Method, computer readable medium, and computerized system for gray level ratio inspection

Abstract

A method for grayscale ratio inspection includes: acquiring an electronic image including ROI pixels of a sampled region of interest (ROI) and reference pixels of a sampled reference region, wherein the ROI pixels are acquired by illuminating the ROI with an electron beam, and the reference pixels are acquired without illuminating the reference region with an electron beam; calculating a reference dark level value based on the values ​​of at least some of the reference pixels; in response to the reference dark level value, calculating a grayscale ratio between a first grayscale value associated with a first subset of the ROI pixels and a second grayscale value associated with a second subset of the ROI pixels; determining whether the grayscale ratio indicates a defect; and generating defect information after determining that the grayscale ratio indicates a defect.

Description

[Technical Field]

[0001] This patent application claims the benefit of U.S. Patent Application No. 17 / 678,733, filed February 23, 2022, the entire disclosure of which is incorporated herein by reference for various purposes.

[0002] This disclosure relates to a grayscale ratio check. [Previous Technology]

[0003] The grayscale ratio (GLR) check includes calculating the grayscale ratio between pixels with different features, such as pixels on the background surface (minus the reference dark level) and pixels on the polysilicon conductor (minus the reference dark level).

[0004] The reference dark level is calculated every few months. However, the reference dark level may change from one image to another for various reasons, including, for example, changes in illumination, changes in collection (e.g., changes caused by changes in the voltage supply to the photomultiplier), etc.

[0005] Changes in the reference dark level introduce significant errors into the calculation of GLR.

[0006] There is an increasing need to provide an accurate method for GLR calculations. [Summary of the Invention]

[0007] GLR checks with dark level compensation can be provided.

Implementation Method

[0017] Numerous specific details are set forth in the following detailed description in order to provide a thorough understanding of embodiments of the present invention.

[0018] However, those skilled in the art will understand that the current embodiments of this application can be practiced without these specific details. In other instances, well-known methods, procedures, and components have not been described in detail so as not to obscure the current embodiments of this application.

[0019] The subject matter considered as an embodiment of this invention is specifically pointed out and explicitly claimed in the concluding section of the specification. However, the embodiments of the organization and method of operation of this invention, as well as their objects, features, and advantages, can be best understood by referring to the following detailed description when read in conjunction with the accompanying drawings.

[0020] It will be understood that, for the sake of simplicity and clarity, the elements shown in the accompanying drawings are not necessarily drawn to scale. For example, for clarity, the dimensions of some elements may be enlarged relative to other elements. Furthermore, element symbols may be repeated between the drawings where deemed appropriate to indicate corresponding or similar elements.

[0021] Since most of the embodiments shown in this case can be implemented using electronic components and circuits known to those skilled in the art, the details will not be explained to the extent deemed necessary, as described above, in order to understand and comprehend the basic concepts of the current embodiments of this case, so as not to confuse or mislead the teachings of the current embodiments of this case.

[0022] Any reference to the method in the specification shall be applied, with the necessary modifications, to a system capable of performing the method.

[0023] Any references to the system in the specification shall be applied, with the necessary modifications, to methods that can be performed by the system.

[0024] The term "and / or" means additionally or alternatively.

[0025] Systems, methods and non-transient computer-readable media for GLR inspection can be provided.

[0026] Figure 1 illustrates the region of interest (ROI) 41 of the sample, the reference region 42 of the sample, and an example of a structural element located within the region of interest.

[0027] The structural element includes a first background surface element 21, a first sidewall 22 of the trench, a bottom 23 of the trench, a second sidewall 24 of the trench, and a second background surface 25. Any other structural element may be provided.

[0028] The first background surface 21 and the second background surface 25 are located at a first height, while the bottom 23 of the trench is located below the first height. The first background surface may be different from the bottom of the trench in terms of material composition.

[0029] The first background surface element 21 is captured by the first sub-region 31 of the electronic image 40. The first sidewall 22 of the trench is captured by the second sub-region 32 of the electronic image 40. The bottom 23 of the trench is captured by the third sub-region 33 of the electronic image 40. The second sidewall 24 of the trench is captured by the fourth sub-region 34 of the electronic image 40. The second background surface 25 is captured by the fifth sub-region 35 of the electronic image 40.

[0030] Figure 1 illustrates the ROI and reference region associated with the acquisition of electronic images. Other ROIs and / or other reference regions can be defined for different electronic images. A reference region of one image can be part of the ROI of another image, and vice versa.

[0031] ROI may far exceed the reference area. For example, the reference area may include 2-10 rows compared to the hundreds or even more than 1,000 rows of the ROI.

[0032] Figure 2 illustrates the scanning mode for the ROI 41 and the sampling reference area 42 used for scanning sampling. Figure 2 illustrates the scanning mode of the grid scanning mode. Other scanning modes can be applied.

[0033] The scanning mode includes a first part 51 for scanning the reference area 42 and a second part 52 for scanning the ROI 41.

[0034] Figure 3 shows the image 61 of ROI 41 and reference area 42.

[0035] Figure 3 also illustrates a reference dark level value of 80.

[0036] ROI is extracted from ROI pixels 62(1,1) - 62(Q,R), where Q and R represent the row and column respectively, and are positive integers.

[0037] The reference area is captured by reference pixels 61(1,1) - 61(J,K), where J and K represent the row and column respectively, and are positive integers.

[0038] Figure 4 is a timing diagram 70 illustrating the multiple iterations of electronic image acquisition. The first electronic image is acquired by acquiring the first reference region (during time period 71 (1)) and acquiring the first ROI (during time period 72 (1)).

[0039] The Nth electronic image is acquired by acquiring the Nth reference region (during time period 71(N)) and the Nth ROI (during time period 72(N)). (N is a positive integer.)

[0040] Figure 5 is an example of the pixels of the structural elements and various data structures.

[0041] The first background surface element 21 is captured by the first sub-region 31, which includes the first background surface element pixels 31(1,1) - 31(B,C).

[0042] The first sidewall 22 is captured by the second sub-region 32 of the electronic image 40, which includes the first sidewall pixels 32(1,1) – 32(D,E).

[0043] The bottom 23 of the trench is captured by a third sub-region 33, which includes bottom pixels 33(1,1) – 33(F,G).

[0044] The second sidewall 24 is captured by the fourth sub-region 34, which includes the second sidewall pixels 34(1,1) – 34(H,L).

[0045] The second background surface 25 is captured by the fifth sub-region 35, which includes the second background surface 35(1,1) – 35(M,P).

[0046] Figure 5 illustrates a first grayscale value 81 associated with the first background surface element 21, a second grayscale value 82 associated with the second sidewall 22 of the trench, a third grayscale value 83 associated with the bottom 23 of the trench, a fourth grayscale value associated with the second sidewall 24 of the trench, and a fifth grayscale value associated with the second background surface 25.

[0047] Subtract the reference dark level value from the first grayscale value to provide a first dark level compensation value 91. Subtract the reference dark level value from the second grayscale value to provide a second dark level compensation value 92. Subtract the reference dark level value from the third grayscale value to provide a third dark level compensation value 93. Subtract the reference dark level value from the fourth grayscale value to provide a fourth dark level compensation value 94. Subtract the reference dark level value from the fifth grayscale value to provide a fifth dark level compensation value 95.

[0048] Any gray level ratio can be calculated by referring to the first gray level value to the fifth gray level value and the reference gray level value 80.

[0049] Assume that the grayscale ratio of 99 is the ratio between the third grayscale value and the fifth grayscale value.

[0050] Determining whether a defect exists may include comparing the grayscale ratio with (a) one or more grayscale values ​​101(1) – 101(V) indicating the absence of a defect, and / or comparing the grayscale ratio with (b) one or more grayscale values ​​102(1) – 102(V) indicating the absence of a defect. This comparison may provide an indication of whether the grayscale ratio 99 indicates a defect, and if so, defect information 105 may be generated.

[0051] Figure 7 is an example of a method 700 for grayscale ratio checking.

[0052] Method 700 can be performed on one or more electronic images, such as images 40, 40' and 40'' shown in FIG6.

[0053] Method 700 may begin with step 110 of obtaining an electronic image, which may include ROI pixels of a sampled region of interest (ROI) and reference pixels of a sampled reference region.

[0054] ROI pixels are obtained by illuminating the ROI with an electron beam.

[0055] A reference pixel is obtained without illuminating the reference area with an electron beam. The reference pixel may include deflecting the electron beam outside the sample, using a blanking unit, or preventing the generation of an electron beam.

[0056] Step 110 may include generating an electronic image. Generating may include illuminating the ROI with an electron beam and detecting electrons emitted from the ROI.

[0057] Step 110 may include receiving an electronic image.

[0058] Step 110 may include obtaining an electronic image by applying a scanning pattern that covers the reference region and the ROI. For example, referring to the scanning pattern of FIG2, the scanning pattern includes a first portion 51 for scanning the reference region 42 and a second portion 52 for scanning the ROI 41.

[0059] Step 110 can be followed by step 120, which calculates the reference dark level value based on at least some of the values ​​in the reference pixels.

[0060] An ROI can include multiple related sub-regions and can calculate many grayscale ratios. A related sub-region is a sub-region that should be evaluated by applying grayscale ratio calculations.

[0061] The reference dark level value can be used to calculate multiple gray levels of the ROI. This is illustrated by the repeated steps 130, 140, 150, and 160.

[0062] Assuming there are multiple ROIs within the electronic image, step 120 can be followed by step 130, which selects one of the multiple ROIs. Any selection procedure can be used. For example, selection can be based on importance, priority, location of the ROI, etc.

[0063] Step 130 can be followed by step 140, which calculates the grayscale ratio between the first grayscale value associated with the first subset of ROI pixels and the second grayscale value associated with the second subset of ROI pixels.

[0064] This calculation responds to a reference dark level value.

[0065] The ROI and the reference region can be adjacent to each other—for example, see ROI 41 and reference region 42 in Figures 1 and 2. The ROI can be spaced apart from the reference region.

[0066] The first subset of ROI pixels can be obtained from the first sub-region of ROI, and the second subset of ROI pixels can be obtained from the second sub-region of ROI.

[0067] The first sub-region may differ from the second sub-region in at least one of height and material composition. For example, at least refer to the height difference between the first background surface element 21 and the bottom 23 of the trench in FIG1.

[0068] Step 140 may include: o Calculating a first grayscale value (GL1) by averaging at least some grayscale values ​​in a first subset of ROI pixels. o Calculating a second grayscale value (GL2) by averaging at least some grayscale values ​​in a second subset of ROI pixels. o Subtracting a reference dark level value (GLref) from the first grayscale value to provide a first dark level compensation value (GLcomp1). o Subtracting the reference dark level value (GLref) from the second grayscale value to provide a second dark level compensation value (GLcomp2). o Dividing the first dark level compensation value by the second dark level compensation value to provide a grayscale ratio (GLR). GLR=(GL1-GLref) / (GL2-GLref)=GLcomp1 / GLcomp2

[0069] Step 140 can be followed by step 150, which determines whether the grayscale ratio indicates a defect.

[0070] Step 150 may be followed by step 160 in response to the decision, for example, generating defect information, storing defect information, sending defect detection, etc. after determining the grayscale ratio to indicate the defect.

[0071] Step 160 may also include jumping to step 130 when the electronic image includes one or more unchecked ROIs. This conditional jump may be performed in a step other than step 160.

[0072] When there are no unchecked ROIs, or when it is determined that the evaluation of the electronic images is complete, step 160 may be followed by step 170, which checks whether there are one or more electronic images to be checked.

[0073] Step 150 may include at least one of the following operations:

[0074] The grayscale ratio is compared with one or more grayscale values ​​indicating defects.

[0075] The grayscale ratio is compared with one or more grayscale values ​​that indicate the absence of defects.

[0076] Figure 8 is an example of a computerized system 800, which includes a processing circuit 810 and a memory unit 820. The computerized system may include an electronic image acquisition unit 830, which includes an electronic sensor 840.

[0077] The computerized system may be a scanning electron microscope (SEM), an electron imager, or may belong to an SEM or an electron imager. It may communicate with an SEM or an electron imager, or may receive electronic images in any way.

[0078] The processing circuit 810 may be an image processor, and may include one or more integrated circuits, etc.

[0079] The processing circuit 810 may be configured to: (a) acquire an electronic image including ROI pixels of a sampled region of interest (ROI) and reference pixels of a sampled reference region; wherein the ROI pixels are acquired by illuminating the ROI with an electron beam; wherein the reference pixels are acquired without illuminating the reference region with an electron beam; (b) calculate a reference dark level value based on the values ​​of at least some of the reference pixels; (c) calculate a grayscale ratio between a first grayscale value associated with a first subset of the ROI pixels and a second grayscale value associated with a second subset of the ROI pixels; wherein the calculation is in response to the reference dark level value; (d) determine whether the grayscale ratio indicates a defect; and (e) generate defect information after determining that the grayscale ratio indicates a defect.

[0080] In the foregoing specification, specific examples of embodiments of the present invention have been described with reference to them. However, it will be apparent that various modifications and changes may be made therein without departing from the broader spirit and scope of the embodiments of the present invention as set forth in the appended claims.

[0081] Furthermore, the terms “front,” “rear,” “top,” “bottom,” “above,” “below,” etc. (if any) used in this specification and the claims are for descriptive purposes and are not necessarily used to describe permanent relative positions. It should be understood that the terms used so are interchangeable where appropriate, such that the embodiments of this case described herein can, for example, operate in orientations other than those shown or otherwise described herein.

[0082] The connection discussed herein can be any type of connection suitable for transmitting signals from or to a corresponding node, unit, or device, for example, via a relay device. Therefore, unless otherwise implied or stated, the connection can be, for example, a direct connection or an indirect connection. Connections can be illustrated or described with reference to a single connection, multiple connections, unidirectional connections, or bidirectional connections. However, different embodiments can vary the implementation of the connection. For example, separate unidirectional connections can be used instead of bidirectional connections, and vice versa. Furthermore, multiple connections can be replaced by a single connection that transmits multiple signals in a serial or time-multiplexed manner. Similarly, a single connection carrying multiple signals can be separated into various different connections carrying subsets of these signals. Therefore, many options exist for transmitting signals.

[0083] Any arrangement of components used to achieve the same function is effectively “associated” to achieve the desired function. Therefore, any two components combined herein to achieve a particular function can be considered as “associated” with each other to achieve the desired function, regardless of the architecture or intermediate components. Similarly, any two such associated components can also be considered as “operably connected” or “operably coupled” to each other to achieve the desired function.

[0084] Furthermore, those skilled in the art will recognize that the boundaries between the above operations are merely illustrative. Multiple operations may be combined into a single operation, a single operation may be distributed among additional operations, and operations may be performed with at least partial overlap in time. Additionally, alternative embodiments may include multiple instances of a particular operation, and the order of operations may be varied in various other embodiments.

[0085] Furthermore, for example, in one embodiment, the illustrated example can be implemented as a circuit system located on a single integrated circuit or in the same device. Alternatively, the example can be implemented as any number of separate integrated circuits or separate devices interconnected with each other in a suitable manner.

[0086] However, other modifications, variations, and substitutions are also possible. Therefore, the specification and drawings should be considered illustrative rather than restrictive.

[0087] Any reference marks placed between parentheses in a claim should not be construed as limiting the claim. The word "comprising" does not exclude the presence of other elements or steps besides those listed in the claim. The terms "a" or "an" as used herein are defined as one or more. Furthermore, the use of introductory phrases such as "at least one" and "one or more" in a claim should not be construed as implying that the introduction of another claim element by the indefinite article "a" or "an" limits any particular claim containing such an introduced claim element to embodiments of the present case containing only one such element, even when the same claim includes the introductory phrase "one or more" or "at least one" with an indefinite article such as "a" or "an". The same applies to the use of definite articles. Unless otherwise stated, terms such as "first" and "second" are used to arbitrarily distinguish elements described by such terms. Therefore, these terms are not necessarily intended to indicate the time or other priority of such elements. The mere fact that certain measures are recited in mutually different claims does not indicate that combinations of these measures cannot be advantageously used.

[0088] Although certain features of the embodiments of this case have been described and illustrated herein, many modifications, substitutions, alterations, and equivalents will now occur to those skilled in the art. Therefore, it should be understood that the appended claims are intended to cover all such modifications and alterations falling within the true spirit of the embodiments of this case. [Simplified Explanation of the Diagram]

[0008] The subject matter considered as an embodiment of this invention is specifically pointed out and explicitly claimed in the concluding section of the specification. However, the embodiments of the organization and method of operation of this invention, as well as their objects, features, and advantages, can be best understood by referring to the following detailed description when read in conjunction with the accompanying drawings, in which:

[0009] Figure 1 shows the region of interest of the sample, the reference region of the sample, and an example of a structural element located within the region of interest;

[0010] Figure 2 is an example of a scanning pattern for scanning the region of interest and the reference region;

[0011] Figure 3 is an example of pixels in the region of interest, pixels in the reference region, and reference dark level values;

[0012] Figure 4 is an example of a timing diagram;

[0013] Figure 5 shows examples of pixels of structural elements and various data structures;

[0014] Figure 6 is an example of multiple electronic images;

[0015] Figure 7 is an example of the method; and

[0016] Figure 8 is an example of the system. [Biomaterial Storage]

[0090] Domestic storage information (please note in order of storage institution, date, and number): None. International storage information (please note in order of storage country, institution, date, and number): None.

Claims

1. A method for grayscale ratio inspection, the method comprising the steps of: (a) acquiring an electronic image including a sampled region of interest (ROI) pixels and reference pixels of a sampled reference region, wherein the ROI pixels are acquired by illuminating the ROI with an electron beam, and the reference pixels are acquired without illuminating the reference region with an electron beam; (b) calculating a reference dark level value based on the values ​​of at least some of the reference pixels; (c) Calculating a grayscale ratio between a first grayscale value associated with a first subset of the ROI pixels and a second grayscale value associated with a second subset of the ROI pixels, wherein calculating the grayscale ratio includes the following steps: (i) calculating the first grayscale value by averaging at least some grayscale values ​​in the first subset of the ROI pixels; (ii) calculating the second grayscale value by averaging at least some grayscale values ​​in the second subset of the ROI pixels; (iii) subtracting a reference dark level value from the first grayscale value to provide a first dark level compensation value; (iv) subtracting the reference dark level value from the second grayscale value to provide a second dark level compensation value; and (v) dividing the first dark level compensation value by the second dark level compensation value; (d) determining whether the grayscale ratio indicates a defect; and (e) generating defect information after determining that the grayscale ratio indicates a defect. The first subset of the ROI pixels is obtained from a first sub-region of the ROI, and the second subset of the ROI pixels is obtained from a second sub-region of the ROI. The first sub-region and the second sub-region are regions relating to structural elements located within the ROI.

2. The method as described in claim 1, wherein determining whether the grayscale ratio indicates a defect is made by comparing the grayscale ratio with one or more grayscale values ​​that indicate a defect.

3. The method as described in claim 1, wherein determining whether the grayscale ratio indicates a defect is made by comparing the grayscale ratio with one or more grayscale values ​​indicating a lack of defect.

4. The method as described in claim 1, wherein the ROI and the reference regions are adjacent to each other.

5. The method as described in claim 1, wherein obtaining the electronic image includes applying a scanning pattern covering the reference region and the ROI.

6. The method as described in claim 1, wherein the first sub-region differs from the second sub-region in at least one of height and material composition.

7. The method as described in claim 1, comprising repeating steps (c), (d), and (e) for multiple subsets of ROI pixels associated with multiple pairs of subregions of the ROI, wherein the first subset and the second subset of the ROI pixels are a pair within the multiple subsets.

8. The method as claimed in claim 1, wherein steps (a) to (e) are repeated for each of the plurality of electronic images.

9. The method as described in claim 8, wherein a reference region of one image is part of a region of interest (ROI) of another electronic image.

10. A non-transient computer-readable medium storing computer-readable instructions for performing grayscale ratio checks by: (a) acquiring an electronic image including ROI pixels of a sampled region of interest (ROI) and reference pixels of a sampled reference region, wherein the ROI pixels are acquired by illuminating the ROI with an electron beam, and the reference pixels are acquired without illuminating the reference region with an electron beam; (b) calculating a reference dark level value based on the values ​​of at least some of the reference pixels; (c) Calculating a grayscale ratio between a first grayscale value associated with a first subset of the ROI pixels and a second grayscale value associated with a second subset of the ROI pixels, wherein calculating the grayscale ratio includes the following steps: (i) calculating the first grayscale value by averaging at least some grayscale values ​​in the first subset of the ROI pixels; (ii) calculating the second grayscale value by averaging at least some grayscale values ​​in the second subset of the ROI pixels; (iii) subtracting a reference dark level value from the first grayscale value to provide a first dark level compensation value; (iv) subtracting the reference dark level value from the second grayscale value to provide a second dark level compensation value; and (v) dividing the first dark level compensation value by the second dark level compensation value; (d) determining whether the grayscale ratio indicates a defect; and (e) generating defect information after determining that the grayscale ratio indicates a defect. The first subset of the ROI pixels is obtained from a first sub-region of the ROI, and the second subset of the ROI pixels is obtained from a second sub-region of the ROI. The first sub-region and the second sub-region are regions relating to structural elements located within the ROI.

11. A computerized system for grayscale ratio inspection, the system comprising a processing circuit configured to cause the system to: (a) acquire an electronic image including ROI pixels of a sampled region of interest (ROI) and reference pixels of a sampled reference region, wherein the ROI pixels are acquired by illuminating the ROI with an electron beam, and the reference pixels are acquired without illuminating the reference region with the electron beam; (b) calculate a reference dark level value based on the values ​​of at least some of the reference pixels; (c) Calculating a grayscale ratio between a first grayscale value associated with a first subset of the ROI pixels and a second grayscale value associated with a second subset of the ROI pixels, wherein calculating the grayscale ratio includes the following steps: (i) calculating the first grayscale value by averaging at least some grayscale values ​​in the first subset of the ROI pixels; (ii) calculating the second grayscale value by averaging at least some grayscale values ​​in the second subset of the ROI pixels; (iii) subtracting a reference dark level value from the first grayscale value to provide a first dark level compensation value; (iv) subtracting the reference dark level value from the second grayscale value to provide a second dark level compensation value; and (v) dividing the first dark level compensation value by the second dark level compensation value; (d) determining whether the grayscale ratio indicates a defect; and (e) generating defect information after determining that the grayscale ratio indicates a defect. The first subset of the ROI pixels is obtained from a first sub-region of the ROI, and the second subset of the ROI pixels is obtained from a second sub-region of the ROI. The first sub-region and the second sub-region are regions relating to structural elements located within the ROI.

12. The computerized system as described in claim 11, wherein the system includes an electronic image acquisition unit that includes an electronic sensor.

Images