaining the gradation distribution of the brightness / contrast image includes: Obtaining a normal distribution of the number of pixel dots corresponding to each gray level in the brightness / contrast image; calculating a number of pixel dots corresponding to each gray level within a predetermined number of sigmas in the normal distribution to obtain a gray level distribution of the brightness / contrast image; Obtaining a gradation distribution evaluation value of the brightness / contrast image based on the gradation distribution of the brightness / contrast image, determining whether the gradation is acceptable or not based on the number of pixel dots corresponding to the gradation within a preset number of sigmas in the normal distribution and the number of pixel dots corresponding to the same gradation in a preset standard gradation distribution; and calculating the pass rate of all gradations within a preset number of sigmas in the normal distribution as a gradation distribution evaluation value of the brightness / contrast image.

8. The method for detecting defects on a wafer according to claim 7.

9. The preset number of sigmas is 1 to 2 sigmas.

9. The method for detecting defects on a wafer according to claim 8.

10. If the difference between the ratio of the number of pixel dots corresponding to the gray levels within a predetermined number of sigmas in the normal distribution and the number of pixel dots corresponding to the same gray levels in the standard gray level distribution and 100% is less than 5%, the gray level is determined to be acceptable; and / or The gradation distribution evaluation value does not meet the preset condition when the pass rate of all the gradations is 95% or less, and when the pass rate of all the gradations is greater than 95%, the gradation distribution evaluation value meets the preset condition.

9. The method for detecting defects on a wafer according to claim 8.

11. When the gradation distribution evaluation value meets a preset condition, the method further comprises: acquiring an astigmatism image of a wafer to be detected and calculating an image sharpness of the astigmatism image; obtaining a sharpness evaluation value of the astigmatism image based on an image sharpness of the astigmatism image; and determining whether a sharpness evaluation value of the astigmatism image matches a preset condition, and if the sharpness evaluation value of the astigmatism image does not match the preset condition, stopping defect detection on the wafer to be detected, and if the sharpness evaluation value of the astigmatism image matches the preset condition, performing an electron beam scan on a target defect detection area on the wafer to be detected.

8. The wafer defect inspection method according to claim 7.

12. obtaining a sharpness evaluation value of the astigmatism image based on the image sharpness of the astigmatism image includes calculating a sharpness difference value between the image sharpness of the astigmatism image and a preset standard sharpness of the astigmatism image, and obtaining a sharpness evaluation value of the astigmatism image; The sharpness evaluation value of the astigmatism image not meeting the preset condition means that the sharpness evaluation value of the astigmatism image is equal to or greater than a second sharpness difference threshold, and the sharpness evaluation value of the astigmatism image meeting the preset condition means that the sharpness evaluation value of the astigmatism image is less than the second sharpness difference threshold.

12. The wafer defect inspection method according to claim 11.

13. Prior to performing electron beam scanning on a target defect detection area of ​​the wafer to be inspected, the method includes: acquiring an astigmatism image of a wafer to be detected and calculating an image sharpness of the astigmatism image; obtaining a sharpness evaluation value of the astigmatism image based on an image sharpness of the astigmatism image; and determining whether or not a sharpness evaluation value of the astigmatism image matches a preset condition, and stopping defect detection of the wafer to be detected when the sharpness evaluation value of the astigmatism image does not match the preset condition.

7. The wafer defect inspection method according to claim 1, wherein the wafer defect inspection method comprises:

14. Prior to performing electron beam scanning on a target defect detection area of ​​the wafer to be inspected, the method includes: acquiring a focused image of a wafer to be detected and calculating an image sharpness of the focused image; obtaining a sharpness evaluation value of the focused image based on an image sharpness of the focused image; and determining whether or not a sharpness evaluation value of the focused image matches a preset condition, and if the sharpness evaluation value of the focused image does not match the preset condition, stopping defect detection of the wafer to be detected.

7. The wafer defect inspection method according to claim 1, wherein the wafer defect inspection method comprises:

15. obtaining a sharpness evaluation value of the focused image based on the image sharpness of the focused image includes calculating a sharpness difference value between the image sharpness of the focused image and a standard sharpness of a focused image set in advance, and obtaining a sharpness evaluation value of the focused image; The sharpness evaluation value of the focused image does not match the preset condition when the sharpness evaluation value of the focused image is equal to or greater than a third sharpness difference threshold value.

15. The method for detecting defects on a wafer according to claim 14.

16. When the sharpness evaluation value of the focused image meets a preset condition, the method further comprises: Acquiring a brightness / contrast image of a wafer to be detected and acquiring a gradation distribution of the brightness / contrast image; obtaining a gradation distribution evaluation value of the brightness / contrast image based on the gradation distribution of the brightness / contrast image; determining whether the gradation distribution evaluation value matches a preset condition; When the gradation distribution evaluation value does not match a preset condition, the defect detection of the wafer to be detected is stopped, and when the gradation distribution evaluation value matches a preset condition, an astigmatism image of the wafer to be detected is obtained, and an image sharpness of the astigmatism image is calculated. obtaining a sharpness evaluation value of the astigmatism image based on an image sharpness of the astigmatism image; determining whether or not a sharpness evaluation value of the astigmatism image meets a preset condition; If the sharpness evaluation value of the astigmatism image does not match a preset condition, stopping the defect detection of the wafer to be detected; If the sharpness evaluation value of the astigmatism image meets a preset condition, performing an electron beam scan on a target defect detection area of ​​the wafer to be detected.

15. The method for detecting defects on a wafer according to claim 14.

17. a target wafer scanning module for scanning a target defect detection area of ​​a target wafer with an electron beam to detect defects in the target defect detection area, the target wafer having one or more defect detection areas; an image sharpness calculation module for acquiring a wafer image of the wafer to be detected and calculating an image sharpness of the wafer image; a sharpness evaluation value calculation module for obtaining a sharpness evaluation value of the wafer image based on an image sharpness of the wafer image; a sharpness evaluation value determination module for determining whether the sharpness evaluation value of the wafer image meets a preset condition; a detection result marking module for marking a defect detection result of the wafer to be detected as an unreliable detection result when a sharpness evaluation value of the wafer image does not match a preset condition. A wafer defect inspection apparatus comprising:

18. one or more processors and memory; The memory is for storing one or more computer programs that, when executed by the one or more processors, cause the processor to realize the wafer defect detection method according to any one of claims 1 to 6.

1. An electron beam scanning device comprising:

19. A method for detecting defects on a wafer, comprising: storing computer-readable instructions, the computer-readable instructions being executed by a computer processor to cause the computer to perform the wafer defect detection method according to any one of claims 1 to 6. A computer-readable storage medium comprising:

Images