Grayscale ratio check

Abstract

A method for grayscale ratio inspection includes: acquiring an electronic image, the electronic image including ROI pixels of a region of interest (ROI) of a sample and reference pixels of a reference region of the sample, 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; calculating a reference dark level value based on values of at least some of the reference pixels; 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 in response to the reference dark level value; determining whether the grayscale ratio indicates a defect; and generating defect information after determining that the grayscale ratio indicates a defect.

Description

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

[0002] Grayscale ratio (GLR) inspection involves calculating the grayscale ratio between the grayscale of pixels of different features, for example, pixels of a background surface (minus a reference dark level) and pixels of a polysilicon conductor (minus a reference dark level).

[0003] The reference dark level is calculated every few months. However, the reference dark level may vary from one image to another due to various reasons including, for example, illumination variations, collection variations (such as those caused by variations in the photomultiplier voltage supply), etc.

[0004] Variations in the reference dark level introduce significant errors in the calculation of the GLR.

[0005] There is an increasing need to provide accurate methods for GLR calculations. Summary of the Invention

[0006] GLR inspection with dark level compensation can be provided. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] The subject matter which is regarded as embodiments of the present disclosure is particularly pointed out and distinctly claimed in the concluding portion of the specification. However, the present disclosure, both as to organization and method of operation, together with objects, features, and advantages thereof, may be best understood by reference to the following detailed description when read in connection with the accompanying drawings, in which:

[0008] Figure 1 are examples of a region of interest of a sample, a reference region of a sample, and a structural element positioned within the region of interest;

[0009] Figure 2 is an example of a scanning pattern that scans a region of interest and a reference region;

[0010] Figure 3 are examples of pixels of the region of interest, pixels of the reference region, and reference dark level values;

[0011] Figure 4 is an example of a timing diagram;

[0012] Figure 5 Pixels are examples of structural elements and various data structures;

[0013] Figure 6 is an example of multiple electronic images;

[0014] Figure 7is an example of a method; and

[0015] Figure 8 is an example of a system. DETAILED DESCRIPTION

[0016] In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of embodiments of the present disclosure.

[0017] However, it will be understood by those skilled in the art that the present embodiments of the present disclosure can be practiced without these specific details.In other instances, well-known methods, procedures, and components are not described in detail so as not to obscure the present embodiments of the present disclosure.

[0018] The subject matter which is regarded as embodiments of the present disclosure is particularly pointed out and distinctly claimed in the concluding portion of the specification. However, the present disclosure, both as to organization and method of operation, together with objects, features, and advantages thereof, may be best understood by reference to the following detailed description when read in connection with the accompanying drawings.

[0019] It will be appreciated that for simplicity and clarity of illustration, the elements shown in the drawings are not necessarily drawn to scale. For example, the dimensions of some of the elements may be exaggerated relative to other elements for clarity. Furthermore, where deemed appropriate, reference numerals may be repeated between the drawings to indicate corresponding or similar elements.

[0020] Since most of the illustrated embodiments of the present disclosure can be implemented using electronic components and circuits known to those skilled in the art, details will not be explained to a greater extent than deemed necessary in order to understand and appreciate the basic concepts of the present embodiments of the present disclosure, so as not to confuse or obscure the teachings of the present embodiments of the present disclosure.

[0021] Any reference in the specification to a method should apply mutatis mutandis to a system capable of performing that method.

[0022] Any reference in the specification to a system shall apply mutatis mutandis to a method performable by the system.

[0023] The term "and / or" means additionally or alternatively.

[0024] Systems, methods, and non-transitory computer-readable media for GLR inspection may be provided.

[0025] Figure 1 A region of interest (ROI) 41 of a sample, a reference region 42 of the sample, and examples of structural elements positioned within the region of interest are shown.

[0026] The structural elements comprise a first background surface element 21, a first side wall 22 of the trench, a bottom 23 of the trench, a second side wall 24 of the trench and a second background surface 25. Any other structural elements may be provided.

[0027] 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 in material composition from the trench bottom.

[0028] The first background surface element 21 is captured by the first sub-area 31 of the electron image 40. The first sidewall 22 of the trench is captured by the second sub-area 32 of the electron image 40. The bottom 23 of the trench is captured by the third sub-area 33 of the electron image 40. The second sidewall 24 of the trench is captured by the fourth sub-area 34 of the electron image 40. The second background surface element 25 is captured by the fifth sub-area 35 of the electron image 40.

[0029] Figure 1 ROIs and reference regions associated with the acquisition of electronic images are shown. Other ROIs and / or other reference regions can be defined for different electronic images. A reference region of one image can be part of an ROI of another image, and vice versa.

[0030] The ROI may be much larger than the reference region, for example, the reference region may include 2-10 lines compared to several hundred lines or even more than 1000 lines of the ROI.

[0031] Figure 2 A scanning pattern for scanning a ROI 41 of a sample and a reference region 42 of the sample is shown. Figure 2 The scanning mode shown is a raster scanning mode. Other scanning modes can be applied.

[0032] The scanning pattern includes a first portion 51 for scanning the reference region 42 and a second portion 52 for scanning the ROI 41 .

[0033] Figure 3 An image 61 of the ROI 41 and the reference region 42 is shown.

[0034] Figure 3 A reference dark level value 80 is also shown.

[0035] The ROI is captured by ROI pixels 62(1,1)-62(Q,R), where Q and R represent row and column, respectively, and are positive integers.

[0036] The reference area is captured by reference pixels 61(1,1)-61(J,K), where J and K represent rows and columns, respectively, and are positive integers.

[0037] Figure 4is a timing diagram 70 showing multiple iterations of acquisition of electronic images. A first electronic image is acquired by acquiring a first reference region (during time period 71 (1)) and acquiring a first ROI (during time period 72 (1)).

[0038] The Nth electronic image (N is a positive integer) is acquired by acquiring the Nth reference region (during the period 71 (N)) and acquiring the Nth ROI (during the period 72 (N)).

[0039] Figure 5 Pixels are examples of structural elements and various data structures.

[0040] The first background surface elements 21 are captured by a first sub-area 31 comprising first background surface element pixels 31 ( 1 , 1 ) - 31 (B, C).

[0041] The first sidewall 22 is captured by a second sub-region 32 of the electronic image 40 , which includes first sidewall pixels 32 ( 1 , 1 )- 32 (D, E).

[0042] The bottom 23 of the trench is captured by a third sub-region 33 of the electron image 33 , which comprises bottom pixels 33 ( 1 , 1 )– 33 (F,G).

[0043] The second sidewall 24 is captured by a fourth sub-region 34 , which includes second sidewall pixels 34 ( 1 , 1 )- 34 (H, L).

[0044] The second background surface 25 is captured by a fifth sub-region 35 , which includes second background surfaces 35 ( 1 , 1 )- 35 (M,P).

[0045] Figure 5 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 groove, a third grayscale value 83 associated with the bottom 23 of the groove, a fourth grayscale value associated with the second sidewall 24 of the groove, and a fifth grayscale value associated with the second background surface 25 are shown.

[0046] The reference dark level value is subtracted from the first gray value to provide a first dark level compensation value 91. The reference dark level value is subtracted from the second gray value to provide a second dark level compensation value 92. The reference dark level value is subtracted from the third gray value to provide a third dark level compensation value 93. The reference dark level value is subtracted from the fourth gray value to provide a fourth dark level compensation value 94. The reference dark level value is subtracted from the fifth gray value to provide a fifth dark level compensation value 95.

[0047] Any grayscale ratio may be calculated with reference to the first to fifth grayscale values and the reference grayscale value 80 .

[0048] Assume that the grayscale ratio 99 is a ratio between the third grayscale value and the fifth grayscale value.

[0049] Determining whether a defect is present can include comparing the grayscale ratio to (a) one or more grayscale values 101(1)-101(V) indicating a lack of a defect, and / or comparing the grayscale ratio to (b) one or more grayscale values 102(1)-102(V) indicating a lack of a defect. The comparison can provide an indication of whether the grayscale ratio 99 indicates a defect, and if so, defect information 105 can be generated.

[0050] Figure 7 is an example of a method 700 for grayscale ratio inspection.

[0051] Method 700 may be performed on one or more electronic images, such as Figure 6 The images 40, 40' and 40" are shown in FIG.

[0052] The method 700 may begin with step 110 of obtaining an electronic image, which may include a region of interest (ROI) pixels of a sample and reference pixels of a reference region of the sample.

[0053] ROI pixels are obtained by illuminating the ROI with an electron beam.

[0054] The reference pixel is obtained without illuminating the reference area with an electron beam. The reference pixel can include deflecting the electron beam outside the sample, using a blanking element, preventing the generation of an electron beam, etc.

[0055] Step 110 may include generating an electron image. Generating may include illuminating the ROI with an electron beam and detecting electrons emitted from the ROI.

[0056] Step 110 may include receiving an electronic image.

[0057] Step 110 may include obtaining an electronic image by applying a scanning pattern covering the reference region and the ROI. Figure 2 The scanning mode includes a first part 51 for scanning the reference area 42 and a second part 52 for scanning the ROI 41.

[0058] Step 110 may be followed by a step 120 of calculating a reference dark level value based on the values of at least some of the reference pixels.

[0059] The ROI can include multiple relevant sub-regions and many grayscale ratios can be calculated. The relevant sub-regions are the sub-regions that should be evaluated by applying the grayscale ratio calculation.

[0060] The reference dark level value can be used to calculate multiple grayscale ratios of the ROI. This is illustrated by multiple repetitions of steps 130, 140, 150 and 160.

[0061] Assuming that there are multiple ROIs in the electronic image, step 120 may be followed by step 130 of selecting an ROI from the multiple ROIs. Any selection process may be used. For example, the selection may be based on importance, priority, location of the ROI, etc.

[0062] Step 130 may be followed by step 140 of calculating a grayscale ratio between a first grayscale value associated with a first subset of ROI pixels and a second grayscale value associated with a second subset of ROI pixels.

[0063] The calculation is responsive to a reference dark level value.

[0064] The ROI and the reference region can be adjacent to each other - see e.g. Figure 1 and Figure 2 ROI 41 and reference region 42. The ROI may be spaced apart from the reference region.

[0065] A first subset of ROI pixels may be obtained from a first sub-region of the ROI, and a second subset of ROI pixels may be obtained from a second sub-region of the ROI.

[0066] The first sub-region may differ from the second sub-region in at least one of height and material composition. Figure 1 The height difference between the first background surface element 21 and the bottom 23 of the groove.

[0067] Step 140 may include:

[0068] o Calculating a first grayscale value (GL1) by averaging the grayscale of at least some of the first subset of ROI pixels.

[0069] o Calculating a second grayscale value (GL2) by averaging the grayscale of at least some of the second subset of ROI pixels.

[0070] o Subtracting a reference dark level value (GLref) from the first grayscale value to provide a first dark level compensation value (GLcomp1).

[0071] o Subtracting the reference dark level value (GLref) from the second grayscale value to provide a second dark level compensation value (Glcomp2).

[0072] o Dividing the first dark level compensation value by the second dark level compensation value to provide a grayscale ratio (GLR).

[0073] GLR=(GL1-GLref) / (GL2-GLref)=GLcomp1 / GLcomp2

[0074] Step 140 may be followed by step 150 of determining whether the grayscale ratio indicates a defect.

[0075] Step 150 may be followed by step 160 in response to the determination, for example, generating defect information after determining that the grayscale ratio indicates a defect, storing the defect information, sending the defect detection, etc.

[0076] Step 160 may also include jumping to step 130 when the electronic image includes one or more unexamined ROIs. This conditional jump may be performed in a step different from step 160.

[0077] When there are no uninspected ROIs, or when it is determined that the evaluation of the electronic images is complete, step 160 may be followed by step 170 of checking whether there are one or more electronic images to be inspected.

[0078] Step 150 may include at least one of the following operations:

[0079] The grayscale ratio is compared to one or more grayscale values indicative of a defect.

[0080] The grayscale ratio is compared to one or more grayscale values that indicate a lack of defects.

[0081] Figure 8 is an example of a computerized system 800 that includes a processing circuit 810 , a memory unit 820 . The computerized system may include an electronic image acquisition unit 830 that includes an electronic sensor 840 .

[0082] The computerized system may be a scanning electron microscope (SEM), an electron imager, may be part of a SEM, may be part of an electron imager, may be in communication with a SEM, may be in communication with an electron imager, or may receive an electronic image in any manner.

[0083] The processing circuit 810 may be an image processor and may include one or more integrated circuits.

[0084] The processing circuit 810 may be configured to:

[0085] (a) acquiring an electronic image comprising a region of interest (ROI) pixel of a sample and reference pixels of a reference region of the sample; wherein the ROI pixel is acquired by illuminating the ROI with an electron beam; wherein the reference pixel is acquired without illuminating the reference region with an electron beam;

[0086] (b) calculating a reference dark level value based on values of at least some of the reference pixels;

[0087] (c) calculating a grayscale ratio between a first grayscale value associated with a first subset of ROI pixels and a second grayscale value associated with a second subset of ROI pixels; wherein the calculating is responsive to a reference dark level value;

[0088] (d) determining whether the grayscale ratio indicates a defect; and

[0089] (e) Generating defect information after determining that the grayscale ratio indicates a defect.

[0090] In the foregoing specification, embodiments of the present disclosure have been described with reference to specific examples thereof. It will, however, be evident that various modifications and changes may be made therein without departing from the broader spirit and scope of embodiments of the present disclosure as set forth in the appended claims.

[0091] Furthermore, the terms "front," "back," "top," "bottom," "above," "below," and the like, if any, in the specification and claims are used for descriptive purposes and are not necessarily intended to describe permanent relative positions. It is understood that the terms so used are interchangeable under appropriate circumstances such that the embodiments of the disclosure described herein are, for example, capable of operation in other orientations than those illustrated or otherwise described herein.

[0092] As discussed herein, the connection can be any type of connection suitable for transmitting a signal, for example, from a corresponding node, unit or device or to a corresponding node, unit or device via an intermediate device. Therefore, unless otherwise implied or indicated, the connection can be, for example, a direct connection or an indirect connection. Connections can be described or described with reference to a single connection, multiple connections, a unidirectional connection or a bidirectional connection. However, different embodiments can change the implementation of the connection. For example, a separate unidirectional connection can be used instead of a bidirectional connection, and vice versa. In addition, multiple connections can be replaced by a single connection that transmits multiple signals in a serial manner or in a time-multiplexed manner. Similarly, a single connection that carries multiple signals can be separated into various different connections that carry a subset of these signals. Therefore, there are many options for transmitting signals.

[0093] Any arrangement of components to achieve the same functionality is effectively "associated" such that the desired functionality is achieved. Thus, any two components herein combined to achieve a particular functionality may be considered to be "associated" with each other such that the desired functionality is achieved, regardless of architectures or intermediary components. Similarly, any two components so associated may also be considered to be "operably connected" or "operably coupled" to each other such that the desired functionality is achieved.

[0094] Furthermore, those skilled in the art will recognize that the boundaries between the above-described 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 at least partially overlapping in time. Furthermore, alternative embodiments may include multiple instances of a particular operation, and the order of the operations may be changed in various other embodiments.

[0095] Furthermore, for example, in one embodiment, the illustrated examples may be implemented as circuitry located on a single integrated circuit or in the same device. Alternatively, the examples may be implemented as any number of separate integrated circuits or separate devices interconnected with each other in a suitable manner.

[0096] However, other modifications, changes, and substitutions are possible. Accordingly, the specification and drawings are to be regarded in an illustrative rather than a restrictive sense.

[0097] In the claims, any reference signs placed between parentheses should not be construed as limiting the claim. The word "comprising" does not exclude the presence of other elements or steps than those listed in the claim. As used herein, the terms "a" or "an" are defined as one or more than one. In addition, the use of introductory phrases such as "at least one" and "one or more" in the claims should not be interpreted as implying that any particular claim containing such introduced claim element by introducing another claim element through the indefinite article "a" or "an" should be limited to embodiments of the present disclosure that only contain one such element, even when the same claim includes the introductory phrases "one or more" or "at least one" with indefinite articles 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 between the elements described by such terms. Therefore, these terms are not necessarily intended to indicate a temporal or other priority order of such elements. The mere fact that certain measures are recited in mutually different claims does not indicate that a combination of these measures cannot be used to advantage.

[0098] While certain features of the embodiments of the present disclosure have been illustrated and described herein, many modifications, substitutions, changes, and equivalents will now occur to those skilled in the art. It will therefore be understood that the appended claims are intended to cover all such modifications and changes that fall within the true spirit of the embodiments of the present disclosure.

Claims

1. A method for grayscale ratio inspection, the method comprising: (a) acquiring an electronic image, the electronic image comprising ROI pixels of a region of interest (ROI) of a sample and reference pixels of a reference region of the sample, 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 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 comprises: (i) calculating the first grayscale value by averaging the grayscales of at least some of the first subset of the ROI pixels, (ii) calculating the second grayscale value by averaging the grayscales of at least some of the second subset of the ROI pixels, (iii) subtracting the 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 the 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, and the first sub-region and the second sub-region are regions associated with a structural element located within the ROI. 2 . The method of claim 1 , wherein determining whether the grayscale ratio indicates a defect is performed by comparing the grayscale ratio to one or more grayscale values indicative of a defect. 3 . The method of claim 1 , wherein determining whether the grayscale ratio indicates a defect is determined by comparing the grayscale ratio to one or more grayscale values that indicate a lack of a defect. The method of claim 1 , wherein the ROI and the reference region are adjacent to each other. The method of claim 1 , wherein obtaining the electronic image comprises applying a scanning pattern covering the reference region and the ROI. The method of 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 of claim 1 , comprising repeating steps (c), (d) and (e) for multiple pairs of subsets of ROI pixels associated with multiple pairs of sub-regions of the ROI, wherein the first subset of ROI pixels and the second subset of ROI pixels are one of the multiple pairs of subsets.

8. The method of claim 1, wherein steps (a) through (e) are repeated for each electronic image in a plurality of electronic images.

9. The method of claim 8, wherein the reference region of one image is a portion of a ROI of another electronic image.

10. A non-transitory computer-readable medium storing computer-readable instructions for performing a grayscale ratio check by the following steps: (a) acquiring an electronic image, the electronic image comprising ROI pixels of a region of interest (ROI) of a sample and reference pixels of a reference region of the sample, 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 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 comprises: (i) calculating the first grayscale value by averaging the grayscales of at least some of the first subset of the ROI pixels, (ii) calculating the second grayscale value by averaging the grayscales of at least some of the second subset of the ROI pixels, (iii) subtracting the 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 the 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, and the first sub-region and the second sub-region are regions associated with a structural element located within the ROI.

11. A computerized system for grayscale ratio inspection, the system comprising processing circuitry configured to cause the system to: (a) acquiring an electronic image, the electronic image comprising ROI pixels of a region of interest (ROI) of a sample and reference pixels of a reference region of the sample, 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) calculating a reference dark level value based on 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 comprises: (i) calculating the first grayscale value by averaging the grayscales of at least some of the first subset of the ROI pixels, (ii) calculating the second grayscale value by averaging the grayscales of at least some of the second subset of the ROI pixels, (iii) subtracting the 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 the 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, and the first sub-region and the second sub-region are regions associated with a structural element located within the ROI.

12. The computerized system of claim 11, wherein the system comprises an electronic image acquisition unit comprising an electronic sensor.

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