Wafer surface defect detection method and device, electronic equipment and storage medium

Abstract

The invention provides a wafer surface defect detection method and device, electronic equipment and a storage medium, and belongs to the technical field of wafer surface detection.The wafer surface defect detection method comprises the steps that a bright field image and a dark field image of the surface of a to-be-detected wafer are obtained; acquiring a first size of a target defect at the same position in the bright field image and the dark field image in the bright field image and a second size of the target defect in the dark field image; and determining a target defect type of the target defect according to the first size and the second size. According to the scheme, the defects on the surface of the to-be-detected wafer can be accurately detected.

Description

Technical Field

[0001] The present disclosure relates to the technical field of wafer surface detection, and in particular to a wafer surface defect detection method, device, electronic equipment and storage medium. Background Art

[0002] During the wafer manufacturing process, surface defects may occur due to the crystal phase of the wafer itself, the mechanical action of the process, the corrosion of chemical solutions, and the residual particles of environmental control. These defects will affect the performance of the final product. Therefore, it is very necessary to detect wafer surface defects. Through detection, defects in the manufacturing process can be discovered and repaired in a timely manner.

[0003] Among the defects on the wafer surface, there is a type of defect with a large area and obvious height difference. This type of defect has a great impact on subsequent processes and cannot be eliminated by cleaning. It needs to be distinguished separately for management and control.

[0004] Among the relevant detection methods, there is no effective method for this type of etching morphology defects with large area and obvious height difference. Summary of the invention

[0005] The present disclosure provides a wafer surface defect detection method, device, electronic equipment and storage medium, which can accurately detect defects on the surface of a wafer to be tested.

[0006] The technical solution of the present disclosure is achieved as follows: In a first aspect, the present disclosure provides a method for detecting wafer surface defects, comprising: obtaining a bright field image and a dark field image of the surface of a wafer to be tested; obtaining a first size in the bright field image and a second size in the dark field image of a target defect at the same position in the bright field image and the dark field image; and determining a target defect type of the target defect based on the first size and the second size.

[0007] In a second aspect, the present disclosure provides a wafer surface defect detection device, which includes: an acquisition part, configured to acquire a bright field image and a dark field image of the surface of a wafer to be tested, and to acquire a first size in the bright field image and a second size in the dark field image of a target defect at the same position in the bright field image and the dark field image; a determination part, configured to determine a target defect type of the target defect based on the first size and the second size.

[0008] In a third aspect, the present disclosure provides an electronic device comprising a processor, a memory, and a program or instruction stored in the memory and executable on the processor, wherein the program or instruction, when executed by the processor, implements the steps of the wafer surface defect detection method as described in the first aspect.

[0009] In a fourth aspect, the present disclosure provides a computer-readable storage medium storing a program or instruction, which, when executed by a processor, implements the steps of the wafer surface defect detection method as described in the first aspect.

[0010] In a fifth aspect, the present disclosure provides a computer program product, wherein the computer program product includes a computer program or instructions. When the computer program product runs on a processor, the processor executes the computer program or instructions to implement the steps of the wafer surface defect detection method as described in the first aspect.

[0011] In a sixth aspect, the present disclosure provides a chip, comprising a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run a program or instruction to implement the wafer surface defect detection method as described in the first aspect.

[0012] The present disclosure provides a wafer surface defect detection method, which determines the target defect type of the target defect at the same position on the surface of the wafer to be tested according to the size of different defect types in the bright field image and the dark field image, thereby improving the detection accuracy. In addition, for gentle slope defects, since the scattered light of the gentle slope is weak and cannot be detected by dark field scattering, the combined detection results of the bright field image and the dark field image can also avoid the gentle slope defect from being judged as an etching morphology defect. Therefore, compared with the single light field detection method, this solution greatly improves the detection accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 A schematic diagram of the structure of a wafer surface defect detection system provided by the present disclosure; Figure 2 One of the flow charts of the wafer surface defect detection method provided by the present disclosure; Figure 3 Schematic diagram of defects at the same position on the wafer surface provided by the present disclosure; Figure 4 An exemplary schematic diagram of wafer surface defects provided by the present disclosure; Figure 5 The second flowchart of the wafer surface defect detection method provided by the present disclosure; Figure 6 A structural block diagram of a wafer surface defect detection device provided by the present disclosure; Figure 7 A schematic diagram of the hardware structure of an electronic device provided by the present invention. DETAILED DESCRIPTION

[0014] The following will be combined with the drawings in the present disclosure to clearly describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments in the present application belong to the scope of protection of the present application.

[0015] The terms "first", "second", etc. in the specification of this application are used to distinguish similar objects, rather than to describe a specific order or precedence. It should be understood that the terms used in this way can be interchangeable where appropriate, so that the present disclosure can be implemented in an order other than those illustrated or described herein, and the objects distinguished by "first", "second", etc. are generally of one type, and the number of objects is not limited. For example, the first object can be one or more.

[0016] In the related technology, optical detection technology is usually used to detect defects on the surface of the wafer. Optical detection technology includes diffraction method, interference method and scattering method. The diffraction method relies on the diffraction phenomenon of light. It is necessary to compare the signal obtained after scanning the light at each point on the surface of the wafer with the signal obtained at the same position of the recorded intact positive film to determine whether there are defects on the surface of the wafer. The interference method is based on the interference phenomenon of light waves. Although it can provide high-resolution images for detecting surface defects such as pits, protrusions, sharp corners, and grooves, its disadvantages are high cost and slow detection speed, which is not suitable for large-scale rapid detection. The scattering method uses the scattering characteristics of the incident light to detect defects. Due to its high detection efficiency and simple result analysis, it is suitable for large-scale wafer defect detection.

[0017] The scattering method is divided into bright field scattering and dark field scattering according to the different lighting methods and imaging principles. Bright field scattering refers to the light source directly irradiating the wafer surface, that is, the angle between the incident light of the light source and the normal of the wafer surface is 0 degrees. The defects on the wafer surface are determined by detecting the reflected light that has lost a part of the light intensity. Dark field scattering refers to the light source irradiating the wafer surface at an inclined angle, that is, the angle between the incident light of the light source and the normal of the wafer surface is greater than 0 degrees and less than 90 degrees. The defects on the wafer surface will scatter light, which will be collected and imaged.

[0018] However, the detection result of dark field scattering only identifies the theoretical size of the defect based on the scattered light of the defect. In practice, when the defect is larger than 100nm, the scattered light cannot accurately express the true size of the defect due to different defect morphologies. For example, the middle of an etched morphology defect may be very flat, resulting in the scattered light of the flat middle part not being very strong, and can only be determined by the edge. However, the edge of an etched morphology defect is linear and relatively narrow, and the distribution of etched morphology defects on the wafer is not fixed. However, the incident direction of the light is the same, resulting in different scattered light of defects at different positions and angles, and the defect size calculated based on the scattered light is also different. Therefore, the defects indicated by the detection result of dark field scattering are different from the actual defects.

[0019] When testing through bright field scattering, usually the height difference is compared between two test points with a large distance (such as more than 25 microns). If the height difference is greater than a certain value, it will be judged that there are one or more defects. Therefore, the defect judgment is sufficient in distance, and larger defects can be identified through bright field scattering. However, when the defect shape is a gentle slope, it can be detected through bright field scattering, and because the size of the gentle slope defect is usually larger, this kind of gentle slope defect is easily judged as an etching morphology defect.

[0020] Although etching morphology defects can be detected by both bright field scattering and dark field scattering, the detection accuracy is low and many defects are missed.

[0021] Based on the above problems, the present disclosure aims to provide a wafer surface defect detection method that can effectively detect etching morphology defects on the wafer surface.

[0022] First, the present disclosure provides a wafer surface defect detection system capable of implementing the above-mentioned wafer surface defect detection method. Figure 1 As shown in the figure, a wafer surface defect detection system shown in the present disclosure includes: multiple light sources, a camera 20 and a controller 30, Figure 1 Two light sources, a dark field light source 101 and a bright field light source 102, are exemplarily shown in the figure. In practice, in order to improve the imaging quality, multiple light sources may be used.

[0023] Among them, the dark field light source 101 is configured to provide oblique light to the wafer surface 1, and the angle θ between the incident light of the dark field light source 101 and the normal 2 of the wafer surface 1 is greater than 0 degree and less than 90 degrees; the bright field light source 102 is configured to provide direct light to the wafer surface 1, and the incident light of the bright field light source 102 is parallel to the normal 2 of the wafer surface 1 to be measured.

[0024] The camera 20 is configured to collect scattered light from the surface 1 of the wafer to be tested to form image information and transmit it to the controller 30. In order to collect high-quality images, the camera 20 can be a high-resolution, high-sensitivity camera.

[0025] The controller 30 is configured to obtain a first size of a target defect at the same position in the bright field image and the dark field image in the bright field image, and a second size in the dark field image; and determine a target defect type of the target defect according to the first size and the second size.

[0026] The wafer surface defect detection system disclosed in the present invention is integrated on an automated wafer inspection line and integrated with other monitoring systems of the wafer manufacturing process, and can perform online real-time detection to achieve comprehensive process control and quality assurance.

[0027] The wafer surface defect detection method provided by the present disclosure is described in detail below through specific embodiments and application scenarios in conjunction with the accompanying drawings.

[0028] like Figure 2 As shown, the present disclosure provides a method for detecting wafer surface defects, which may include the following steps S201 to S203.

[0029] In step S201, a bright field image and a dark field image of the surface of a wafer to be tested are acquired.

[0030] Among them, the bright field image is an image obtained in a bright field environment provided by a bright field light source, and the dark field image is an image obtained in a dark field environment provided by a dark field light source.

[0031] In order to improve the accuracy of defect detection on the wafer surface, in some embodiments, a bright field illumination image in a bright field environment and a dark field illumination image in a dark field environment are collected; the bright field illumination image and the dark field illumination image are preprocessed to obtain a preprocessed bright field illumination image and a preprocessed dark field illumination image; defects in the preprocessed bright field illumination image and the preprocessed dark field illumination image are marked through edge detection algorithms and morphological operations to obtain a bright field image and a dark field image.

[0032] Preprocessing includes denoising, grayscale conversion, binarization, etc. Among them, denoising can be achieved through filtering algorithms to reduce the noise introduced by the camera, electronic interference or environmental factors, and improve the signal-to-noise ratio of bright field illumination images and dark field illumination images; grayscale conversion is to convert color images into grayscale images, simplify data, and highlight important information in the image; binarization is to convert grayscale images into images containing only two pixel values ​​(usually black and white) for further processing. Both grayscale conversion and binarization are intended to reduce data complexity and computational costs while retaining key information in the image.

[0033] Edge detection algorithms (such as the Canny operator) are used to identify the edges of objects included in the image. Morphological operations can be used to remove noise, enhance image features, connect adjacent areas, and extract image edges. For example, corrosion operations can make bright areas in the image smaller, while dilation operations make bright areas larger. The surface of the wafer is a mirror surface when there are no defects. In this case, there are no objects with edges in the bright field illumination images and dark field illumination images collected. Therefore, if there are edges in the bright field illumination images and dark field illumination images collected, it means that there are defects in the wafer.

[0034] Through edge detection algorithms and morphological operations, the preprocessed bright field illumination image and the preprocessed dark field illumination image are marked according to the edges, and the marking includes the position and the size of the connected area, and finally the bright field image and the dark field image containing the marking are obtained.

[0035] In step S202 , a first size of a target defect at the same position in the bright field image and the dark field image in the bright field image and a second size of the target defect in the dark field image are obtained.

[0036] For each defect included in the bright field image and each defect included in the dark field image, determine whether they are defects at the same position. In some feasible methods, obtain a first area on the wafer to be tested corresponding to each defect in the dark field image, and a second area on the wafer to be tested corresponding to each defect in the bright field image; determine the overlapping area between the first area and the second area, and use the defect covering the overlapping area as the target defect.

[0037] Some defect types can only be detected in a bright field environment, some defect types can only be detected in a dark field environment, and some defect types can be detected in both bright field and dark field environments. For defects included in both bright field images and dark field images, if a defect is located in a first area on the surface of the wafer to be tested in a bright field image and in a second area on the surface of the wafer to be tested in a dark field image, and the first area and the second area overlap, then the defect is determined to be a target defect.

[0038] like Figure 3 As shown, in the bright field image, area 10 corresponds to a certain defect in the surface 1 of the wafer to be tested, and in the dark field image, area 11 corresponds to the certain defect in the surface 1 of the wafer to be tested. Area 10 and area 11 have overlapping areas, and area 12 shown by shade in the figure is the overlapping area, and the certain defect is determined to be the target defect.

[0039] Among them, the size includes the length, width and height of the defect. The specific size is determined by: determining the minimum circumscribed rectangle of the area corresponding to the defect, the length and width of the minimum circumscribed rectangle are the length and width of the defect, and the height is the difference between the maximum distance and the minimum distance from the wafer surface at each position in the defect area.

[0040] In step S203 , a target defect type of the target defect is determined according to the first size and the second size.

[0041] In some embodiments, a first defect type corresponding to the target defect in the bright field image is determined based on the first size; a second defect type corresponding to the target defect in the dark field image is determined based on the second size; and a target defect type is determined based on the first defect type and the second defect type.

[0042] Among them, the defects that can be detected in a bright field environment are the first defect type, and the defects that can be detected in a dark field environment are the second defect type. The first defect type includes large-sized defects and step-shaped defects in the bright field, etc.; the second defect type includes large-sized defects in the dark field, particles, scratches, surface protrusion defects, etc. The specific defects included in the above-mentioned first type defects and second type defects are not limited in this disclosure, and all defects that can be detected in bright field or dark field environments are within the protection scope of this disclosure.

[0043] The target defect type includes any of the following: etching morphology defects, gentle slope defects, step defects, wide scratches, large-area surface protrusion defects, narrow scratches, small-area surface protrusion defects, particles. The target defect type can also be other types that can be detected in bright field or dark field environment.

[0044] In some achievable methods, a second defect type corresponding to the target defect in the dark field image is determined based on the second size; and the target defect type is determined based on the first defect type and the second defect type, specifically: when the first defect type is a large-size defect in the bright field and the second defect type is a large-size defect in the dark field, the target defect type is determined to be an etching morphology defect.

[0045] In some embodiments, the determination conditions of etching morphology defects are preset, and whether it is an etching morphology defect is determined according to whether the determination conditions are met. Specifically, when the first size belongs to the first preset range, the first defect type corresponding to the target defect in the bright field image is determined to be a bright field large size defect; when the second size belongs to the second preset range, the second type of defect corresponding to the target defect in the dark field image is determined to be a dark field large size defect.

[0046] The first preset range and the second preset range are determined according to the characteristics of the etching morphology defects. The minimum value range of the first preset range can be: length greater than or equal to 15 microns and less than or equal to 40 microns, width greater than or equal to 15 microns and less than or equal to 40 microns, height greater than or equal to 4 nanometers and less than or equal to 8 nanometers; the minimum value range of the second preset range can be: length greater than or equal to 50 nanometers and less than or equal to 150 nanometers, width greater than or equal to 50 nanometers and less than or equal to 150 nanometers. The minimum value range of the first preset range and the minimum value range of the second preset range are only an implementable method and are not intended to limit the present disclosure. Depending on the size of the defects in the actual wafer, other ranges may also be used.

[0047] Exemplarily, the minimum length and width of the first preset range are both 15 microns, and the minimum height is 4 nanometers, and the minimum length and width of the second preset range are both 50 nanometers. The first preset range is: the length and width are both greater than 15 microns, and the height is greater than or equal to 4 nanometers, and the second preset range is: the length and width are both greater than 50 nanometers; the minimum length and width of the first preset range are both 20 microns, and the minimum height is 5 nanometers, and the minimum length and width of the second preset range are both 100 nanometers. The first preset range is: the length and width are both greater than 20 microns, and the height is greater than or equal to 5 nanometers, and the second preset range is: the length and width are both greater than 100 nanometers; the minimum length and width of the first preset range are both 40 microns, and the minimum height is 8 nanometers, and the minimum length and width of the second preset range are both 150 nanometers. The first preset range is: the length and width are both greater than 40 microns, and the height is greater than or equal to 8 nanometers, and the second preset range is: the length and width are both greater than 150 nanometers. Here, only some points in the minimum value range in the first preset range and some points in the minimum value range in the second preset range are given as examples. Other points are also within the protection scope of the present disclosure and will not be described again here to avoid repetition.

[0048] That is, when the first size of the target defect belongs to the first preset range and the second size belongs to the second preset range, the target defect is determined to be an etching morphology defect.

[0049] In addition to large-sized defects in dark field, the second defect type may also include other types of defects that can be detected in a dark field environment, such as particles, scratches, and surface protrusion defects; in addition to large-sized defects in bright field, the first defect type may also include other types of defects that can be detected in a bright field environment, such as step-shaped defects. For other types of defects, if the size of a defect in a bright field environment falls within the first preset range, and the defect is not detected at the same position in a dark field environment, the defect is determined to be a gentle slope defect; if the size of a defect in a bright field environment does not fall within the first preset range, and the defect is not detected at the same position in a dark field environment, the defect is determined to be a step-shaped defect. If the size of a defect in a dark field environment belongs to the second preset range, and the defect is not detected at the same position in a bright field environment, the defect is determined to be a wide scratch or a large-area surface protrusion defect; if the size of a defect in a dark field environment belongs to the third preset range, and the defect is not detected at the same position in a bright field environment, the defect is determined to be a narrow scratch or a small-area surface protrusion defect; if the size of a defect in a dark field environment belongs to the fourth preset range, and the defect is not detected at the same position in a bright field environment, the defect is determined to be a particle. Among them, any value in the wide range in the third preset range is smaller than any value in the wide range in the second preset range, any value in the wide range in the fourth preset range is smaller than any value in the wide range in the second preset range in the third preset range, and any value in the long range is smaller than any value in the long range in the second preset range.

[0050] After determining the target defect type of the target defect, the wafers to be tested can be classified according to the target defect type. For defect types that cannot be cleaned or repaired, they are marked as unqualified, for minor defect types, they are marked as qualified, and for repairable defect types, they are marked as to be repaired. In addition, the defect distribution in each wafer to be tested can be counted. If the defect is systematically distributed and reappears in a specific area, this may indicate that there is a problem with a specific process and the process needs to be adjusted in a timely manner.

[0051] Therefore, small and randomly distributed defects may have little impact on the overall performance, while large and systematically distributed defects may seriously affect the performance of the wafer. According to the size, shape and distribution of the defects, the impact of the defects on the wafer to be tested is determined, and those with a large impact need to be repaired.

[0052] In some embodiments, the bright field image and the dark field image are input into the defect classification model, and the defect type included in the wafer to be tested is output. The defect classification model is used to classify the defect type according to the size of the defect marked by the bright field image and the dark field image. In this way, the judgment criteria of etching morphology defects can be adaptively changed through the defect classification model to improve the accuracy of detecting etching morphology defects.

[0053] In an exemplary embodiment of the present disclosure, the above defect classification model is obtained by training multiple sample data, each of which includes defect size, defect location and defect type. Specifically, the defect classification model extracts features from defects marked in bright field images and dark field images, including location and size, and then determines the defect type included on the wafer surface based on the extracted features. Defect types include cracks, scratches, particles, surface protrusion defects, step defects and etching morphology defects. Figure 4 As shown in the figure, the morphology of some defect types under a scanning electron microscope, including step defects, etching morphology defects, scratches, surface protrusion defects and particles. The white line segments in the figure are scales. The length of each line segment represented in the figure actually represents the length of the corresponding mark on the line segment. For example, in the image of etching morphology defects, the white line segment indicates that the actual length is 25 microns.

[0054] In order to further improve the accuracy of the defect classification model, in some embodiments, a defect database is established to collect bright field images, dark field images of defective wafers and corresponding defect types and locations for continuous optimization of the defect classification model and improving the accuracy of defect identification.

[0055] In this way, the wafer surface defect detection method provided by the present disclosure determines the target defect type of the target defect at the same position on the surface of the wafer to be tested according to the sizes of different defect types in the bright field image and the dark field image, thereby improving the detection accuracy. In addition, for gentle slope defects, since the scattered light of the gentle slope is weak and cannot be detected by dark field scattering, the combined detection results of the bright field image and the dark field image can also avoid the gentle slope defects from being judged as etching morphology defects. Therefore, compared with the single light field detection method, this solution greatly improves the detection accuracy.

[0056] In some embodiments, in combination Figure 2 ,like Figure 5 As shown, the above step S201 obtains image information of the surface of the wafer to be measured under different light fields, which can be specifically implemented through the following steps S201a and S201d.

[0057] In step S201a, the direct wavelength of the direct light is determined according to the defect depth range corresponding to the defect type to be detected.

[0058] In step S201b, direct light of a direct wavelength is used to illuminate the surface of the wafer to be tested, and a bright field image is acquired.

[0059] In step S201c, the oblique angle and the oblique wavelength of the oblique light are determined according to the defect size range corresponding to the defect type to be detected.

[0060] In step S201d, the surface of the wafer to be tested is illuminated by oblique light of an oblique wavelength and an oblique angle, and a dark field image is acquired.

[0061] Among them, the defect types to be detected include: etching morphology defects, gentle slope defects, step defects, wide scratches, large-area surface protrusion defects, narrow scratches, small-area surface protrusion defects, particles, etc. The target defect type is one of the defect types to be detected.

[0062] The depth ranges corresponding to different defect types to be detected (the difference between the maximum distance and the minimum distance from the wafer surface at each position in the defect area) may be the same or different. For small defects such as particles and scratches, the depth is usually shallow; for larger etched morphology defects, step-shaped defects, etc., the depth is usually deep. According to the depth range corresponding to the defect type, a specific wavelength of light is selected to enhance the contrast of a specific type of defect, so as to detect the specific defect type on the surface of the wafer to be tested. This is because different wavelengths of light interact differently with materials and can highlight different surface features. For example, ultraviolet light is electromagnetic radiation with a wavelength of 10nm to 400nm. Ultraviolet light can be absorbed by many materials. Since ultraviolet light has a shorter wavelength than visible light, it can be scattered by defects on the surface of the wafer to be tested. It is suitable for detecting shallow defects: such as narrow scratches, small-area surface protrusion defects or particles on the surface of the wafer. However, ultraviolet light can penetrate materials, and deep defects, such as etched morphology defects, will scatter and absorb ultraviolet light, causing the intensity and distribution of the transmitted ultraviolet light to change. Therefore, ultraviolet light is suitable for detecting deep defect types. The correspondence between the specific wavelength and the defect type is determined according to the actual situation. The wavelength of light can be roughly divided into ultraviolet and infrared. Ultraviolet can be further divided into more detailed categories, such as deep ultraviolet and extreme ultraviolet, etc., which are not limited in this disclosure.

[0063] The size ranges corresponding to different defect types may be the same or different. For the same irradiation angle, the imaging quality of defects in different size ranges is different. Therefore, the appropriate irradiation angle is determined according to the size range. The angle between the incident angle and the normal of the oblique light (oblique angle) is divided into two levels, namely the low angle range and the high angle range. Among them, any angle in the low angle range is greater than any angle in the high angle range. For example, the low angle range is the angle between the incident angle and the normal greater than 45 degrees and less than or equal to 90 degrees, and the high angle range is the angle between the incident angle and the normal greater than 0 degrees and less than or equal to 45 degrees. Different oblique angles have different detection sensitivities for different defect types. The high angle range is suitable for detecting larger or deeper defects, such as etching morphology defects. This angle can highlight the contour of the object and the surface convexity changes. Light irradiation in the low angle range can reduce the interference of reflected light, making the defects more obvious, and is suitable for detecting smaller surface defects, such as narrow scratches, small-area surface protrusion defects or particles.

[0064] It should be noted that the purpose of angle adjustment is to make the incident light as parallel to the normal of the defective surface as possible, so that the defective surface reflects more scattered light, thereby improving the imaging quality. The above-mentioned adjustment of the angle of the incident light according to the size is also to make the incident light as parallel to the normal of the defective surface as possible.

[0065] In summary, for larger or deeper defects, high-angle illumination and longer wavelengths are used to enhance contrast, and for small defects, low-angle illumination and ultraviolet light can highlight these small defects and enhance their visibility. In this way, for different defect types, light fields with different wavelengths and illumination angles are used to make the defects in the obtained image clearer and more accurate, thereby making the defect type determination more accurate.

[0066] Based on the same concept as the above-mentioned wafer surface defect detection method, the present disclosure also provides a wafer surface defect detection device, such as Figure 6 As shown, the wafer surface defect detection device 60 includes: an acquisition part 601 and a determination part 602; the acquisition part 601 is configured to acquire a bright field image and a dark field image of the surface of the wafer to be tested, and to acquire a first size in the bright field image and a second size in the dark field image of a target defect at the same position in the bright field image and the dark field image; the determination part 602 is configured to determine a target defect type of the target defect based on the first size and the second size.

[0067] In some embodiments, the determination part 602 is specifically configured to determine a first defect type corresponding to the target defect in the bright field image according to the first size; determine a second defect type corresponding to the target defect in the dark field image according to the second size; and determine the target defect type according to the first defect type and the second defect type.

[0068] In some embodiments, the determining part 602 is specifically configured to determine that the target defect type is an etching morphology defect when the first defect type is a bright field large-size defect and the second defect type is a dark field large-size defect.

[0069] In some embodiments, the determination part 602 is specifically configured to determine that a first defect type corresponding to the target defect in the bright field image is a large-size bright field defect when the first size falls within a first preset range; and determine a second defect type corresponding to the target defect in the dark field image according to the second size, including: when the second size falls within a second preset range, determining that the second type of defect corresponding to the target defect in the dark field image is a large-size dark field defect.

[0070] In some embodiments, the acquisition part 601 is also configured to acquire a first area corresponding to each defect in the dark field image on the wafer to be tested, and a second area corresponding to each defect in the bright field image on the wafer to be tested; the determination part 602 is also configured to determine the overlapping area between the first area and the second area, and take the defect covering the overlapping area as the target defect.

[0071] In some embodiments, the acquisition part 601 is specifically configured to determine the direct wavelength of the direct light according to the defect depth range corresponding to the defect type to be detected; use the direct light of the direct wavelength to illuminate the surface of the wafer to be tested, and acquire a bright field image.

[0072] In some embodiments, the acquisition part 601 is specifically configured to determine the oblique angle and oblique wavelength of the oblique light according to the defect size range corresponding to the defect type to be detected; use the oblique light with the oblique wavelength and oblique angle to illuminate the surface of the wafer to be tested, and acquire a dark field image.

[0073] In some embodiments, the acquisition part 601 is specifically configured to collect bright field illumination images in a bright field environment and dark field illumination images in a dark field environment; preprocess the bright field illumination images and the dark field illumination images to obtain preprocessed bright field illumination images and preprocessed dark field illumination images; mark defects in the preprocessed bright field illumination images and the preprocessed dark field illumination images through edge detection algorithms and morphological operations to obtain bright field images and dark field images.

[0074] In the embodiments of the present application, each module can implement the wafer surface defect detection method provided in the above method embodiments and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0075] Please refer to Figure 7, which shows a structural block diagram of an electronic device provided by an exemplary embodiment of the present disclosure. In some examples, the electronic device may be at least one of a smart phone, a smart watch, a desktop computer, a laptop, a virtual reality terminal, an augmented reality terminal, a wireless terminal, and a laptop computer. The electronic device has a communication function and can access a wired network or a wireless network. The electronic device may generally refer to one of a plurality of terminals, and those skilled in the art may know that the number of the above terminals may be more or less. It can be understood that the electronic device undertakes the calculation and processing work of the technical solution of the present disclosure, and the present disclosure does not limit this.

[0076] like Figure 7 As shown, the electronic device in the present disclosure may include one or more of the following components: a processor 710 and a memory 720 .

[0077] Optionally, the processor 710 uses various interfaces and lines to connect various parts of the entire electronic device, and executes various functions of the electronic device and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 720, and calling data stored in the memory 720. Optionally, the processor 710 can be implemented in at least one hardware form of digital signal processing (DSP), field programmable gate array (FPGA), and programmable logic array (PLA). The processor 710 can integrate one or a combination of a central processing unit (CPU), a graphics processing unit (GPU), a neural network processor (NPU), and a baseband chip. Among them, the CPU mainly processes the operating system, user interface, and application programs; the GPU is responsible for rendering and drawing the content that needs to be displayed on the touch display; the NPU is used to implement artificial intelligence (AI) functions; and the baseband chip is used to process wireless communications. It is understandable that the above baseband chip may not be integrated into the processor 710, but may be implemented by a separate chip.

[0078] The memory 720 may include a random access memory (RAM) or a read-only memory (ROM). Optionally, the memory 720 includes a non-transitory computer-readable storage medium. The memory 720 may be used to store instructions, programs, codes, code sets, or instruction sets. The memory 720 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above various method embodiments, etc.; the data storage area may store data created according to the use of the electronic device, etc.

[0079] In addition, those skilled in the art can understand that the structure of the electronic device shown in the above drawings does not constitute a limitation on the electronic device, and the electronic device may include more or fewer components than shown, or combine certain components, or arrange the components differently. For example, the electronic device also includes a display screen, a camera assembly, a microphone, a speaker, a radio frequency circuit, an input unit, a sensor (such as an acceleration sensor, an angular velocity sensor, a light sensor, etc.), an audio circuit, a WiFi module, a power supply, a Bluetooth module and other components, which will not be described in detail here.

[0080] The present disclosure also provides a computer-readable storage medium storing at least one instruction, wherein the at least one instruction is used to be executed by a processor to implement the wafer surface defect detection method as described in the above embodiments.

[0081] The present disclosure also provides a computer program product, which includes computer instructions, which are stored in a computer-readable storage medium; a processor of an electronic device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the electronic device executes to implement the wafer surface defect detection method described in the above-mentioned embodiments.

[0082] An embodiment of the present application further provides a chip, which includes a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run programs or instructions to implement the various processes of the above-mentioned wafer surface defect detection method embodiment, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0083] It should be understood that the chip mentioned in the embodiments of the present application can also be called a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.

[0084] In the several embodiments provided in the present disclosure, it should be understood that the disclosed systems, devices, servers and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0085] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0086] In addition, each functional unit in each embodiment of the present disclosure may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0087] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program code.

[0088] Those skilled in the art should be aware that in one or more of the above examples, the functions described in the present disclosure can be implemented using hardware, software, firmware, or any combination thereof. When implemented using software, these functions can be stored in a computer-readable medium or transmitted as one or more instructions or codes on a computer-readable medium. Computer-readable media include computer storage media and communication media, wherein communication media include any media that facilitates the transmission of computer programs from one place to another. Storage media can be any available media that can be accessed by a general or special-purpose computer.

[0089] It should be noted that the technical solutions described in the present disclosure can be combined arbitrarily without conflict.

[0090] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by a technician familiar with the technical field within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention.

Claims

1. A wafer surface defect detection method, characterized in that: The wafer surface defect detection method comprises: Acquire bright field images and dark field images of the surface of the wafer to be tested; Acquire a first size of a target defect at the same position in the bright field image and the dark field image in the bright field image, and a second size of the target defect in the dark field image; A target defect type of the target defect is determined according to the first size and the second size.

2. The wafer surface defect detection method according to claim 1, characterized in that: Determining the target defect type of the target defect according to the first size and the second size includes: Determining a first defect type corresponding to the target defect in the bright field image according to the first size; Determining, according to the second size, a second defect type corresponding to the target defect in the dark field image; The target defect type is determined according to the first defect type and the second defect type.

3. The wafer surface defect detection method according to claim 2, characterized in that: The first defect type includes bright field large-size defects, and the second defect type includes dark field large-size defects; and determining the target defect type according to the first defect type and the second defect type includes: When the first defect type is a bright field large-size defect and the second defect type is a dark field large-size defect, the target defect type is determined to be an etching morphology defect.

4. The wafer surface defect detection method according to claim 3, characterized in that: The determining, according to the first size, a first defect type corresponding to the target defect in the bright field image includes: When the first size falls within a first preset range, determining that a first defect type corresponding to the target defect in the bright field image is a bright field large-size defect; The determining, according to the second size, a second defect type corresponding to the target defect in the dark field image includes: When the second size belongs to a second preset range, it is determined that the second type of defect corresponding to the target defect in the dark field image is a dark field large-size defect.

5. The wafer surface defect detection method according to claim 1, characterized in that: The wafer surface defect detection method further includes: Acquire a first region on the wafer to be tested corresponding to each defect in the dark field image, and a second region on the wafer to be tested corresponding to each defect in the bright field image; An overlapping area between the first area and the second area is determined, and a defect covering the overlapping area is used as the target defect.

6. The wafer surface defect detection method according to claim 1, characterized in that: The step of obtaining a bright field image of the surface of the wafer to be tested comprises: Determine the direct wavelength of the direct light according to the defect depth range corresponding to the defect type to be detected; The surface of the wafer to be tested is illuminated by direct light of the direct wavelength, and the bright field image is acquired.

7. The wafer surface defect detection method according to any one of claims 1 to 6, characterized in that: The step of obtaining a dark field image of the surface of the wafer to be tested comprises: Determine the oblique angle and wavelength of the oblique light according to the defect size range corresponding to the defect type to be detected; The oblique light of the oblique wavelength and the oblique angle is used to illuminate the surface of the wafer to be tested, and the dark field image is acquired.

8. The wafer surface defect detection method according to any one of claims 1 to 6, characterized in that: The step of obtaining a bright field image and a dark field image of the surface of the wafer to be tested comprises: Collect bright field illumination images in a bright field environment, and dark field illumination images in a dark field environment; Preprocessing the bright field illumination image and the dark field illumination image to obtain a preprocessed bright field illumination image and a preprocessed dark field illumination image; By using edge detection algorithm and morphological operation, defects in the preprocessed bright field illumination image and the preprocessed dark field illumination image are marked to obtain a bright field image and a dark field image.

9. A wafer surface defect detection device, characterized in that: The wafer surface defect detection device comprises: An acquisition part is configured to acquire a bright field image and a dark field image of the surface of the wafer to be tested, and to acquire a first size of a target defect at the same position in the bright field image and the dark field image in the bright field image, and a second size in the dark field image; The determining part is configured to determine a target defect type of the target defect according to the first size and the second size.

10. An electronic device, characterized in that: It includes a processor, a memory, and a program or instruction stored in the memory and executable on the processor, wherein the program or instruction, when executed by the processor, implements the steps of the wafer surface defect detection method as described in any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that: The readable storage medium stores programs or instructions, and when the programs or instructions are executed by the processor, the steps of the wafer surface defect detection method as described in any one of claims 1 to 8 are implemented.

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