Defect Detection Method, Device, Detection Equipment and Storage Medium for Semiconductor Structure

Abstract

Embodiments of the present application provide a method, apparatus, detection device, and storage medium for detecting defects in a semiconductor structure. In some embodiments, the method for detecting defects in a semiconductor structure includes: identifying convex points on the boundary contour of a channel hole in a to-be-detected image of the semiconductor structure; determining an offset distance between the convex point with the largest protrusion degree and its corresponding reference point; and determining the defect degree of the channel hole based on the determined offset distance. The method, apparatus, detection device, and storage medium for detecting defects in a semiconductor structure provided by the embodiments of the present application can detect defects in the channel holes of the semiconductor structure.

Description

Technical Field

[0001] Embodiments of the present application relate to the field of semiconductor technology, and more particularly, to a method, apparatus, detection device, and storage medium for detecting defects in a semiconductor structure. Background Art

[0002] In current three-dimensional memories, a stacked three-dimensional memory structure is usually achieved by vertically stacking multiple layers of data storage units. To obtain the above-mentioned stacked three-dimensional memory structure, a stacked structure needs to be formed on a silicon substrate, and the stacked structure is etched to form a channel hole. Further deposition and etching are performed to form a channel structure covering the inner wall of the channel hole, and then a semiconductor layer is filled to form a channel structure located in the channel hole.

[0003] As the number of stacked layers increases, the etched channel holes may have etching defects, resulting in sharp corners in the channel holes, which affects the performance of the channel structure. However, there is currently no relevant detection method for the above-mentioned etching defects, which seriously affects the performance of the finally prepared memory structure. Summary of the Invention

[0004] In a first aspect, embodiments of the present application provide a method for detecting defects in a semiconductor structure, including: identifying convex points on the boundary contour of a channel hole in a to-be-tested image of the semiconductor structure; determining an offset distance between the convex point with the largest protrusion degree and its corresponding reference point; and determining the defect degree of the channel hole according to the determined offset distance.

[0005] In some illustrative embodiments of the present application, determining the offset distance between the convex point with the largest protrusion degree and its corresponding reference point includes: determining the convex point with the largest protrusion degree from the identified convex points; and determining the offset distance between the convex point with the largest protrusion degree and its corresponding reference point.

[0006] In some illustrative embodiments of the present application, determining the convex point with the largest protrusion degree from the identified convex points includes: identifying concave points on the boundary contour of the channel hole; determining the perpendicular distance from each concave point to the line connecting the two adjacent convex points to the concave point, and determining a first concave point with the largest perpendicular distance between the adjacent two convex points from the concave points; and determining the convex point with the largest protrusion degree from the two convex points adjacent to the first concave point.

[0007] In some illustrative embodiments of the present application, determining the convex point with the largest protrusion degree from the two convex points adjacent to the first concave point includes: determining the convex point with the largest distance from the first concave point among the two adjacent convex points as the convex point with the largest protrusion degree.

[0008] In some illustrative embodiments of the present application, the reference point corresponding to the convex point with the largest protrusion degree is the first concave point.

[0009] In some illustrative embodiments of the present application, determining the offset distance between the bump with the largest protrusion degree and its corresponding reference point includes: determining the offset distance between each identified bump and its corresponding reference point; and taking the maximum value among all the offset distances as the offset distance between the bump with the largest protrusion degree and its reference point.

[0010] In some illustrative embodiments of the present application, the method further includes: identifying the concave points of the boundary contour of the channel hole; wherein, the reference point includes the concave point adjacent to the bump.

[0011] In some illustrative embodiments of the present application, the offset distance between the bump with the largest protrusion degree and its corresponding reference point includes: the distance between the bump with the largest protrusion degree and its corresponding reference point in a specified direction, wherein the specified direction is perpendicular to the extending direction of the gate slit of the semiconductor structure.

[0012] In some illustrative embodiments of the present application, the bump or the concave point is an extreme point in the boundary contour of the channel hole.

[0013] In some illustrative embodiments of the present application, before identifying the bump, the method further includes: extracting the contour in the image to be measured; and performing noise reduction processing on the extracted contour to remove the part of the contour far from the boundary contour of the channel hole.

[0014] In some illustrative embodiments of the present application, the method further includes: in response to the defect degree of the channel hole not meeting the preset requirement, executing an alarm instruction.

[0015] In some illustrative embodiments of the present application, the image to be measured includes a scanning electron microscope image of the channel hole in the extending direction of the channel hole.

[0016] In some illustrative embodiments of the present application, the semiconductor structure is a three-dimensional memory or a part of a three-dimensional memory.

[0017] In a second aspect, an embodiment of the present application provides a defect detection device for a semiconductor structure, including: an identification module, configured to identify the bumps of the boundary contour of the channel hole in the image to be measured of the semiconductor structure; a determination module, configured to determine the offset distance between the bump with the largest protrusion degree and its corresponding reference point; and a detection module, configured to determine the defect degree of the channel hole according to the determined offset distance.

[0018] In some illustrative embodiments of the present application, the determination module is configured to: determine the bump with the largest protrusion degree from the identified bumps; and determine the offset distance between the bump with the largest protrusion degree and its corresponding reference point.

[0019] In some exemplary embodiments of the present application, the determination module is further configured to: identify the concave points of the boundary contour of the channel hole; determine the vertical distance from each concave point to the line connecting two convex points adjacent to the concave point, and determine the first concave point with the largest vertical distance from the two adjacent convex points from the concave points; and determine the convex point with the largest protrusion degree from the two convex points adjacent to the first concave point.

[0020] In some exemplary embodiments of the present application, the reference point corresponding to the convex point with the greatest protrusion degree is the first concave point.

[0021] In some exemplary embodiments of the present application, the determination module is configured to: determine the offset distance between each identified salient point and its corresponding reference point; and take the maximum value of all offset distances as the offset distance between the salient point with the greatest protrusion and its corresponding reference point.

[0022] In some exemplary embodiments of the present application, the recognition module is further configured to: identify concave points of a boundary contour of the channel hole; wherein the reference point includes a concave point adjacent to a convex point.

[0023] In some exemplary embodiments of the present application, the offset distance between the most protruding bump and its corresponding reference point includes: the distance between the most protruding bump and its corresponding reference point in a specified direction, wherein the specified direction is perpendicular to the extension direction of the gate gap of the semiconductor structure.

[0024] In some exemplary embodiments of the present application, the semiconductor structure is a three-dimensional memory or a part of a three-dimensional memory.

[0025] In a third aspect, an embodiment of the present application provides a detection device, comprising: a memory for storing computer instructions; and a processor for communicating with the memory to execute the computer instructions, thereby implementing the defect detection method mentioned in the above embodiment.

[0026] In a fourth aspect, an embodiment of the present application provides a readable storage medium, in which computer instructions are stored. When the computer instructions are executed by a processor, the defect detection method mentioned in the above embodiment is implemented.

[0027] According to the embodiments of the present application, the image to be tested of the semiconductor structure can be identified to obtain the offset distance between the most protruding point and its corresponding reference point to measure the degree of defect in the channel hole, so that the defects in the channel hole of the semiconductor structure can be automatically detected. Compared with manual defect assessment, the evaluation results of defects based on the offset distance are more objective and the cost of defect assessment is lower. In addition, the detection of channel hole defects ensures the performance of the final semiconductor structure. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Other features, objects, and advantages of the present application will become more apparent by reading the detailed description of non-limiting embodiments with reference to the following drawings. Among them:

[0029] Figure 1 is a schematic flow chart of a method for defect detection of a semiconductor structure according to an embodiment of the present application;

[0030] Figures 2a to 2d is a partial schematic view of a scanning electron microscope image of a three-dimensional memory according to an embodiment of the present application;

[0031] Figure 3 is a schematic view of a partial boundary contour of a channel hole according to an embodiment of the present application;

[0032] Figure 4 is Figure 2a a schematic view of the positions of the convex point with the maximum degree of protrusion and the first concave point of some of the channel holes in

[0033] Figure 5 is a schematic block diagram of a device for defect detection of a semiconductor structure according to an embodiment of the present application;

[0034] Figure 6 is a block diagram of a detection device according to an embodiment of the present application. Detailed Embodiments

[0035] To better understand the present application, more detailed descriptions of various aspects of the present application will be made with reference to the drawings. It should be understood that these detailed descriptions are only descriptions of exemplary embodiments of the present application and do not limit the scope of the present application in any way. Throughout the specification, the same reference numerals refer to the same elements. The expression "and / or" includes any and all combinations of one or more of the associated listed items.

[0036] It should be noted that in this specification, the expressions such as first and second are only used to separate one feature from another feature region and do not represent any limitation on the feature, especially not any order. Therefore, without departing from the teachings of the present application, the first concave point discussed in the present application may also be referred to as the second concave point, and vice versa.

[0037] In the drawings, the drawings are only examples and are not drawn to scale strictly. As used herein, the terms "substantially" and similar terms are used as approximate terms and not as terms of degree, and are intended to illustrate the inherent deviations in measured or calculated values that will be recognized by those of ordinary skill in the art.

[0038] It should also be understood that expressions such as "including", "comprising", "having", "containing" and / or "comprising of" are open rather than closed expressions in this specification, which means that the stated features, elements and / or components exist, but do not exclude the existence of one or more other features, elements, components and / or their combinations. In addition, when describing the embodiments of the present application, the use of "may" means "one or more embodiments of the present application". And the term "exemplary" is intended to refer to an example or illustration.

[0039] Unless otherwise defined, all terms used herein (including engineering terms and scientific and technical terms) have the same meaning as commonly understood by those of ordinary skill in the art to which this application belongs. It should also be understood that unless clearly stated in this application, words defined in common dictionaries should be interpreted as having a meaning consistent with their meaning in the context of the relevant art, and should not be interpreted in an idealized or overly formal sense.

[0040] It should be noted that, without conflict, the embodiments in this application and the features in the embodiments can be combined with each other. In addition, unless clearly defined or in contradiction with the context, the specific steps included in the methods described in this application do not have to be limited to the recorded order, but can be executed in any order or executed in parallel. The present application will be described in detail below with reference to the drawings and in conjunction with the embodiments.

[0041] Figure 1 is a schematic flow chart of a defect detection method 1000 for a semiconductor structure according to an embodiment of the present application. This defect detection method can be executed, for example, by a defect detection device. As Figure 1 shown, the defect detection method 1000 for a semiconductor structure can, for example, include the following steps:

[0042] S11, identifying the convex points of the boundary contour of the channel holes in the image to be measured of the semiconductor structure.

[0043] S12, determining the offset distance between the convex point with the largest degree of protrusion and its corresponding reference point.

[0044] S13, determining the defect degree of the channel holes according to the determined offset distance.

[0045] According to this embodiment, by identifying the image to be measured of the semiconductor structure, the offset distance between the convex point with the largest degree of protrusion and its corresponding reference point can be obtained to measure the defect degree of the channel holes, so that the defects of the channel holes of the semiconductor structure can be automatically detected. Based on the offset distance to evaluate the defects, compared with the manual evaluation of defects, the evaluation result is more objective and the cost of evaluating defects is lower. In addition, detecting the defects of the channel holes ensures the performance of the finally formed semiconductor structure.

[0046] The following will, in conjunction with Figures 2a to 4 give an example description of each step of the above-mentioned defect detection method 1000.

[0047] Step S11

[0048] In some embodiments of the present application, before step S11, the defect detection method 1000 may further, for example, include: obtaining the boundary contour of the channel hole of the semiconductor structure. The step of obtaining the boundary contour of the channel hole may, for example, include: extracting the contour in the image to be measured; and performing noise reduction processing on the extracted contour to remove the part of the contour that is far from the boundary contour of the channel hole. Exemplarily, considering that the channel hole is generally close to a preset regular shape (such as a circle or an ellipse), the contour in the extracted contour that is close to the shape of the channel hole can be used as the boundary contour of the channel hole.

[0049] As an option, the image to be measured may, for example, include a scanning electron microscope image of the channel hole in the extending direction of the channel hole. For example, the defect detection device can obtain the scanning electron microscope image scanned by the scanning electron microscope from the stacking direction of the stacked structure of the semiconductor structure. Among them, the scanning electron microscope can scan the semiconductor structure after forming the channel hole to obtain the image to be measured, or can scan the semiconductor structure after forming the channel structure to obtain the image to be measured, and the present application does not limit this.

[0050] In some embodiments of the present application, the extreme points in the boundary contour of the channel hole can be identified as convex points or concave points, that is, the convex points or concave points are the extreme points in the boundary contour of the channel hole. Among them, the concave point refers to the extreme point that is recessed inward in the boundary contour, and the convex point refers to the extreme point that protrudes outward in the boundary contour. The extreme points may, for example, include the inflection points on the boundary contour of the channel hole.

[0051] The above-mentioned semiconductor structure may, for example, be a three-dimensional memory or a part of a three-dimensional memory. Exemplarily, Figures 2a to 2d is a partial schematic diagram of a scanning electron microscope image of a three-dimensional memory according to an embodiment of the present application. As Figure 2a shown, the three-dimensional memory may, for example, include: a stacked structure, a channel hole 100, and a gate gap 200. The stacked structure may, for example, include alternately stacked gate layers (not shown) and insulating layers (not shown). The channel hole 100 may, for example, penetrate the stacked structure along the stacking direction of the stacked structure and be substantially perpendicular to the stacked structure. The gate gap 200 may, for example, extend in a direction perpendicular to the stacking direction of the stacked structure (its extending direction may, for example, Figure 2a be the x direction in Figure 2a ), be substantially perpendicular to the stacked structure, and be formed between adjacent channel holes 100. The defect detection device can extract the contour in the image to be measured through a contour extraction algorithm. For example, the contour extracted based on Figure 2bAs shown. The extracted contour may include, for example, the boundary contour (e.g., 110) of the channel hole 100 in the image to be measured, the boundary contour (e.g., 210) of the gate slit 200, and the contour of some noise points in the scanning electron microscope image. The defect detection device may perform noise reduction processing on the extracted contour to remove the part (such as the contour of the noise points) in the extracted contour that is far from the boundary contour 110 of the channel hole, so as to obtain the boundary contour of the channel hole 100, as Figure 2c shown. The extreme points of the boundary contour of the channel hole 100 can be detected by the defect detection device / detection equipment further described below. For example, Figure 2c the extreme points of the boundary contour of a channel hole 100 in Figure 2d can be, for example, as shown by each white dot in

[0052] Step S12

[0053] In one embodiment of the present application, determining the offset distance between the convex point with the largest convexity degree and its corresponding reference point may include: determining the convex point with the largest convexity degree from the identified convex points; determining the offset distance between the convex point with the largest convexity degree and its corresponding reference point. In other words, the defect detection device may first determine the convex point with the largest convexity degree, and then determine the offset distance between the convex point with the largest convexity degree and its corresponding reference point.

[0054] As an option, the step of determining the convex point with the largest convexity degree from the identified convex points may include: identifying the concave points of the boundary contour of the channel hole; determining the vertical distance from each concave point to the line connecting the two adjacent convex points, and determining the first concave point with the largest vertical distance between the two adjacent convex points from the concave points; determining the convex point with the largest convexity degree from the two convex points adjacent to the first concave point. Among them, identifying the concave points of the boundary contour of the channel hole may refer to the relevant content of identifying the convex points of the boundary contour of the channel hole, which will not be elaborated here.

[0055] Exemplarily, a partial boundary contour of the channel hole may be, for example Figure 3 as shown. The boundary contour of this part of the channel hole includes a concave point (A1) and convex points (B1 and B2), and the vertical distance from the concave point (A1) to the line connecting the two adjacent convex points (B1 and B2) is d.

[0056] As an example, the defect detection device may, for example, determine the convex point with the largest convexity degree from the two adjacent convex points that is the farthest from the first concave point in the specified direction, and the specified direction is perpendicular to the extension direction of the gate slit of the semiconductor structure.

[0057] It should be understood that, without departing from the teachings of the present application, one of the two adjacent bumps can also be selected as the bump with the largest protrusion degree based on other rules, and the present application does not limit this.

[0058] It should be understood that, without departing from the teachings of the present application, the bump with the largest protrusion degree can also be determined by other means, and the present application does not limit this.

[0059] In some embodiments of the present application, after determining the bump with the largest protrusion degree, the defect detection device determines the reference point corresponding to the bump with the largest protrusion degree, and the determination method may include but is not limited to:

[0060] Method 1: The defect detection device may, for example, use the first concave point as the reference point corresponding to the bump with the largest protrusion degree, that is, the reference point corresponding to the bump with the largest protrusion degree is the first concave point.

[0061] Method 2: The defect detection device may, for example, use one or both of the two concave points adjacent to the bump with the largest protrusion degree as the reference point corresponding to the bump with the largest protrusion degree, that is, the reference point corresponding to the bump with the largest protrusion degree is the concave point adjacent to the bump with the largest protrusion degree. By way of example, the defect detection device can arbitrarily select an adjacent concave point as the reference point, or can select a concave point from the two adjacent concave points based on a preset selection rule, or the defect detection device can use both of the two adjacent concave points as the reference points and respectively determine the offset distances between the bump with the largest protrusion degree and the two adjacent concave points.

[0062] It should be understood that, without departing from the teachings of the present application, other points of the channel hole can also be selected as the reference point corresponding to the bump with the largest protrusion degree, and the present application does not limit this.

[0063] In some other embodiments of the present application, determining the offset distance between the bump with the largest protrusion degree and its corresponding reference point may include, for example: determining the offset distances between each identified bump and its corresponding reference point; using the maximum value among all the offset distances as the offset distance between the bump with the largest protrusion degree and its corresponding reference point. In other words, the defect detection device can first determine the offset distances between each identified bump and its corresponding reference point, and then select the maximum value among all the offset distances as the offset distance between the reference points corresponding to the bump with the largest protrusion degree. Among them, the reference point may include, for example, the concave point adjacent to the bump, and the specific determination process can refer to the relevant description above about the reference point corresponding to the bump with the largest protrusion degree, and will not be elaborated here.

[0064] In some embodiments of the present application, the offset distance between the bump with the greatest degree of protrusion and its corresponding reference point includes: the distance h (see Figures 2a to 2d , Figure 3 ) in the y-direction of the bump with the greatest degree of protrusion and its corresponding reference point in a specified direction (see the y-direction in Figure 3 ), where the specified direction is perpendicular to the extending direction of the gate slot of the semiconductor structure (see the x-direction in Figures 2a to 2d , Figure 3 ). Since the formed channel holes usually deform in the direction close to the gate slot to form cusp defects, the distance between the bump with the greatest degree of protrusion and its corresponding reference point in the direction perpendicular to the extending direction of the gate slot can be selected to measure the defect degree of the channel holes, making the measurement result more accurate.

[0065] Exemplarily, Figure 4 is Figure 2a a schematic diagram of the bump with the greatest degree of protrusion and the first concave point of a partial channel hole 100 in Figure 4 . As shown in Figure 2a , the first concave points corresponding to the partial channel holes 100 in

[0066] are respectively: P1, P2, P3, P4, and P5, and the corresponding bumps with the greatest degree of protrusion are respectively: Q1, Q2, Q3, Q4, and Q5. The offset distances between the bumps with the greatest degree of protrusion of each channel hole 100 and their corresponding reference points are respectively: the distance between P1 and Q1 in the y-direction, the distance between P2 and Q2 in the y-direction, the distance between P3 and Q3 in the y-direction, the distance between P4 and Q4 in the y-direction, and the distance between P5 and Q5 in the y-direction.

[0067] Step 13

[0068] It should be understood that without departing from the teachings of the present application, the offset distance between the bump with the greatest degree of protrusion and its corresponding reference point can be, for example, other distances between the two points, such as the straight-line distance between the bump with the greatest degree of protrusion and its corresponding reference point. The present application does not limit this.

[0069] It should be understood that without departing from the teachings of the present application, the defect detection device can also, for example, detect other defects of the channel holes. The present application does not limit this.

[0070] In some embodiments of the present application, the defect detection device can directly determine the defect degree of the channel hole according to the determined offset distance. In other words, the defect detection device can use the determined offset distance as a parameter to measure the defect degree of the boundary of the channel hole.

[0071] As an example, the defect detection device can perform qualitative analysis on the defect degree of the channel hole according to the determined offset distance. For example, the defect detection device determines whether the defect degree of the channel hole is serious based on the magnitude of the determined offset distance, and whether there are sharp points in the boundary contour of the channel hole. For example, if the offset distance is greater than the distance threshold, it is determined that the defect degree of the channel hole is a serious defect or a defective one; if the offset distance is less than the distance threshold, it is determined that the defect degree of the channel hole is a minor defect or no defect.

[0072] As another example, the defect detection device can perform quantitative analysis on the defect degree of the channel hole according to the determined offset distance. For example, the defect detection device can perform quantitative analysis on the defect degree of the channel hole according to the mapping relationship (such as a functional relationship) between the preset offset distance and the defect degree value.

[0073] It should be understood that without departing from the teachings of the present application, the mapping relationship between the offset distance and the defect degree value can be set according to experience or the influence of the sharp corner defect of the channel hole on the performance of the semiconductor device, and the present application does not limit this.

[0074] In some embodiments of the present application, the defect detection device can determine other parameters according to the determined offset distance, and then determine the defect degree of the channel hole based on the other parameters. In other words, the defect detection device can use the other parameters determined based on the determined offset distance as parameters to measure the defect degree of the channel hole. For example, the reference point can be, for example, the first concave point mentioned above. Determining the defect degree of the channel hole according to the determined offset distance can include, for example: calculating the offset angle of the convex point with the maximum protrusion degree relative to the reference point according to the determined offset distance; determining the defect degree according to the offset angle. That is, using the offset angle as a parameter to measure the sharpness of the boundary of the channel hole.

[0075] As an example, the defect detection device can perform qualitative analysis on the defect degree of the channel hole according to other parameters such as the offset angle determined based on the offset distance. For example, the defect detection device determines whether the defect degree of the channel hole is serious based on the magnitude of the determined offset angle, and whether there are sharp corners in the boundary contour of the channel hole.

[0076] As another example, the defect detection device can perform quantitative analysis on the defect degree of the channel hole according to other parameters such as the offset angle determined based on the offset distance.

[0077] For example, the defect detection device can quantitatively analyze the defect degree of the channel hole according to the offset angle. The defect detection device can first determine a reference angle, and quantitatively analyze the defect degree of the channel hole according to the mapping relationship (such as a functional relationship) between the preset offset distance, the reference angle, and the defect degree value.

[0078] It should be understood that without departing from the teachings of the present application, the reference angle can be set to angles such as 90° or 180° as needed, and the mapping relationship between the offset distance, the reference angle, and the defect degree value can be adjusted according to the selection of the reference point and the reference angle. The present application places no restrictions on this.

[0079] In some embodiments of the present application, the defect detection method 1000 may further include, for example: executing an alarm instruction in response to the defect degree of the channel hole not meeting the preset requirements. Among them, the preset requirements can be set according to the method of analyzing the defect degree. For example, if a quantitative analysis of the defect degree is performed, the preset requirements can be, for example, that the defect degree value is less than a preset value, and the size of the preset value can be set as needed; if a qualitative analysis of the defect degree is performed, the preset requirements can be, for example, that the defect degree is a minor defect.

[0080] It should be understood that without departing from the teachings of the present application, the preset requirements can be adjusted as needed, and the present application places no restrictions on this.

[0081] Figure 5 It is a schematic block diagram of a defect detection device 2000 for a semiconductor structure according to an exemplary embodiment of the present application.

[0082] As Figure 5 shown, the defect detection device 2000 may include, for example: an identification module 2100, a determination module 2200, and a detection module 2300. Among them, the identification module 2100 can be used, for example, to identify the convex points of the boundary contour of the channel hole in the image to be measured of the semiconductor structure, the determination module 2200 can be used, for example, to determine the offset distance between the convex point with the maximum protrusion degree and its corresponding reference point, and the detection module 2300 can be used, for example, to determine the defect degree of the channel hole according to the determined offset distance.

[0083] According to the embodiments of the present application, by identifying the image to be measured of the semiconductor structure, the offset distance between the convex point with the maximum protrusion degree and its corresponding reference point can be obtained to measure the defect degree of the channel hole, so that the defects of the channel hole of the semiconductor structure can be automatically detected. Based on the offset distance to evaluate the defect, compared with manual evaluation of the defect, the evaluation result is more objective, and the cost of evaluating the defect is lower. In addition, detecting the defects of the channel hole ensures the performance of the finally formed semiconductor structure more.

[0084] In some embodiments of the present application, the determination module 2200 may be configured to, for example: determine the bump with the largest protruding degree from the identified bumps; determine the offset distance between the bump with the largest protruding degree and its corresponding reference point.

[0085] In some embodiments of the present application, the determination module 2200 is further configured to: identify the concave points of the boundary contour of the channel hole; determine the perpendicular distance from each concave point to the line connecting the two adjacent convex points, and determine the first concave point with the largest perpendicular distance from the adjacent two convex points from the concave points; determine the convex point with the largest protruding degree from the two convex points adjacent to the first concave point.

[0086] Exemplarily, determining the convex point with the largest protruding degree from the two convex points adjacent to the first concave point may include, for example: determining the convex point with the farthest distance from the first concave point among the two adjacent convex points as the convex point with the largest protruding degree.

[0087] In some embodiments of the present application, the reference point corresponding to the convex point with the largest protruding degree is the first concave point.

[0088] In some other embodiments of the present application, the determination module 2200 is configured to: determine the offset distance between each identified convex point and its corresponding reference point; use the maximum value among all the offset distances as the offset distance between the convex point with the largest protruding degree and its corresponding reference point.

[0089] In some embodiments of the present application, the identification module 2100 is configured to: identify the concave points of the boundary contour of the channel hole; wherein, the reference points include the concave points adjacent to the convex points.

[0090] In some embodiments of the present application, the offset distance between the convex point with the largest protruding degree and its corresponding reference point includes: the distance between the convex point with the largest protruding degree and its corresponding reference point in a specified direction, wherein the specified direction is perpendicular to the extending direction of the gate slit of the semiconductor structure.

[0091] In some embodiments of the present application, the convex point or the concave point may be, for example, an extreme point in the boundary contour of the channel hole.

[0092] In some embodiments of the present application, the identification module 2100 may further be configured to: extract the contour in the image to be measured; and perform noise reduction processing on the extracted contour to remove the part of the contour that is far from the boundary contour of the channel hole.

[0093] In some embodiments of the present application, the detection module 2300 may further be configured to: in response to the defect degree of the channel hole not meeting the preset requirements, execute an alarm instruction.

[0094] In some embodiments of the present application, the image to be detected includes a scanning electron microscope image of a channel hole in the extending direction of the channel hole. Exemplarily, the defect detection device 2000 may further include, for example, an image acquisition module (not shown), such as a scanning electron microscope, which is configured to capture a scanning electron microscope image of a channel hole in the extending direction of the channel hole during the semiconductor manufacturing process as the image to be detected.

[0095] In some embodiments of the present application, the semiconductor structure may be, for example, a three-dimensional memory or a part of a three-dimensional memory.

[0096] Embodiments of the present application also provide a detection device and a readable storage medium.

[0097] Figure 6 is a block diagram of a detection device 3000 according to an embodiment of the present application. The device is intended to represent various forms of digital computers, such as, a laptop computer, a desktop computer, a workbench, a personal digital assistant, a server, a blade server, a mainframe computer, and other suitable computers. The device may also represent various forms of mobile devices, such as, a personal digital processor, a cellular phone, a smart phone, a wearable device, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present application described and / or claimed herein.

[0098] As Figure 6 shown, the detection device 3000 includes: one or more processors 3100, a memory 3200, and an interface (not shown) for connecting the components, including a high-speed interface and a low-speed interface. The various components are interconnected using different buses and may be mounted on a common motherboard or otherwise mounted as required. The processor 3100 may process instructions executed within the detection device 3000, including instructions stored in the memory 3200 or on the memory 3200 to display graphical information of a GUI on an external input / output device (such as a display device coupled to the interface). In other embodiments, if necessary, multiple processors 3100 and / or multiple buses may be used together with multiple memories 3200 and multiple memories 3200. Similarly, multiple detection devices 3000 may be connected, each device providing some necessary operations (such as, as a server array, a set of blade servers, or a multi-processor system). Figure 6 One processor 3100 is taken as an example in

[0099] The memory 3200 is the readable storage medium provided by this application. For example, it is a non-transitory computer-readable storage medium. Among them, the memory 3200 stores instructions that can be executed by at least one processor 3100, so that at least one processor 3100 executes the defect detection method provided by this application. The readable storage medium of this application stores computer instructions, and these computer instructions are used to make a computer execute the defect detection method for a semiconductor structure provided by this application.

[0100] As a non-transitory computer-readable storage medium, the memory 3200 can be used to store non-transitory software programs, non-transitory computer-executable programs, and modules. The processor 3100 executes various functional applications and data processing of the server by running the non-transitory software programs, instructions, and modules stored in the memory 3200, that is, implements the defect detection method for a semiconductor structure in the above method embodiments.

[0101] The memory 3200 may include a program storage area and a data storage area. Among them, the program storage area can store an operating system and application programs required for at least one function; the data storage area can store data created according to the use of the detection device for quality control, etc. In addition, the memory 3200 may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state storage devices. In some embodiments, the memory 3200 may include a memory remotely set relative to the processor 3100, and these remote memories can be connected to the detection device 3000 through a network. Examples of the above network include but are not limited to the Internet, an enterprise intranet, a local area network, a mobile communication network, and combinations thereof.

[0102] The detection device 3000 may further include: an input device 3300 and an output device 3400. The processor 3100, the memory 3200, the input device 3300, and the output device 3400 can be connected through a bus or other means. Figure 6 Taking connection through a bus as an example.

[0103] The input device 3300 can receive input digital or character information, and generate key signal inputs related to user settings and function controls of the detection device for quality control, such as input devices like a touch screen, a keypad, a mouse, a trackpad, a touchpad, a pointing stick, one or more mouse buttons, a trackball, a joystick, etc. The output device 3400 may include a display device, an auxiliary lighting device (for example, an LED), and a tactile feedback device (for example, a vibration motor), etc. The display device may include but is not limited to a liquid crystal display (LCD), a light-emitting diode (LED) display, and a plasma display. In some embodiments, the display device may be a touch screen.

[0104] The various embodiments of the systems and techniques described herein can be implemented in digital electronic circuitry, integrated circuit systems, ASICs (application specific integrated circuits), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special-purpose or general-purpose programmable processor that receives data and instructions from, and transmits data and instructions to, a storage system, at least one input device, and at least one output device.

[0105] These computer programs (also referred to as programs, software, software applications, or code) include machine instructions for a programmable processor and can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. As used herein, the terms “machine-readable medium” and “computer-readable medium” refer to any computer program product, apparatus, and / or device (e.g., a disk, optical disk, memory, programmable logic device (PLD)) for providing machine instructions and / or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term “machine-readable signal” refers to any signal for providing machine instructions and / or data to a programmable processor.

[0106] In order to provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) by which the user can provide input to the computer. Other kinds of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic, speech, or tactile input).

[0107] The systems and techniques described herein can be implemented in a computing system including backend components (e.g., as a data server), or a computing system including middleware components (e.g., an application server), or a computing system including frontend components (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with embodiments of the systems and techniques described herein), or a computing system including any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected to each other by digital data communication in any form or medium (e.g., a communication network). Examples of communication networks include: local area networks, wide area networks, and the Internet.

[0108] A computer system can include a client and a server. The client and the server are generally far from each other and typically interact through a communication network. The client-server relationship is created by computer programs running on respective computers and having a client-server relationship with each other. The server can be a server of a distributed system, or a server combined with a blockchain. The server can also be a cloud server, or an intelligent cloud computing server or an intelligent cloud host with artificial intelligence technology. The server can be a server of a distributed system, or a server combined with a blockchain. The server can also be a cloud server, or an intelligent cloud computing server or an intelligent cloud host with artificial intelligence technology.

[0109] A method, device, detection equipment, and storage medium for defect detection of a semiconductor structure provided according to an embodiment of the present application can identify a to-be-tested image of the semiconductor structure to obtain an offset distance between the bump with the largest protrusion degree and its corresponding reference point, so as to measure the defect degree of the channel hole, enabling automatic detection of the defect of the channel hole of the semiconductor structure, and ensuring better performance of the finally formed semiconductor structure. Based on the offset distance to evaluate the defect, compared with manual evaluation of the defect, the evaluation result is more objective and the cost of evaluating the defect is lower.

[0110] It should be understood that various forms of the processes shown above can be used, with steps reordered, added, or deleted. For example, the steps recited in the present application can be executed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions disclosed in the present application can be achieved, and no limitation is made herein.

[0111] Although a semiconductor structure is described herein, it can be understood that one or more features can be omitted, substituted, or added from the semiconductor structure. For example, the semiconductor structure can also include, for example, a substrate in which various well regions and other necessary components can be formed as needed.

[0112] The above description is only for the implementation mode of this application and the explanation of the technical principles applied. Those skilled in the art should understand that the scope of protection involved in this application is not limited to the technical solution formed by the specific combination of the above technical features, and should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the technical concept. For example, the technical solution formed by mutually replacing the above features with the technical features (but not limited to) disclosed in this application that have similar functions.

Claims

1. A method for detecting defects in a semiconductor structure, characterized in that, Including: Identifying the convex points and concave points of the boundary contour of the channel holes in the image to be measured of the semiconductor structure; Determining the offset distance between the convex point with the maximum degree of protrusion and its corresponding reference point; And Determining the defect degree of the channel holes according to the determined offset distance; Wherein, determining the convex point with the maximum degree of protrusion includes: Determining the vertical distance from each of the concave points to the line connecting the two convex points adjacent to the concave point, and determining a first concave point with the maximum vertical distance between adjacent two convex points from the concave points; and, Determining the convex point with the maximum degree of protrusion from the two convex points adjacent to the first concave point.

2. The method according to claim 1, wherein: Determining the offset distance between the convex point with the maximum degree of protrusion and its corresponding reference point includes: Determining the convex point with the maximum degree of protrusion from the identified convex points; and Determining the offset distance between the convex point with the maximum degree of protrusion and its corresponding reference point.

3. The method according to claim 1, wherein, Determining the convex point with the maximum degree of protrusion from the two convex points adjacent to the first concave point includes: Determining the convex point with the maximum degree of protrusion as the convex point that is the farthest from the first concave point in a specified direction among the two adjacent convex points, and the specified direction is perpendicular to the extending direction of the gate slit of the semiconductor structure.

4. The method according to claim 1, wherein: The reference point corresponding to the convex point with the maximum degree of protrusion is the first concave point.

5. The method according to claim 1, wherein Determining the offset distance between the convex point with the maximum degree of protrusion and its corresponding reference point includes: Determining the offset distance between each identified convex point and its corresponding reference point; and Taking the maximum value among all the offset distances as the offset distance between the convex point with the maximum degree of protrusion and its reference point.

6. The method according to claim 5, wherein The method further includes: Identifying the concave points of the boundary contour of the channel holes; Wherein, the reference point includes the concave point adjacent to the convex point.

7. The method according to claim 1, wherein: The offset distance between the convex point with the maximum degree of protrusion and its corresponding reference point includes: the distance between the convex point with the maximum degree of protrusion and its corresponding reference point in a specified direction, wherein the specified direction is perpendicular to the extending direction of the gate slit of the semiconductor structure.

8. A defect detection device for a semiconductor structure, characterized in that, Including: An identification module, configured to identify the convex points and concave points of the boundary contour of the channel holes in the image to be measured of the semiconductor structure; A determination module, configured to determine the offset distance between the convex point with the maximum degree of protrusion and its corresponding reference point, and includes: determining the vertical distance from each of the concave points to the line connecting the two convex points adjacent to the concave point, and determining a first concave point with the maximum vertical distance between adjacent two convex points from the concave points; and, determining the convex point with the maximum degree of protrusion from the two convex points adjacent to the first concave point; and A detection module, configured to determine the defect degree of the channel holes according to the determined offset distance.

9. The device according to claim 8, wherein: The determination module is configured to: Determine the convex point with the maximum degree of protrusion from the identified convex points; and Determine the offset distance between the convex point with the maximum degree of protrusion and its corresponding reference point.

10. The device according to claim 8, wherein: The reference point corresponding to the convex point with the maximum degree of protrusion is the first concave point.

11. The device according to claim 8, wherein The determination module is configured to: Determine the offset distance between each identified convex point and its corresponding reference point; and The maximum value among all the offset distances is used as the offset distance between the salient point with the greatest protrusion and its corresponding reference point.

12. The device according to claim 11, wherein The identification module is further configured to: identifying concave points of a boundary contour of the channel hole; The reference point includes a concave point adjacent to the convex point.

13. The device according to any one of claims 8 to 12, wherein The offset distance between the convex point with the greatest protrusion and its corresponding reference point includes: the distance between the convex point with the greatest protrusion and its corresponding reference point in a specified direction, wherein the specified direction is perpendicular to the extension direction of the gate gap of the semiconductor structure.

14. A detection device, characterized in that: include: Memory, for storing computer instructions; as well as A processor, configured to communicate with the memory to execute the computer instructions, thereby implementing the defect detection method according to any one of claims 1 to 7.

15. A readable storage medium, characterized in that, The readable storage medium stores computer instructions, and when the computer instructions are executed by a processor, the defect detection method according to any one of claims 1 to 7 is implemented.

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