Detection method and device of through hole measurement data, detection equipment and storage medium

Abstract

The invention discloses a through hole measurement data detection method and device, detection equipment and a storage medium, and the method comprises the steps: obtaining the measurement data of a to-be-detected through hole in a semiconductor structure, the measurement data representing the height of the through hole, and obtaining the measurement data based on a first grayscale image of the to-be-detected through hole in a first measurement view field, the first measurement view field represents a predefined position of the to-be-detected through hole and is smaller than an opening area of the to-be-detected through hole; generating a gray value distribution curve based on a second gray image of the to-be-detected through hole in the second measurement view field; the second measurement view field is larger than an opening area of the to-be-detected through hole; determining a credible measurement area in the second grayscale image based on the grayscale value distribution curve; and determining whether the measurement data of the to-be-detected through hole is abnormal based on the coincidence degree of the credible measurement area and the first measurement view field. According to the invention, the accuracy and credibility of through hole height measurement are improved, and the filling quality in a through hole filling process is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of semiconductor technology, and in particular to a via measurement data detection method and device, a detection equipment and a storage medium. BACKGROUND

[0002] With the continuous advancement of semiconductor process nodes, the size of semiconductor devices is continuously reduced, and the aspect ratio of vias in semiconductor structures is continuously improved, making the filling process of high aspect ratio vias increasingly difficult. In the filling process of high aspect ratio vias, the accuracy of the measurement data of the via height is crucial for evaluating the filling quality of the via.

[0003] However, the related art cannot ensure the accuracy of the measurement data of the via height, thereby not only slowing down the development process of new nodes, but also causing the via to be filled unevenly and opened, thereby reducing the yield of semiconductor devices. SUMMARY

[0004] To solve the problems of the prior art, the embodiments of the present application provide a via measurement data detection method and device, a detection equipment and a storage medium. The technical solution is as follows:

[0005] On the one hand, a via measurement data detection method is provided, comprising:

[0006] Obtaining measurement data of a to-be-detected via; the measurement data represents the via height of the to-be-detected via, and the measurement data is obtained based on a first gray scale image of the to-be-detected via under a first measurement field of view; the first measurement field of view represents a predefined position of the to-be-detected via and is smaller than an opening area of the to-be-detected via;

[0007] Generating a gray scale value distribution curve based on a second gray scale image of the to-be-detected via under a second measurement field of view; the second measurement field of view is larger than the opening area of the to-be-detected via, and the gray scale value distribution curve represents the gray scale values of each pixel point in a target direction in the second gray scale image;

[0008] Determining a trusted measurement area in the second gray scale image based on the gray scale value distribution curve;

[0009] Determining whether the measurement data of the to-be-detected via is abnormal based on the degree of overlap between the trusted measurement area and the first measurement field of view.

[0010] On the other hand, a via measurement data detection device is provided, comprising:

[0011] a measurement data obtaining module, configured to obtain measurement data of a via to be detected, the measurement data representing a via height of the via to be detected, the measurement data being obtained based on a first grayscale image of the via to be detected under a first measurement field of view, the first measurement field of view representing a predefined position of the via to be detected and being smaller than an opening area of the via to be detected;

[0012] a grayscale value distribution curve generating module, configured to generate a grayscale value distribution curve based on a second grayscale image of the via to be detected under a second measurement field of view, the second measurement field of view being larger than the opening area of the via to be detected, the grayscale value distribution curve representing grayscale values of each pixel point in a target direction in the second grayscale image;

[0013] a trusted measurement area determining module, configured to determine a trusted measurement area in the second grayscale image based on the grayscale value distribution curve;

[0014] a detection result determining module, configured to determine whether the measurement data of the via to be detected is abnormal based on a degree of overlap between the trusted measurement area and the first measurement field of view.

[0015] In some exemplary embodiments, the apparatus further comprises a buffer measurement area determining module, configured to determine a buffer measurement area in the second grayscale image based on the grayscale value distribution curve;

[0016] The detection result determining module comprises:

[0017] a first overlap degree determining module, configured to determine a first overlap degree between the trusted measurement area and the first measurement field of view;

[0018] a second overlap degree determining module, configured to determine a second overlap degree between a non-overlapping area between the buffer measurement area and the trusted measurement area and the first measurement field of view based on the non-overlapping area;

[0019] a detection result determining submodule, configured to determine whether the measurement data of the via to be detected is abnormal based on the first overlap degree and the second overlap degree.

[0020] In some exemplary embodiments, the detection result determining submodule comprises:

[0021] a normal determining module, configured to determine that the measurement data of the via to be detected is normal if a first detection condition is met, the first detection condition being that the first overlap degree is greater than or equal to a first overlap degree threshold value and the second overlap degree is less than or equal to a second overlap degree threshold value;

[0022] The abnormality determining module is configured to determine that the measurement data of the to-be-detected via hole is abnormal when a second detection condition is met, the second detection condition being that the first coincidence degree is less than the first coincidence degree threshold and / or the second coincidence degree is greater than the second coincidence degree threshold.

[0023] In some example embodiments, the first coincidence degree determining module comprises:

[0024] The first overlap region determining module is configured to determine an intersection between the trusted measurement region and a measurement region corresponding to the first measurement field of view, to obtain a first overlap region.

[0025] The first area ratio determining module is configured to determine a ratio between an area of the first overlap region and an area of the measurement region, to obtain the first coincidence degree.

[0026] In some example embodiments, the second coincidence degree determining module comprises:

[0027] The non-overlap region determining module is configured to determine a non-overlap region between the buffer measurement region and the trusted measurement region.

[0028] The second overlap region determining module is configured to determine an intersection between the non-overlap region and a measurement region corresponding to the first measurement field of view, to obtain a second overlap region.

[0029] The second area ratio determining module is configured to determine a ratio between an area of the second overlap region and an area of the measurement region, to obtain the second coincidence degree.

[0030] In some example embodiments, the trusted measurement region determining module is specifically configured to: determine a trusted gray threshold based on the gray value distribution curve; and determine a trusted measurement region in the second gray image according to the trusted gray threshold.

[0031] The buffer measurement region determining module is specifically configured to: determine a buffer gray threshold based on the gray value distribution curve; and determine a buffer measurement region in the second gray image according to the buffer gray threshold, the buffer gray threshold being not more than the trusted gray threshold.

[0032] In some example embodiments, the trusted measurement region determining module comprises:

[0033] The gray value interval determining module is configured to determine a gray value interval based on the gray value distribution curve.

[0034] The trusted gray threshold determining module is configured to determine a middle value of the gray value interval as a trusted gray threshold.

[0035] In some example embodiments, the gray value distribution curve generation module comprises:

[0036] a three-dimensional gray distribution map generation module configured to generate a three-dimensional gray distribution map based on the second gray image;

[0037] a cutting module configured to obtain the gray value distribution curve based on a vertical cross section of the three-dimensional gray distribution map; the vertical cross section passes through the center of the to-be-detected via hole.

[0038] In some example embodiments, the apparatus further comprises:

[0039] a scanning module configured to acquire a to-be-detected image of the semiconductor structure by using a scanning electron microscope, the to-be-detected image comprising the to-be-detected via hole;

[0040] a gray processing module configured to perform gray processing on the to-be-detected image to obtain a target detection image;

[0041] a measurement data determination module configured to determine the measurement data of the to-be-detected via hole based on a gray value of an image region corresponding to the to-be-detected via hole in the target gray image;

[0042] a second gray image generation module configured to determine an image region corresponding to the to-be-detected via hole in the target detection image based on the second measurement field to obtain the second gray image.

[0043] In another aspect, a detection device is provided, comprising a processor and a memory, the memory storing at least one instruction or at least one program, the at least one instruction or the at least one program being loaded and executed by the processor to implement the via measurement data detection method of any of the above aspects.

[0044] In another aspect, a computer readable storage medium is provided, the computer readable storage medium storing at least one instruction or at least one program, the at least one instruction or the at least one program being loaded and executed by a processor to implement the via measurement data detection method of any of the above aspects.

[0045] The embodiment of the present application is aimed at the measurement data representing the height of the via hole obtained based on the first gray scale image of the via hole in the first measurement field. Since the first measurement field represents the predefined position of the via hole and is smaller than the opening area of the via hole, the measurement data may be inaccurate due to the possible position deviation of the via hole in the manufacturing process of the semiconductor structure. The embodiment of the present application combines the second gray scale image with a larger measurement field to generate a gray scale distribution curve, determines a reliable measurement area in the second gray scale image based on the gray scale distribution curve, and determines whether the measurement data of the via hole is abnormal based on the overlapping degree of the reliable measurement area and the first measurement field. Thus, the abnormal measurement data can be screened out, the accuracy and reliability of the height of the via hole submitted to the subsequent processing process are improved, and the filling quality in the via hole filling process is improved, thereby improving the yield of the semiconductor device. BRIEF DESCRIPTION OF DRAWINGS

[0046] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0047] Figure 1 is a flowchart of a via hole measurement data detection method provided by the embodiment of the present application;

[0048] Figure 2 is an example of the height of the via hole in the via hole filling process provided by the embodiment of the present application;

[0049] Figure 3a is an example of the first measurement field and the second measurement field in the case where the position of the via hole does not deviate provided by the embodiment of the present application;

[0050] Figure 3b is an example of the first measurement field in the case where the position of the via hole deviates provided by the embodiment of the present application;

[0051] Figure 4 is a flowchart of another via hole measurement data detection method provided by the embodiment of the present application;

[0052] Figure 5 is an example of generating a gray scale value distribution curve based on the second gray scale image provided by the embodiment of the present application;

[0053] Figure 6 is an example of the gray scale distribution interval determined based on the gray scale value distribution curve provided by the embodiment of the present application;

[0054] Figure 7is a flowchart of another method for detecting via measurement data provided by embodiments of the present application;

[0055] Figure 8 is an example of a trusted measurement area, a buffer measurement area, and a measurement area corresponding to the first measurement field provided by embodiments of the present application;

[0056] Figure 9 is a structural block diagram of a device for detecting via measurement data provided by embodiments of the present application;

[0057] Figure 10 is a structural block diagram of a detection device provided by embodiments of the present application. DETAILED DESCRIPTION

[0058] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the scope of protection of the present application.

[0059] It should be noted that the terms "first", "second", and the like in the specification and claims of the present application and the above-described drawings are used to distinguish similar objects, and do not necessarily indicate a specific object or a sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product, or server including a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products, or devices.

[0060] It will be understood that when an element or layer is referred to as being "on" or "connected to" another element or layer, it can be directly on or connected to the other element or layer or intervening elements or layers can be present. In contrast, when an element is referred to as being "directly on" or "directly connected to" another element or layer, there are no intervening elements or layers present. It will be understood that, although the terms first, second, third, etc. can be used herein to describe various elements, components, regions, layers and / or sections, these elements, components, regions, layers and / or sections should not be limited by these terms. These terms are only used to distinguish one element, component, region, layer or section from another element, component, region, layer or section. Thus, a first element, component, region, layer or section discussed below could be termed a second element, component, region, layer or section without departing from the teachings of the present application. Similarly, a second element, component, region, layer or section discussed below could be termed a first element, component, region, layer or section without departing from the teachings of the present application.

[0061] In addition, in the embodiments of the present application, the term "module" or "unit" refers to a computer program or a part of a computer program with a predetermined function, and works together with other related parts to achieve a predetermined target, and can be implemented entirely or partially by using software, hardware (such as a processing circuit or a memory), or a combination thereof. Similarly, one processor (or multiple processors or memories) can be used to implement one or more modules or units. In addition, each module or unit can be a part of an integral module or unit that includes the functions of the module or unit.

[0062] In the filling process of the via, one way of measuring the height of the via in the related art is to use TEM sectioning for measurement, but TEM sectioning is a destructive measurement method, and the measurement process is complicated and time-consuming, and it is difficult to support mass measurement; another way is to use SEM for measurement, however, due to the large noise of SEM measurement pictures, the edge boundary of the via with large aspect ratio is blurred and difficult to define, and the measured result has large error, at present, it is usually compared with the TEM result to increase the credibility of the measurement result, such a way not only cannot guarantee the accuracy of the via height measurement data, greatly slows down the development process of new nodes, and even causes the via to be not filled and opened, and reduces the yield of semiconductor devices.

[0063] In view of this, the embodiment of the present application provides a via measurement data detection method. The method is for measurement data representing via height obtained based on a first gray image of a via to be detected in a first measurement field. Since the first measurement field represents a predefined position of the via to be detected and is smaller than an opening area of the via to be detected, considering that a via position offset may occur in the manufacturing process of a semiconductor structure, causing the measurement data to be inaccurate, the embodiment of the present application combines a second gray image with a larger measurement field to generate a gray distribution curve, and determines a reliable measurement area in the second gray image based on the gray distribution curve, and then determines whether the measurement data of the via to be detected is abnormal based on the degree of overlap between the reliable measurement area and the first measurement field, so as to screen out abnormal measurement data, improve the accuracy and reliability of the measurement data submitted to the subsequent processing process, and thus facilitate improving the filling quality in the via filling process and improving the yield of the semiconductor device.

[0064] The following will be described in combination with Figures 1 to 8 The technical solutions of the embodiments of the present application will be described in detail.

[0065] Please refer to Figure 1 which is a flowchart of a via measurement data detection method provided by the embodiment of the present application. The method can be applied to a via measurement data detection device of the embodiment of the present application. The via measurement data detection device can be configured in a detection device. The detection device can be an electronic device including a processor and a memory. The memory stores at least one instruction or at least one program. The at least one instruction or the at least one program is loaded and executed by the processor to implement the via measurement data detection method of any one of the above aspects.

[0066] It should be noted that the present specification provides method operation steps as described in the embodiments or flowcharts, but more or fewer operation steps can be included based on conventional or non-creative labor. The order of steps listed in the embodiments is only one of the many execution orders, and does not represent the only execution order. In actual system or product execution, the method order shown in the embodiments or the drawings can be executed in sequence or in parallel (for example, in a parallel processor or multi-thread processing environment). Specifically, as shown in the Figure 1 The method can include:

[0067] In step S101, the measurement data of the via to be detected is obtained.

[0068] The measurement data of the via to be detected represents the via height of the via to be detected. The measurement data is obtained based on a first gray image of the via to be detected in a first measurement field. The first measurement field represents a predefined position of the via to be detected and the first measurement field is smaller than an opening area of the via to be detected on the surface of the semiconductor structure.

[0069] Specifically, in the filling process of the via, the via height of the via refers to the un-filled height of the via, as shown in Figure 2 Considering different via heights, theoretically, different electron beam reflection behaviors are generated, which is specifically reflected in the difference of image gray values. Therefore, the embodiment of the present application can measure the via height based on the gray values.

[0070] The first measurement field can generally be a preset range centered on the center position of the predefined pattern of the via to be detected. The size of the preset range can be 3-12 nm 2 For example, the first measurement field can be the range of a square frame centered on the center position of the predefined pattern of the via to be detected. The range of the square frame is smaller than the opening area of the via to be detected on the surface of the semiconductor structure. For example, the range of the square frame can be 6*6 nm 2 left and right.

[0071] In step S103, a gray value distribution curve is generated based on the second gray image of the via to be detected under the second measurement field.

[0072] The second measurement field is greater than the opening area of the via to be detected. The gray value distribution curve represents the gray values of the pixel points in a target direction in the second gray image. The target direction passes through the center of the via to be detected in the second gray image. Specifically, the target direction can be the x-axis direction of the second gray image passing through the center of the via to be detected.

[0073] Specifically, the second measurement field is greater than the opening area of the via to be detected, so that the second measurement field can include the complete via to be detected and a part of the background, so that the second measurement field is greater than the first measurement field. In a specific implementation, the second measurement field can be the range of a square frame covering the opening area of the via to be detected.

[0074] As shown in Figure 3a , in the case where the via does not occur position offset, the first gray image of the via under the first measurement field should be Figure 3a the image area framed by the left dashed frame 301, where the range of the dashed frame 301 is referred to as the first measurement field, Figure 3a the range of the right dashed frame 302 is referred to as the second measurement field. The second gray image of the via under the second measurement field includes the complete via and a part of the background formed by the semiconductor structure around the via. In the case where the via occurs position offset, as shown in Figure 3b , the first gray image of the via under the first measurement field can include a part of the background or the hole edge, so that a large measurement error can occur.

[0075] It can be understood that the first measurement field is smaller than the opening area of the to-be-detected via hole, so that compared with the second measurement field, the first measurement field can effectively avoid background interference, but at the same time, due to the small size of the first measurement field, the position offset in the manufacturing process of the via hole will have a significant impact on the measurement data of the to-be-detected via hole. The second measurement field is larger than the opening area of the to-be-detected via hole on the surface of the semiconductor structure, so that compared with the first measurement field, the second measurement field can not be affected by the position offset in the manufacturing process of the via hole. Therefore, the embodiment of the present application uses the second gray image of the to-be-detected via hole in the second measurement field to detect the measurement data obtained based on the first gray image in the first measurement field to determine whether the measurement data is abnormal, thereby effectively filtering the measurement data of the to-be-detected via hole and improving the accuracy and reliability of the measurement data submitted to the subsequent process flow.

[0076] Based on this, in some exemplary embodiments, as shown in FIG. 1, before step S101, the method can further include: Figure 4

[0077] In step S401, a scanning electron microscope is used to obtain a to-be-detected image of the semiconductor structure, and the to-be-detected image includes the to-be-detected via hole.

[0078] In some exemplary embodiments, the to-be-detected image obtained by the scanning electron microscope (SEM) can be an RGB image.

[0079] In step S403, the to-be-detected image is subjected to gray processing to obtain a target gray image.

[0080] Specifically, the pixel value of a pixel point in the to-be-detected image is converted into a gray value between 0 and 255, so as to realize the gray processing of the to-be-detected image.

[0081] In step S405, based on the gray value of the image region corresponding to the first measurement field corresponding to the to-be-detected via hole in the target gray image, the measurement data of the to-be-detected via hole is determined.

[0082] It can be understood that the image region corresponding to the first measurement field corresponding to the to-be-detected via hole in the target gray image is the first gray image, and then based on the gray value of the pixel point in the first gray image, the via hole height of the to-be-detected via hole can be obtained.

[0083] ​Exemplarily, a sampling point can be selected from the first gray-scale image, and the gray-scale value of the sampling point is converted into a corresponding height based on a conversion between the gray-scale value and the height, and then the via height is obtained. The selection of the sampling point can be implemented based on actual experience, for example, the sampling point can be a point at the center position of the first gray-scale image.

[0084] In step S407, an image region corresponding to the via to be detected in the target gray-scale image is determined based on the second measurement field of view, and the second gray-scale image is obtained.

[0085] In some exemplary application scenarios, before step S401, the method can further include:

[0086] A substrate is provided, which includes a semiconductor substrate and a patterned mask layer located on the semiconductor substrate, and the patterned mask layer includes a predefined pattern corresponding to the via to be detected. The first measurement field of view of the embodiments of the present application can be obtained based on the center position of the predefined pattern, for example, it can be a square range of a preset size with the center position of the predefined pattern as the center.

[0087] The semiconductor substrate is etched with the patterned mask layer as a mask to form an initial via in the semiconductor substrate.

[0088] The patterned mask layer is removed, and the semiconductor structure of the embodiments of the present application is obtained based on the initial via.

[0089] Specifically, the semiconductor substrate can be a bulk semiconductor or a silicon-on-insulator (SOI) substrate, etc., which can be doped (for example, doped with p-type dopants or n-type dopants) or undoped. It can be understood that the semiconductor substrate can include functional devices, which can include transistors, resistance structures, capacitance structures, etc.

[0090] The patterned mask layer can be a patterned photoresist layer. The removal of the patterned mask layer can use a wet etching or dry etching process.

[0091] Based on the above embodiments, a semiconductor structure including an unfilled via can be obtained, so that the measurement data of the unfilled via can be detected by using the method of the embodiments of the present application to ensure the accuracy of the measurement data of the unfilled via.

[0092] In some example application scenarios, the semiconductor structure based on the initial via hole can include: forming a filling layer in the initial via hole, wherein the initial via hole and the filling layer are the via hole to be detected in the semiconductor structure, and the semiconductor structure is obtained. For example, when the initial via hole is used to realize the function of a contact hole, the material of the filling layer can include a conductive material, such as copper. It can be understood that when the initial via hole is not used to realize the function of a contact hole, the material of the filling layer can include an insulating material.

[0093] Based on the above-mentioned embodiments, a semiconductor structure including a filled via hole can be obtained, so that the measurement data of the filled via hole can be detected by using the method of the present application, to ensure the accuracy of the measurement data of the filled via hole, and further ensure the filling quality of the via hole.

[0094] In the present application, the gray value distribution curve represents the gray values of the pixels in the target direction in the second gray image, and the target direction passes through the center of the via hole to be detected. Specifically, the target direction is a horizontal direction passing through the center of the via hole to be detected in the second gray image.

[0095] In some example embodiments, in order to improve the detection efficiency and the accuracy of the gray value distribution curve, the step S103 can include: generating a three-dimensional gray distribution map based on the second gray image; and obtaining the gray value distribution curve based on a cross section in a vertical direction of the three-dimensional gray distribution map, the cross section in the vertical direction passing through the center of the via hole to be detected, when the gray value distribution curve is generated based on the second gray image of the via hole to be detected in the second measurement field of view.

[0096] As shown in Figure 5 An example of generating a gray value distribution curve based on a second gray image is shown, where the left second gray image is a two-dimensional image, and a three-dimensional gray distribution map can be obtained by conversion. Then, a cross section in a vertical direction passing through the center of the via hole is used to cut the three-dimensional gray distribution map, and the points on the intersection line of the cross section in the vertical direction and the three-dimensional gray distribution map constitute the gray value distribution curve of the present application.

[0097] Continuing to refer to Figure 1 In step S105, a reliable measurement region is determined in the second gray image based on the gray value distribution curve.

[0098] Considering that the second gray image obtained based on the second measurement field of view inevitably absorbs part of the background noise, in order to ensure the accuracy of the measurement data, in the present application, a reliable measurement region is determined in the second gray image based on the gray value distribution curve, and the gray values in the reliable measurement region can be considered as not being affected by the background noise, i.e., the gray values are reliable.

[0099] In one exemplary embodiment, to ensure the accuracy of the trusted measurement area, the step S105, when determining the trusted measurement area in the second gray image based on the gray value distribution curve, can comprise: determining a trusted gray threshold based on the gray value distribution curve; and determining the trusted measurement area in the second gray image according to the trusted gray threshold, so that the gray value in the trusted measurement area is not less than the trusted gray threshold.

[0100] For example, when determining the trusted gray threshold based on the gray value distribution curve, it can comprise: determining a gray value interval based on the gray value distribution curve; and determining the middle value of the gray value interval as the trusted gray threshold.

[0101] The gray value interval can represent the range of gray values in the gray value distribution curve. In a specific implementation, the maximum gray value and the minimum gray value in the gray value distribution curve can be found, and then the maximum gray value is taken as the upper limit of the gray value interval, and the minimum gray value is taken as the lower limit of the gray value interval, so as to obtain the gray value interval, and then the middle value between the upper limit of the gray value interval and the lower limit of the gray value interval is taken as the trusted gray threshold. For example, the upper limit of the gray value interval is 190, and the lower limit of the gray value interval is 70, that is, the gray value interval is [70, 190], and the middle value of the gray value interval is: 70 + (190-70) / 2 = 130, and then the trusted gray threshold can be determined as 130.

[0102] In actual application, considering that the gray value distribution curve has certain volatility, in order to improve the accuracy of the trusted gray threshold and further improve the accuracy of the trusted measurement area, when determining the lower limit of the gray value interval based on the gray value distribution curve, a lower limit gray value range can be determined based on the gray value distribution curve, and then an average gray value is obtained by averaging the gray values in the gray value distribution curve falling within the lower limit gray value range, and then the average gray value can be taken as the lower limit of the gray value interval. Taking the gray value distribution curve shown in Figure 5 For example, as shown in Figure 6 , the lower limit gray value range can be determined as [40, 70], and then an average gray value as shown by the lower dotted line in Figure 6 is obtained by averaging the gray values in the gray value distribution curve falling within [40, 70], wherein Figure 6 the upper dotted line indicates the maximum gray value of the gray value distribution curve, and the range of gray values defined by the lower dotted line and the upper dotted line is the gray value interval.

[0103] Continuing to refer to Figure 1 , in step S107, based on the degree of coincidence between the trusted measurement area and the first measurement field of view, it is determined whether the measurement data of the through hole to be detected is abnormal.

[0104] Specifically, an intersection between the trusted measurement region and the measurement region corresponding to the first measurement field of view can be determined to obtain a first overlap region, and a ratio between an area of the first overlap region and an area of the measurement region corresponding to the first measurement field of view can be calculated, and the ratio can be taken as the degree of overlap between the trusted measurement region and the first measurement field of view.

[0105] Specifically, the first overlap degree threshold can be set as 80%, and if the degree of overlap between the trusted measurement region and the first measurement field of view exceeds the first overlap degree threshold, it can be determined that the measurement data of the to-be-detected via hole is normal, otherwise, if the degree of overlap between the trusted measurement region and the first measurement field of view does not exceed the first overlap degree threshold, it can be determined that the measurement data of the to-be-detected via hole is abnormal.

[0106] In some exemplary embodiments, in the case of being determined as normal, the measurement data of the to-be-detected via hole can be labeled with a label indicating normal, such as label "0", and in the case of being determined as abnormal, the measurement data of the to-be-detected via hole can be labeled with a label indicating abnormal, such as label "1", so that the to-be-detected via hole determined as abnormal can be identified based on the label in the subsequent process, and the to-be-detected via hole can be processed abnormally, such as being deleted or re-measured, which can be determined based on the proportion of the number of abnormalities to the total number and the importance of the pattern of the abnormal via hole to the process. For the via hole filling process, the to-be-detected via hole determined as abnormal can be processed abnormally, which can include deleting or re-measuring based on the proportion of the number of abnormalities to the total number and the importance of the pattern of the abnormal via hole to the process. For re-measuring, specifically, a new measurement recipe can be selected, such as the abnormal points being concentrated in a certain split condition, indicating that the current measurement recipe cannot well position the measurement under the split condition, or the position of the preset measurement frame is changed based on the existing measurement recipe, such as the pattern of the abnormal points being important and the number being small, so that only the preset measurement frame is changed for re-measurement, thereby improving the filling quality of the via hole and the yield of the semiconductor device.

[0107] In practical applications, considering that if the trusted measurement region is completely relied on, a large amount of data can be deleted, causing serious damage to the data, therefore, in some exemplary embodiments, as shown in Figure 7 The method can further include:

[0108] S701, determining a buffer measurement region in the second gray-scale image based on the gray value distribution curve.

[0109] The gray value of the buffer measurement region is generally smaller than the gray value of the trusted measurement region.

[0110] For example, based on the gray value distribution curve, determining the buffer measurement region in the second gray image can include: determining a buffer gray threshold based on the gray value distribution curve; and determining the buffer measurement region in the second gray image according to the buffer gray threshold.

[0111] The buffer gray threshold is not more than the trusted gray threshold, and the gray value in the buffer measurement region is not less than the buffer gray threshold.

[0112] Specifically, the buffer gray threshold can also be determined based on the aforementioned gray value interval used to determine the trusted gray threshold, for example, 20% to 50% of the gray value interval can be taken as the value range of the buffer gray threshold, such as 30% of the gray value interval as the buffer gray threshold. Taking the aforementioned gray value interval [70, 190] as an example, 30% of the gray value interval is: 70 + (190-70)*0.3 = 106, and the buffer gray threshold can be determined as 106.

[0113] In some examples, in order to improve the accuracy of the trusted measurement region and the buffer measurement region, the three-dimensional gray value distribution diagram shown in the foregoing Figure 5 , the horizontal plane with the trusted gray threshold as the gray value and the horizontal plane with the buffer gray threshold as the gray value are first determined, and then the horizontal plane with the trusted gray threshold as the gray value is used to horizontally cut the three-dimensional gray value distribution diagram, and the intersection line of the horizontal plane and the three-dimensional gray value distribution diagram is projected onto the second gray image to define the trusted measurement region, such as the region 801 shown in the foregoing Figure 8 ; similarly, the horizontal plane with the buffer gray threshold as the gray value is used to horizontally cut the three-dimensional gray value distribution diagram, and the intersection line of the horizontal plane and the three-dimensional gray value distribution diagram is projected onto the second gray image to define the buffer measurement region, such as the region 802 shown in the foregoing Figure 8 .

[0114] Based on this, the foregoing step S107 can include the following steps when implemented:

[0115] S703, determining a first coincidence degree of the trusted measurement region and the first measurement field of view.

[0116] S705, determining a second coincidence degree of the non-overlapping region and the first measurement field of view based on the non-overlapping region between the buffer measurement region and the trusted measurement region.

[0117] Specifically, for the first coincidence degree, the intersection between the trusted measurement region and the measurement region corresponding to the first measurement field of view can be determined to obtain a first overlapping region, and then the ratio between the area of the first overlapping region and the area of the measurement region corresponding to the first measurement field of view is determined to obtain the first coincidence degree.

[0118] Specifically, for the second overlap degree: a non-overlapping region between the buffer measurement region and the trusted measurement region can be determined, then an intersection between the non-overlapping region and a measurement region corresponding to the first measurement field is determined to obtain a second overlapping region, and then a ratio between an area of the second overlapping region and an area of the measurement region corresponding to the first measurement field is determined to obtain the second overlap degree.

[0119] For example, the first overlap degree is 80% and the second overlap degree is 15%. Figure 8 For example, the first overlap degree is 80% and the second overlap degree is 15%. Figure 8 For example, the first overlap degree is 80% and the second overlap degree is 15%. Figure 8 For example, the first overlap degree is 80% and the second overlap degree is 15%. For example, the first overlap degree is 80% and the second overlap degree is 15%.

[0120] S707, based on the first overlap degree and the second overlap degree, determining whether the measurement data of the to-be-detected via hole is abnormal.

[0121] Specifically, in the case of satisfying a first detection condition, it can be determined that the measurement data of the to-be-detected via hole is normal, the first detection condition is that the first overlap degree exceeds a first overlap degree threshold, and the second overlap degree does not exceed a second overlap degree threshold; and in the case of satisfying a second detection condition, it can be determined that the measurement data of the to-be-detected via hole is abnormal, the second detection condition is that the first overlap degree does not exceed the first overlap degree threshold, and / or the second overlap degree exceeds the second overlap degree threshold.

[0122] The first overlap degree threshold can be set based on actual experience, for example, the first overlap degree threshold is set to 80%; the second overlap degree threshold can be set based on actual experience, for example, the second overlap degree threshold is set to 15%. In actual application, the measurement data of the to-be-detected via hole can be labeled based on the detection result according to the following formula:

[0123] Label

[0124] Wherein, Ths represents the first overlap degree threshold; Thb represents the second overlap degree threshold.

[0125] In the above embodiment, the trusted measurement region and the buffer measurement region are combined to determine whether the measurement data of the to-be-detected via hole is abnormal, which avoids the adverse effects on the detection accuracy caused by a large amount of data being cleared.

[0126] Corresponding to the detection method of the via metrology data provided by the above-mentioned embodiments, the embodiment of the present application also provides a detection device of via metrology data. Since the detection device of via metrology data provided by the embodiment of the present application corresponds to the detection method of via metrology data provided by the above-mentioned embodiments, the implementation of the foregoing detection method of via metrology data is also applicable to the detection device of via metrology data provided by the present embodiment. In the present embodiment, it will not be described in detail.

[0127] Please refer to Figure 9 , which shows a structure schematic diagram of a detection device of via metrology data provided by the embodiment of the present application. The device has the function of detecting the method of via metrology data in the above-mentioned method embodiments. The function can be realized by hardware, or the corresponding software can be realized by hardware execution. As Figure 9 shown, the detection device of via metrology data 900 can include:

[0128] The metrology data acquisition module 910 is configured to acquire metrology data of a via to be detected. The metrology data represents a via height of the via to be detected. The metrology data is obtained based on a first gray scale image of the via to be detected under a first metrology field of view. The first metrology field of view represents a predefined position of the via to be detected and is smaller than an opening area of the via to be detected.

[0129] The gray scale value distribution curve generation module 920 is configured to generate a gray scale value distribution curve based on a second gray scale image of the via to be detected under a second metrology field of view. The second metrology field of view is larger than the opening area of the via to be detected. The gray scale value distribution curve represents gray scale values of each pixel point in a target direction in the second gray scale image.

[0130] The trusted metrology area determination module 930 is configured to determine a trusted metrology area in the second gray scale image based on the gray scale value distribution curve.

[0131] The detection result determination module 940 is configured to determine whether the metrology data of the via to be detected is abnormal based on a degree of coincidence of the trusted metrology area and the first metrology field of view.

[0132] In some exemplary embodiments, the device further includes a buffer metrology area determination module configured to determine a buffer metrology area in the second gray scale image based on the gray scale value distribution curve. The detection result determination module 940 includes:

[0133] A first degree of coincidence determination module is configured to determine a first degree of coincidence of the trusted metrology area and the first metrology field of view.

[0134] a second overlap degree determination module, configured to determine a second overlap degree between the non-overlapping region and the first measurement field based on the non-overlapping region between the buffer measurement region and the trusted measurement region;

[0135] a detection result determination sub-module, configured to determine whether the measurement data of the to-be-detected via hole is abnormal based on the first overlap degree and the second overlap degree.

[0136] In some exemplary embodiments, the detection result determination sub-module comprises:

[0137] a normal determination module, configured to determine that the measurement data of the to-be-detected via hole is normal when a first detection condition is satisfied; the first detection condition is that the first overlap degree is greater than or equal to a first overlap degree threshold and the second overlap degree is less than or equal to a second overlap degree threshold;

[0138] an abnormal determination module, configured to determine that the measurement data of the to-be-detected via hole is abnormal when a second detection condition is satisfied; the second detection condition is that the first overlap degree is less than the first overlap degree threshold and / or the second overlap degree is greater than the second overlap degree threshold.

[0139] In some exemplary embodiments, the first overlap degree determination module comprises:

[0140] a first overlap region determination module, configured to determine an intersection between the trusted measurement region and a measurement region corresponding to the first measurement field, to obtain a first overlap region;

[0141] a first area ratio determination module, configured to determine a ratio between an area of the first overlap region and an area of the measurement region, to obtain the first overlap degree.

[0142] In some exemplary embodiments, the second overlap degree determination module comprises:

[0143] a non-overlapping region determination module, configured to determine a non-overlapping region between the buffer measurement region and the trusted measurement region;

[0144] a second overlap region determination module, configured to determine an intersection between the non-overlapping region and a measurement region corresponding to the first measurement field, to obtain a second overlap region;

[0145] a second area ratio determination module, configured to determine a ratio between an area of the second overlap region and an area of the measurement region, to obtain the second overlap degree.

[0146] In some example embodiments, the trusted metrology region determination module is specifically configured to: determine a trusted gray threshold based on the gray value distribution curve; and determine a trusted metrology region in the second gray image according to the trusted gray threshold.

[0147] The buffer metrology region determination module is specifically configured to: determine a buffer gray threshold based on the gray value distribution curve; and determine a buffer metrology region in the second gray image according to the buffer gray threshold, the buffer gray threshold being no more than the trusted gray threshold.

[0148] In some example embodiments, the trusted metrology region determination module comprises:

[0149] The gray value interval determination module is configured to determine a gray value interval based on the gray value distribution curve.

[0150] The trusted gray threshold determination module is configured to determine a middle value of the gray value interval as a trusted gray threshold.

[0151] In some example embodiments, the gray value distribution curve generation module comprises:

[0152] The three-dimensional gray distribution map generation module is configured to generate a three-dimensional gray distribution map based on the second gray image.

[0153] The cutting module is configured to obtain the gray value distribution curve based on a vertical direction cross section of the three-dimensional gray distribution map, the vertical direction cross section passing through a center of the to-be-detected via hole.

[0154] In some example embodiments, the apparatus 900 further comprises:

[0155] The scanning module is configured to acquire a to-be-detected image of the semiconductor structure by using a scanning electron microscope, the to-be-detected image comprising the to-be-detected via hole.

[0156] The gray processing module is configured to perform gray processing on the to-be-detected image to obtain a target detection image.

[0157] The metrology data determination module is configured to determine the metrology data of the to-be-detected via hole based on gray values of an image region corresponding to the to-be-detected via hole in the target gray image.

[0158] The second gray image generation module is configured to determine an image region corresponding to the to-be-detected via hole in the target detection image based on the second metrology field of view to obtain the second gray image.

[0159] It should be noted that the apparatus provided by the above embodiments, in realizing its functions, only divides the above-mentioned various functional modules by way of example, and in actual application, the above-mentioned functions can be completed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the above-described functions. In addition, the apparatus and method embodiments provided by the above embodiments belong to the same concept, and the specific implementation process is detailed in the method embodiments, which will not be repeated here.

[0160] The embodiments of the present application provide a detection device, which comprises a processor and a memory, the memory stores at least one instruction or at least one program, the at least one instruction or the at least one program is loaded and executed by the processor to realize any one of the detection methods of via measurement data provided by the above method embodiments.

[0161] The memory can be used to store software programs and modules, and the processor executes various functional applications and data processing by running the software programs and modules stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store operating systems, application programs required by functions, etc.; the data storage area can store data created according to the use of the device, etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other volatile solid-state memory device. Accordingly, the memory can also include a memory controller to provide access for the processor to the memory.

[0162] Figure 10 The hardware structure block diagram of the detection device for running a detection method of via measurement data provided by the embodiments of the present application is shown in FIG. 1, which can include but is not limited to a processor, a network interface and a memory. The processor, the network interface and the memory in the detection device can be connected through a bus or other means, and in the embodiments of the present specification, the connection through the bus is taken as an example. Figure 10 Figure 10

[0163] ​​The processor (or CPU (Central Processing Unit)) is the computing core and control core of the detection device. The network interface can optionally include a standard wired interface, a wireless interface (such as WI-FI, a mobile communication interface, etc.). The memory is a memory device in the detection device, used to store programs and data. It can be understood that the memory herein can be a high-speed RAM memory device, or a non-volatile memory, for example, at least one disk storage device; optionally, it can also be at least one storage device located away from the aforementioned processor. The memory provides a storage space that stores the operating system of the electronic device, which can include but is not limited to: a Windows system (an operating system), a Linux (an operating system), an Android (a mobile operating system) system, an IOS (a mobile operating system) system, etc., and the present application is not limited thereto; and in the storage space, one or more instructions suitable for being loaded and executed by the processor are also stored, which can be one or more computer programs (including program codes). In the embodiment of the present application, the processor loads and executes one or more instructions stored in the memory to implement any one of the detection methods of the through-hole measurement data provided by the above method embodiments.

[0164] The embodiment of the present application also provides a computer readable storage medium, which can be arranged in the detection device to save at least one instruction or at least one program related to the detection method of the through-hole measurement data, which is loaded and executed by the processor to implement any one of the detection methods of the through-hole measurement data provided by the above method embodiments.

[0165] Optionally, in the present embodiment, the storage medium can include but is not limited to: a U disk, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk, and various media that can store program codes.

[0166] Although the present application is disclosed as above, the present application is not limited thereto. Any person skilled in the art can make various changes and modifications without departing from the spirit and scope of the present application, and therefore the protection scope of the present application should be subject to the scope defined by the claims.

Claims

1. A method for detecting through-hole measurement data, characterized in that, include: Acquire measurement data of the through hole to be detected; the measurement data represents the height of the through hole to be detected, and the measurement data is obtained based on the first grayscale image of the through hole to be detected under the first measurement field of view, the first measurement field of view represents the predefined position of the through hole to be detected and is smaller than the opening area of ​​the through hole to be detected. Based on the second grayscale image of the through hole to be detected under the second measurement field of view, a grayscale value distribution curve is generated; the second measurement field of view is larger than the opening area of ​​the through hole to be detected, and the grayscale value distribution curve represents the grayscale value of each pixel in the target direction in the second grayscale image; Based on the grayscale value distribution curve, a reliable measurement region is determined in the second grayscale image; Based on the degree of overlap between the reliable measurement area and the first measurement field of view, it is determined whether the measurement data of the through hole to be detected is abnormal.

2. The method according to claim 1, characterized in that, Also includes: Based on the grayscale value distribution curve, a buffer measurement area is determined in the second grayscale image; The step of determining whether the measurement data of the through-hole to be detected is abnormal based on the degree of overlap between the reliable measurement area and the first measurement field of view includes: Determine the first degree of overlap between the reliable measurement region and the first measurement field of view; Based on the non-overlapping area between the buffer measurement area and the reliable measurement area, a second degree of overlap between the non-overlapping area and the first measurement field of view is determined. Based on the first degree of overlap and the second degree of overlap, it is determined whether the measurement data of the through hole to be detected is abnormal.

3. The method according to claim 2, characterized in that, The step of determining whether the measurement data of the through-hole to be detected is abnormal based on the first degree of overlap and the second degree of overlap includes: Under the condition that the first detection condition is met, the measurement data of the through hole to be detected is determined to be normal; the first detection condition is that the first degree of overlap exceeds the first degree of overlap threshold, and the second degree of overlap does not exceed the second degree of overlap threshold. If the second detection condition is met, the measurement data of the through hole to be detected is determined to be abnormal; the second detection condition is that the first degree of overlap does not exceed the first degree of overlap threshold, and / or the second degree of overlap exceeds the second degree of overlap threshold.

4. The method according to claim 2, characterized in that, Determining the degree of overlap between the reliable measurement region and the first measurement field of view includes: The intersection of the reliable measurement region and the corresponding measurement region of the first measurement viewpoint is determined to obtain the first overlapping region; The ratio between the area of ​​the first overlapping region and the area of ​​the measurement region is determined to obtain the first degree of overlap.

5. The method according to claim 4, characterized in that, The step of determining the second degree of overlap between the non-overlapping region and the first measurement field of view based on the non-overlapping region between the buffer measurement region and the reliable measurement region includes: Determine the non-overlapping region between the buffer measurement region and the reliable measurement region; The intersection between the non-overlapping region and the corresponding measurement region of the first measurement viewpoint is determined to obtain the second overlapping region; The ratio between the area of ​​the second overlapping region and the area of ​​the measurement region is determined to obtain the second degree of overlap.

6. The method according to claim 2, characterized in that, The step of determining a reliable measurement region in the second grayscale image based on the grayscale value distribution curve includes: determining a reliable grayscale threshold based on the grayscale value distribution curve; and determining a reliable measurement region in the second grayscale image according to the reliable grayscale threshold. The step of determining a buffer measurement region in the second grayscale image based on the grayscale value distribution curve includes: determining a buffer grayscale threshold based on the grayscale value distribution curve; and determining a buffer measurement region in the second grayscale image according to the buffer grayscale threshold, wherein the buffer grayscale threshold does not exceed the reliable grayscale threshold.

7. The method according to claim 6, characterized in that, The step of determining the reliable grayscale threshold based on the grayscale value distribution curve includes: Based on the grayscale value distribution curve, determine the grayscale value range; The median value of the grayscale value range is determined as the reliable grayscale threshold.

8. The method according to any one of claims 1 to 7, characterized in that, The step of generating a grayscale value distribution curve based on the second grayscale image of the through-hole to be detected in the second measurement field of view includes: Based on the second grayscale image, a three-dimensional grayscale distribution map is generated; The grayscale value distribution curve is obtained based on the vertical cross-section of the three-dimensional grayscale distribution map; the vertical cross-section passes through the center of the through hole to be detected.

9. The method according to claim 1, characterized in that, Before acquiring the measurement data of the through hole to be tested, the method further includes: A scanning electron microscope is used to acquire an image of a semiconductor structure to be inspected, the image including the via to be inspected; The image to be detected is converted to grayscale to obtain the target grayscale image; Based on the gray value of the image region corresponding to the first measurement field of view of the through hole to be detected in the target grayscale image, the measurement data of the through hole to be detected is determined; Based on the second measurement field of view, the image region corresponding to the hole to be detected in the target grayscale image is determined, and the second grayscale image is obtained.

10. The method according to claim 9, characterized in that, Before acquiring an image of the semiconductor structure to be inspected using a scanning electron microscope, the method further includes: A substrate is provided, the substrate including a semiconductor substrate and a patterned mask layer located on the semiconductor substrate; the patterned mask layer includes a predefined pattern corresponding to the via to be detected; The semiconductor substrate is etched using the patterned mask layer as a mask to form an initial via in the semiconductor substrate; Remove the patterned mask layer and obtain the semiconductor structure based on the initial via; The first measurement field of view is obtained based on the center position of the predefined pattern corresponding to the through hole to be detected.

11. The method according to claim 10, characterized in that, The process of obtaining the semiconductor structure based on the initial via includes: A filling layer is formed in the initial via; wherein the initial via and the filling layer serve as the via to be detected to obtain the semiconductor structure.

12. The method according to claim 11, characterized in that, After determining whether the measurement data of the via to be detected is abnormal based on the degree of overlap between the reliable measurement area and the first measurement field of view, the method further includes: If the measurement data of the via to be tested is abnormal, then the via to be tested in the semiconductor structure is subjected to abnormal filling processing.

13. A device for detecting through-hole measurement data, characterized in that, include: The measurement data acquisition module is used to acquire measurement data of the through hole to be detected; the measurement data represents the height of the through hole to be detected, and the measurement data is obtained based on the first grayscale image of the through hole to be detected under the first measurement field of view, the first measurement field of view represents the predefined position of the through hole to be detected and is smaller than the opening area of ​​the through hole to be detected. A grayscale value distribution curve generation module is used to generate a grayscale value distribution curve based on a second grayscale image of the through hole to be detected under a second measurement field of view; the second measurement field of view is larger than the opening area of ​​the through hole to be detected, and the grayscale value distribution curve represents the grayscale value of each pixel in the target direction in the second grayscale image; A reliable measurement region determination module is used to determine a reliable measurement region in the second grayscale image based on the grayscale value distribution curve. The detection result determination module is used to determine whether the measurement data of the through hole to be detected is abnormal based on the degree of overlap between the reliable measurement area and the first measurement field of view.

14. A testing device, characterized in that, The method includes a processor and a memory, wherein the memory stores at least one instruction or at least one program, and the at least one instruction or the at least one program is loaded and executed by the processor to implement the method for detecting through-hole measurement data as described in any one of claims 1 to 12.

15. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores at least one instruction or at least one program, which is loaded and executed by a processor to implement the method for detecting through-hole measurement data as described in any one of claims 1 to 12.

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