WO2020195304A1

WO2020195304A1 - Pattern matching method

Info

Publication number: WO2020195304A1
Application number: PCT/JP2020/005798
Authority: WO
Inventors: 祐治三浦
Original assignee: Ｔａｓｍｉｔ株式会社
Priority date: 2019-03-22
Filing date: 2020-02-14
Publication date: 2020-10-01
Also published as: JP2020154977A; TW202046248A

Abstract

The present invention relates to a method for matching a pattern formed on the surface of a sample such as a wafer or a glass substrate, and a CAD pattern created from pattern design data. This pattern matching method includes: executing matching between a pattern on an image (200) and a corresponding CAD pattern (210); creating a histogram of gray levels within a target region (TR) which is within a region-of-interest (ROI) set within the image (200) and which is positioned inside or outside the CAD pattern (210); and determining the matching to have been successful if the number of peaks appearing in the histogram is one.

Description

Pattern matching method

The present invention relates to a method of matching a pattern formed on the surface of a sample such as a wafer or a glass substrate with a CAD pattern created from pattern design data.

The die-to-database method is a pattern matching method that matches a pattern formed on the surface of a sample such as a wafer or a glass substrate with a CAD pattern created from pattern design data. More specifically, in the die-to-database method, the coordinates of the area to be inspected are acquired from the design data, the stage on which the sample is placed is moved to those coordinates, and the image of the pattern on the sample is irradiated with an electron beam. Generated, overlay the image and the CAD pattern created from the design data, create a gray level profile of the image within the set range starting from the edge of the CAD pattern, and from the gray level profile to the pattern on the image The edge is determined, and the matching position where the bias value between the determined edge position and the edge of the corresponding CAD pattern is minimized is determined.

Japanese Unexamined Patent Publication No. 5-324863

However, in the case of repeating patterns such as line-and-space patterns and hole patterns, there are multiple matching position candidates. That is, even if the actual pattern and the CAD pattern deviate by one pitch or several pitches, the actual pattern and the CAD pattern partially match. As a result, the problem of selecting the wrong matching position may occur.

Therefore, the present invention provides a pattern matching method capable of determining the correct matching position.

In one aspect, matching of the pattern on the image with the corresponding CAD pattern is performed, within the region of interest set in the image, and within the target region located inside or outside the CAD pattern. A pattern matching method is provided in which a gray level histogram is created and the matching is determined to be successful when the number of peaks appearing in the histogram is one.

In one aspect, the peak value is greater than a preset threshold.
In one aspect, the region of interest surrounds at least one portion of the pattern on the image.
In one aspect, the CAD pattern is a repeating pattern.
In one aspect, when a plurality of peaks appear in the histogram, the relative positions of the pattern on the image and the corresponding CAD pattern are changed, and the pattern on the image and the corresponding CAD pattern are matched. Is repeated again to create a gray level histogram in the target area again.
In one aspect, a step of changing the relative position of the pattern on the image and the corresponding CAD pattern, and matching of the pattern on the image and the corresponding CAD pattern until it is determined that the matching is successful. And the step of recreating the gray level histogram in the target area are repeated.
In one aspect, the pattern matching method further comprises displaying the image and the region of interest on a display screen.
In one aspect, the pattern matching method further comprises displaying the histogram on the display screen.

In one aspect, the pattern on the image is matched with the corresponding CAD pattern, within the region of interest set in the image, and within the target region located inside or outside the CAD pattern. A computer-readable recording medium containing a program for creating a gray-level histogram and causing the computer to perform a step of determining that the matching was successful when the number of peaks appearing in the histogram is one. Provided.

According to the present invention, it is possible to accurately determine whether or not pattern matching is successful based on the number of peaks in the histogram.

It is a schematic diagram which shows one Embodiment of an image generation apparatus. It is a figure which shows an example of the SEM image and the example of the CAD pattern corresponding to the pattern appearing on the SEM image. It is a figure which shows the example which succeeded in matching the pattern on the SEM image shown in FIG. 2 with the corresponding CAD pattern. It is a figure which shows the example which failed to match the pattern on the SEM image shown in FIG. 2 with the corresponding CAD pattern. It is a figure which shows the example of the interest area and the target area set on the SEM image which the CAD pattern overlapped when the matching was successful. It is a figure which shows the example of the interest area and the target area set on the SEM image which overlapped the CAD pattern at the time of failure of matching. It is a figure which shows an example of the target area when the edge position of an actual pattern deviates greatly from the edge position of a CAD pattern. It is a figure which shows one Embodiment which performs the correction which brings the edge of a CAD pattern in an area of interest closer to the edge of an actual pattern. It is a figure which shows an example of the SEM image and the example of the CAD pattern corresponding to the pattern appearing on the SEM image. It is a figure which shows the example which succeeded in matching the pattern on the SEM image shown in FIG. 9 with the corresponding CAD pattern. It is a figure which shows the example which failed to match the pattern on the SEM image shown in FIG. 9 with the corresponding CAD pattern. It is a figure which shows the example of the interest area and the target area set on the SEM image which the CAD pattern overlapped when the matching was successful. It is a figure which shows the example of the interest area and the target area set on the SEM image which overlapped the CAD pattern at the time of failure of matching. It is a figure which shows an example of the SEM image and the example of the CAD pattern corresponding to the pattern appearing on the SEM image. It is a figure which shows the example which succeeded in matching the pattern on the SEM image shown in FIG. 14 with the corresponding CAD pattern. It is a figure which shows the example which failed to match the pattern on the SEM image shown in FIG. 14 with the corresponding CAD pattern. It is a figure which shows the example of the interest area and the target area set on the SEM image which the CAD pattern overlapped when the matching was successful. It is a figure which shows the example of the interest area and the target area set on the SEM image which overlapped the CAD pattern at the time of failure of matching. It is a figure which shows an example of the SEM image and the example of the CAD pattern corresponding to the pattern appearing on the SEM image. It is a figure which shows the example which succeeded in matching the pattern on the SEM image shown in FIG. 19 with the corresponding CAD pattern. It is a figure which shows the example which failed to match the pattern on the SEM image shown in FIG. 19 with the corresponding CAD pattern. It is a figure which shows the example of the interest area and the target area set on the SEM image which the CAD pattern overlapped when the matching was successful. It is a figure which shows the example of the interest area and the target area set on the SEM image which overlapped the CAD pattern at the time of failure of matching. It is a figure which shows an example of the SEM image and the example of the CAD pattern corresponding to the pattern appearing on the SEM image. It is a figure which shows the example which succeeded in matching the pattern on the SEM image shown in FIG. 24, and the corresponding CAD pattern. It is a figure which shows the example which failed to match the pattern on the SEM image shown in FIG. 24, and the corresponding CAD pattern. It is a figure which shows the example of the interest area and the target area set on the SEM image which the CAD pattern overlapped when the matching was successful. It is a figure which shows the example of the interest area and the target area set on the SEM image which overlapped the CAD pattern at the time of failure of matching. It is a flowchart explaining the pattern matching method which concerns on each above-described embodiment. It is a schematic diagram which shows one Embodiment of the structure of the arithmetic system.

Hereinafter, embodiments of the present invention will be described with reference to the drawings.
FIG. 1 is a schematic view showing an embodiment of an image generator. As shown in FIG. 1, the image generator includes a scanning electron microscope 50 and an arithmetic system 150. The scanning electron microscope 50 is connected to the arithmetic system 150, and the operation of the scanning electron microscope 50 is controlled by the arithmetic system 150.

The calculation system 150 includes a storage device 162 in which a database 161 and a program are stored, a processing device 163 that executes a calculation according to an instruction included in the program, and a display screen 165 that displays an image and a GUI (graphical user interface). ing. The processing device 163 includes a CPU (central processing unit) or a GPU (graphic processing unit) that performs operations according to instructions included in a program stored in the storage device 162. The storage device 162 includes a main storage device (for example, a random access memory) accessible to the processing device 163 and an auxiliary storage device (for example, a hard disk drive or a solid state drive) for storing data and programs.

The arithmetic system 150 is equipped with at least one computer. For example, the arithmetic system 150 may be an edge server connected to the scanning electron microscope 50 by a communication line, or a cloud server connected to the scanning electron microscope 50 by a communication network such as the Internet or a local network. It may be a fog computing device (gateway, fog server, router, etc.) installed in a network connected to the scanning electron microscope 50. The arithmetic system 150 may be a combination of a plurality of servers. For example, the arithmetic system 150 may be a combination of an edge server and a cloud server connected to each other by a communication network such as the Internet or a local network. In another example, the arithmetic system 150 may include a plurality of servers (computers) that are not connected by a network.

The scanning electron microscope 50 includes an electron gun 111 that emits an electron beam composed of primary electrons (charged particles), a focusing lens 112 that focuses the electron beam emitted from the electron gun 111, and an X deflector that deflects the electron beam in the X direction. It includes 113, a Y deflector 114 that deflects the electron beam in the Y direction, and an objective lens 115 that focuses the electron beam on the sample wafer 124.

The focusing lens 112 and the objective lens 115 are connected to the lens control device 116, and the operation of the focusing lens 112 and the objective lens 115 is controlled by the lens control device 116. The lens control device 116 is connected to the arithmetic system 150. The X deflector 113 and the Y deflector 114 are connected to the deflection control device 117, and the deflection operation of the X deflector 113 and the Y deflector 114 is controlled by the deflection control device 117. The deflection control device 117 is also connected to the arithmetic system 150 in the same manner. The secondary electron detector 130 and the backscattered electron detector 131 are connected to the image acquisition device 118. The image acquisition device 118 is configured to convert the output signals of the secondary electron detector 130 and the backscattered electron detector 131 into an image. The image acquisition device 118 is also connected to the arithmetic system 150 in the same manner.

The sample stage 121 arranged in the sample chamber 120 is connected to the stage control device 122, and the position of the sample stage 121 is controlled by the stage control device 122. The stage control device 122 is connected to the arithmetic system 150. A wafer transfer device 140 for mounting the wafer 124 on the sample stage 121 in the sample chamber 120 is also connected to the arithmetic system 150.

The electron beam emitted from the electron gun 111 is focused by the focusing lens 112, then focused by the objective lens 115 while being deflected by the X deflector 113 and the Y deflector 114, and is irradiated on the surface of the wafer 124. When the wafer 124 is irradiated with the primary electrons of the electron beam, the secondary electrons and backscattered electrons are emitted from the wafer 124. Secondary electrons are detected by the secondary electron detector 130, and backscattered electrons are detected by the backscattered electron detector 131. The detected secondary electron signal and backscattered electron signal are input to the image acquisition device 118 and converted into an image. The image is transmitted to the arithmetic system 150.

The design data of the pattern formed on the wafer 124 is stored in advance in the storage device 162. The design data includes pattern design information such as the coordinates of the vertices of the pattern formed on the wafer 124, the position, shape, and size of the pattern, and the number of the layer to which the pattern belongs. A database 161 is constructed in the storage device 162. The pattern design data is stored in advance in the database 161. The arithmetic system 150 can read the pattern design data from the database 161 stored in the storage device 162.

Next, an embodiment of a method of matching the pattern on the image generated by the scanning electron microscope 50 with the corresponding CAD pattern on the design data will be described. In the following description, the image generated by the scanning electron microscope 50 is referred to as an SEM image. The pattern of the wafer 124 is formed based on the design data (also referred to as CAD data). CAD is an abbreviation for computer-aided design.

The design data is data including design information of the pattern formed on the wafer 124, and specifically, the pattern such as the coordinates of the vertices of the pattern, the position, shape, and size of the pattern, and the number of the layer to which the pattern belongs. Includes design information for. The CAD pattern on the design data is a virtual pattern defined by the design information of the pattern included in the design data. In the following description, the pattern already formed on the wafer 124 may be referred to as an actual pattern.

The scanning electron microscope 50 generates an SEM image of a pattern formed on the wafer 124 on the sample stage 121. The arithmetic system 150 acquires an SEM image from the scanning electron microscope 50. FIG. 2 is a diagram showing an example of an SEM image and an example of a CAD pattern corresponding to a pattern (actual pattern) appearing on the SEM image. The pattern 205 appearing on the SEM image 200 shown in FIG. 2 is a line-and-space pattern which is an example of a repeating pattern.

The CAD pattern 210 is created by the arithmetic system 150 based on the design data of the pattern 205. The pattern 205 actually formed on the wafer 124 is formed according to the CAD pattern 210, but the corners of the actual pattern 205 on the wafer 124 may be rounded. Therefore, in order to bring the shape of the CAD pattern 210 closer to the shape of the actual pattern 205, a corner round process for rounding the corners of the CAD pattern 210 may be performed before the matching described below. ..

The calculation system 150 matches the pattern 205 on the SEM image 200 with the corresponding CAD pattern 210. Known techniques are used for matching between these patterns 205. In one example, the arithmetic system 150 superimposes the SEM image 200 and the CAD pattern 210 created from the design data, and creates a gray level profile of the SEM image 200 within a range set starting from the edge of the CAD pattern 210. , The edge of the pattern 205 on the SEM image 200 is determined from the gray level profile, and the matching position where the bias value between the determined edge position and the edge position of the corresponding CAD pattern 210 is minimized is determined. The bias value is an index value indicating the amount of deviation (distance) between the edge determined from the gray level profile and the edge of the corresponding CAD pattern 210. Bias values are calculated for all edges in the SEM image 200.

FIG. 3 is a diagram showing an example in which the pattern 205 on the SEM image 200 and the corresponding CAD pattern 210 are successfully matched. As shown in FIG. 3, the entire pattern 205 on the SEM image 200 and the entire corresponding CAD pattern 210 overlap each other. On the other hand, FIG. 4 is a diagram showing an example in which matching of the pattern 205 on the SEM image 200 with the corresponding CAD pattern 210 failed. As shown in FIG. 4, most of the pattern 205 on the SEM image 200 and most of the corresponding CAD patterns 210 overlap each other, but the

entire patterns

205 and 210 overlap each other in the X direction (for example, an electron beam). (Scanning direction), and some of the

patterns

205 and 210 do not overlap. Such matching failures are likely to occur in the case of repetitive patterns.

In the conventional algorithm, since the two

patterns

205 and 210 shown in FIG. 4 partially match, it is difficult to determine the matching failure. In other words, according to the conventional algorithm, both the matching shown in FIG. 3 and the matching shown in FIG. 4 are determined to be successful. However, the pattern 205 on the SEM image 200 shown in FIG. 4 and the CAD pattern 210 are deviated by one pitch, and to be exact, they have not been successfully matched.

Therefore, in the present embodiment, after matching the pattern 205 on the SEM image 200 with the CAD pattern 210, the success or failure of the matching is determined as follows. As shown in FIG. 5, the arithmetic system 150 sets the region of interest ROI on the SEM image 200 on which the CAD patterns 210 are superimposed. ROI is an abbreviation for Region of Interest. The region of interest ROI is a region smaller than the SEM image 200 and is located within the SEM image 200. In one embodiment, the SEM image 200 may be equally divided into a plurality of regions, and one of the plurality of regions may be used as the region of interest ROI. For example, as in the example shown in FIG. 5, the region of interest ROI may be one of four regions in which the SEM image 200 is equally divided.

The position and size of the region of interest ROI is predetermined by the arithmetic system 150 or the user. For example, the arithmetic system 150 displays the SEM image 200 on the display screen 165 shown in FIG. 1, and the user can determine the position and size of the region of interest ROI with reference to the SEM image 200 on the display screen 165. Good. In another example, the arithmetic system 150 is based on the shape of the CAD pattern 210 in the region of interest ROI, the edge length of the CAD pattern 210, the distance from the proximity pattern 205, the stretching direction of the CAD pattern 210, the apex of the CAD pattern 210, and the like. The position and size of the region of interest ROI are determined based on the calculated feature amount, or the combination of the region of interest ROI used for past pattern matching and the success / failure result of pattern matching is machine-learned as training data. The position and size of the region of interest ROI may be determined by the model.

The region of interest ROI is displayed on the display screen 165 shown in FIG. 1 together with the SEM image 200. The arithmetic system 150 may determine a plurality of region of interest candidates. The plurality of interest region candidates are displayed on the display screen 165, and the user can select the optimum one interest region ROI from the plurality of interest region candidates on the display screen 165.

The region of interest ROI is an region within the SEM image 200 and surrounds at least a part of the pattern 205 appearing in the SEM image 200. In the example shown in FIG. 5, the region of interest ROI surrounds the outermost edge of pattern 205 on the SEM image 200.

The arithmetic system 150 creates a gray level histogram in the target region TR located in the interest region ROI set in the SEM image 200 and inside or outside the CAD pattern 210. In the embodiment shown in FIG. 5, the target region TR is a region located within the region of interest ROI and outside the CAD pattern 210. As can be seen from FIG. 5, the entire target region TR is located in the region outside the pattern 205 on the SEM image 200, that is, in the space portion 206. The gray level in the target area TR includes only the gray level G1 of the space portion 206. Therefore, only one peak indicating gray level G1 appears in the histogram. The horizontal axis of the histogram represents the gray level, and the vertical axis represents the number of pixels.

The calculation system 150 displays the region of interest ROI, the target region TR, the SEM image 200, the CAD pattern 210, and the histogram on the display screen 165. The arithmetic system 150 counts the number of peaks in the histogram, and if the number of peaks is one, it is determined that the matching is successful.

FIG. 6 is a diagram showing a target area TR when matching fails and a gray level histogram in the target area TR. The position and size of the region of interest ROI are the same as the region of interest ROI when the matching shown in FIG. 5 is successful. The target region TR extends to the pattern 205 on the SEM image 200 and the space portion 206. The gray level in the target area TR includes the gray level G1 of the space portion 206 and the gray level G2 of the pattern 205. Therefore, two peaks indicating two gray levels G1 and G2 appear in the histogram.

The calculation system 150 counts the number of peaks in the histogram and determines that the matching has failed because the number of peaks is two.

In this way, the arithmetic system 150 can accurately determine whether or not the matching of the

patterns

205 and 210 is successful based on the number of peaks in the histogram.

If the matching of

patterns

205 and 210 fails (that is, if multiple peaks appear in the histogram), the arithmetic system 150 changes the relative position of the pattern 205 on the image and the corresponding CAD pattern 210 and SEM. Matching the pattern 205 on the image 200 with the corresponding CAD pattern 210 is performed again, and a gray level histogram in the target region TR is created again.

The arithmetic system 150 changes the relative position of the pattern 205 on the image and the corresponding CAD pattern 210 until it determines that the matching is successful (that is, until only one peak appears in the histogram), and the SEM image. The step of rematching the pattern 205 on the 200 with the corresponding CAD pattern 210 and the step of recreating the gray level histogram in the target region TR are repeated. Each time matching is performed, the matching position where the bias value between the edge position of the pattern 205 on the SEM image 200 and the edge of the corresponding CAD pattern 210 is minimized is determined.

In general, the edges of the actual pattern are often deformed compared to the CAD pattern. Therefore, even if pattern matching is successful, parts having different gray levels may be included in the target area TR. In such a case, multiple peaks appear in the histogram. Therefore, in order to more accurately determine the success or failure of matching, the arithmetic system 150 compares the peak value of the histogram with a preset threshold value, and the number of peaks having a value larger than the threshold value is 1. In one case, it may be determined that the matching was successful, and if there are a plurality of peaks having a value larger than the threshold value, it may be determined that the matching has failed.

As shown in FIG. 7, when the edge position of the actual pattern 205 deviates greatly from the edge position of the CAD pattern 210, a plurality of peaks may appear in the gray level histogram in the target area TR. Therefore, in such a case, as shown in FIG. 8, it is preferable to perform correction to bring the edge of the CAD pattern 210 in the region of interest ROI closer to the edge of the actual pattern 205. This correction may be performed manually by the user via the GUI while visually observing the region of interest ROI on the display screen 165, or the arithmetic system 150 may perform the position of the edge of the CAD pattern 210 and the edge of the actual pattern 205. May be automatically corrected based on the difference (bias value) of. Further, when the actual pattern undergoes shape deformation or position change due to OPE (optical proximity effect), the arithmetic system 150 is obtained from the position difference (bias value) between the edge of the CAD pattern 210 and the edge of the actual pattern 205. The target area TR may be corrected using the external image (Contour).

FIG. 9 is a diagram showing another example of the SEM image and an example of the CAD pattern 310 corresponding to the pattern (actual pattern) on the SEM image. The actual pattern 305 on the SEM image 300 shown in FIG. 9 is a line-and-space pattern which is an example of a repeating pattern, as in the embodiment shown in FIG. The details of the present embodiment, which are not particularly described, are the same as those of the embodiments described with reference to FIGS. 2 to 6, and thus the overlapping description will be omitted.

FIG. 10 is a diagram showing an example in which the pattern 305 on the SEM image 300 shown in FIG. 9 and the corresponding CAD pattern 310 are successfully matched. As shown in FIG. 10, the entire pattern 305 on the SEM image 300 and the entire corresponding CAD pattern 310 overlap each other. On the other hand, FIG. 11 is a diagram showing an example in which matching of the pattern 305 on the SEM image 300 with the corresponding CAD pattern 310 failed. As shown in FIG. 11, most of the pattern 305 on the SEM image 300 and most of the corresponding CAD patterns 310 overlap each other, but the whole of these

patterns

305 and 310 are displaced from each other in the X direction. , Part of the pattern 305 does not overlap.

FIG. 12 is a diagram showing a target region TR when matching is successful and a gray level histogram in the target region TR. In this embodiment, the position and size of the region of interest ROI is the same as in the embodiment shown in FIG. 5, but the target region TR is different from the embodiment shown in FIG. That is, the target region TR is a region located in the region of interest ROI and inside the CAD pattern 310. As can be seen from FIG. 12, the entire target region TR is located within the pattern 305 on the SEM image 300. The gray level in the target area TR includes only the gray level G3 of the pattern 305. Therefore, only one peak showing gray level G3 appears in the histogram. Since only one peak appears in the histogram, the arithmetic system 150 determines that the matching is successful.

FIG. 13 is a diagram showing a target region TR when matching fails and a gray level histogram in the target region TR. The position and size of the region of interest ROI are the same as the region of interest ROI when the matching shown in FIG. 12 is successful. The target region TR is located in the pattern 305 on the SEM image 300 and in the space portion 306 located outside the pattern 305. The gray level in the target region TR includes the gray level G3 of the pattern 305 and the gray level G4 of the space portion 306. Therefore, two peaks showing two gray levels G3 and G4 appear in the histogram. Since the two peaks appear in the histogram, the arithmetic system 150 determines that the matching has failed.

FIG. 14 is a diagram showing still another example of the SEM image and an example of the CAD pattern corresponding to the pattern (actual pattern) on the SEM image. The actual pattern 405 on the SEM image 400 shown in FIG. 14 is a hole pattern which is an example of a repeating pattern. The details of the present embodiment, which are not particularly described, are the same as those of the embodiments described with reference to FIGS. 2 to 6, and thus the overlapping description will be omitted.

FIG. 15 is a diagram showing an example in which the pattern 405 on the SEM image 400 shown in FIG. 14 and the corresponding CAD pattern 410 are successfully matched. As shown in FIG. 15, the entire pattern 405 on the SEM image 400 and the entire corresponding CAD pattern 410 overlap each other. On the other hand, FIG. 16 is a diagram showing an example in which matching of the pattern 405 on the SEM image 400 with the corresponding CAD pattern 410 failed. As shown in FIG. 16, most of the patterns 405 on the SEM image 400 and most of the corresponding CAD patterns 410 overlap each other, but the whole of these

patterns

405 and 410 are displaced from each other in the X direction. , Some of the

patterns

405 and 410 do not overlap.

FIG. 17 is a diagram showing a target region TR when matching is successful and a gray level histogram in the target region TR. In this embodiment, the location and size of the region of interest ROI is the same as in the embodiment shown in FIG. 5, but may be different. The target region TR is a region located within the region of interest ROI and outside the CAD pattern 410. As can be seen from FIG. 17, the entire target region TR is located outside the pattern 405 on the SEM image 400. The gray level in the target region TR includes only the gray level G5 in the region outside the pattern 405. Therefore, only one peak showing gray level G5 appears in the histogram. Since only one peak appears in the histogram, the arithmetic system 150 determines that the matching is successful.

FIG. 18 is a diagram showing a target region TR when matching fails and a gray level histogram in the target region TR. The position and size of the region of interest ROI are the same as the region of interest ROI when the matching shown in FIG. 17 is successful. The target region TR covers both the pattern 405 on the SEM image 400 and the region outside the pattern 405. The gray level in the target region TR includes the gray level G5 of the region outside the pattern 405 and the gray level G6 of the pattern 405. Therefore, two peaks showing two gray levels G5 and G6 appear in the histogram. Since the two peaks appear in the histogram, the arithmetic system 150 determines that the matching has failed.

FIG. 19 is a diagram showing still another example of the SEM image and an example of the CAD pattern corresponding to the pattern (actual pattern) on the SEM image. The CAD pattern 510 on the SEM image 500 shown in FIG. 19 is a rectangular hole pattern. The actual pattern 505 shown in FIG. 19 is a lower layer line and space pattern that can be seen through the upper hole pattern 507. The details of the present embodiment, which are not particularly described, are the same as those of the embodiments described with reference to FIGS. 2 to 6, and thus the overlapping description will be omitted.

When the brightness of the lower layer is almost the same as the brightness of the upper layer, the arithmetic system 150 may detect the edge of the pattern 505 of the lower layer in the pattern matching, and the matching may fail. Even in such a case, the calculation system 150 correctly determines the success or failure of the matching, and if the matching fails, repeats the matching until the matching is successful, as described above.

FIG. 20 is a diagram showing an example in which the hole pattern 507 in the upper layer on the SEM image 500 shown in FIG. 19 and the corresponding CAD pattern 510 are successfully matched. As shown in FIG. 20, the entire upper hole pattern 507 on the SEM image 500 and the entire corresponding CAD pattern 510 overlap each other. On the other hand, FIG. 21 is a diagram showing an example in which matching of the upper hole pattern 507 on the SEM image 500 with the corresponding CAD pattern 510 has failed. As shown in FIG. 21, most of the upper hole pattern 507 and most of the corresponding CAD patterns 510 overlap each other, but the whole of these

patterns

507 and 510 are offset from each other in the X direction, and the patterns Some of 507 and 510 do not overlap.

FIG. 22 is a diagram showing a target region TR when matching is successful and a gray level histogram in the target region TR. In this embodiment, the location and size of the region of interest ROI is the same as in the embodiment shown in FIG. 5, but may be different. The target region TR is a region located within the region of interest ROI and outside the CAD pattern 510. As can be seen from FIG. 22, the entire target region TR is located outside the upper hole pattern 507 and the lower line and space pattern 505 on the SEM image 500. The gray level in the target region TR includes only the gray level G7 in the outer region 508 of the upper hole pattern 507. Therefore, only one peak showing gray level G7 appears in the histogram. Since only one peak appears in the histogram, the arithmetic system 150 determines that the matching is successful.

FIG. 23 is a diagram showing a target region TR when matching fails and a gray level histogram in the target region TR. The position and size of the region of interest ROI are the same as the region of interest ROI when the matching shown in FIG. 22 is successful. The target region TR covers an outer region 508 of the upper hole pattern 507 on the SEM image 500 and a part of the lower line and space pattern 505. The gray level in the target region TR includes a gray level G7 in the outer region 508 of the upper hole pattern 507 and a part of the gray level G8 in the lower line and space pattern 505. Therefore, two peaks showing two gray levels G7 and G8 appear in the histogram. Since the two peaks appear in the histogram, the arithmetic system 150 determines that the matching has failed.

FIG. 24 is a diagram showing still another example of the SEM image and an example of the CAD pattern corresponding to the pattern (actual pattern) on the SEM image. The actual pattern 605 on the SEM image 600 shown in FIG. 24 is a line-and-space pattern which is an example of a repeating pattern. The details of the present embodiment, which are not particularly described, are the same as those of the embodiments described with reference to FIGS. 2 to 6, and thus the overlapping description will be omitted.

FIG. 25 is a diagram showing an example in which the pattern 605 on the SEM image 600 shown in FIG. 24 and the corresponding CAD pattern 610 are successfully matched. As shown in FIG. 25, the entire pattern 605 on the SEM image 600 and the entire corresponding CAD pattern 610 overlap each other. On the other hand, FIG. 26 is a diagram showing an example in which matching of the pattern 605 on the SEM image 600 and the corresponding CAD pattern 610 failed. As shown in FIG. 26, most of the patterns 605 on the SEM image 600 and most of the corresponding CAD patterns 610 overlap each other, but the whole of these

patterns

605 and 610 are in the Y direction (X direction). It is offset in the vertical direction), and some of the

patterns

605 and 610 do not overlap.

FIG. 27 is a diagram showing a target region TR when matching is successful and a gray level histogram in the target region TR. In this embodiment, the location of the region of interest ROI is different from, but may be the same, as in the embodiment shown in FIG. The target region TR is a region located within the region of interest ROI and inside the CAD pattern 610. As can be seen from FIG. 27, the entire target region TR is located within the pattern 605 on the SEM image 600. The gray level in the target area TR includes only the gray level G9 of the pattern 605. Therefore, only one peak showing gray level G9 appears in the histogram. Since only one peak appears in the histogram, the arithmetic system 150 determines that the matching is successful.

FIG. 28 is a diagram showing a target region TR when matching fails and a gray level histogram in the target region TR. The position and size of the region of interest ROI are the same as the region of interest ROI when the matching shown in FIG. 27 is successful. The target region TR is located inside the pattern 605 on the SEM image 600 and outside the pattern 605. The gray level in the target region TR includes the gray level G9 of the pattern 605 and the gray level G10 outside the pattern 605. Therefore, two peaks indicating gray levels G9 and G10 appear in the histogram. Since the two peaks appear in the histogram, the arithmetic system 150 determines that the matching has failed.

According to each of the above-described embodiments, the arithmetic system 150 can accurately determine whether or not the pattern matching is successful based on the number of peaks in the histogram. When the matching fails, the arithmetic system 150 can determine the correct matching position by repeating the matching until the matching is successful.

FIG. 29 is a flowchart illustrating the pattern matching method according to each of the above-described embodiments.
In step 1, the scanning electron microscope 50 produces an SEM image of the pattern formed on the wafer 124 on the sample stage 121.
In step 2, the arithmetic system 150 acquires an SEM image from the scanning electron microscope 50.
In step 3, the arithmetic system 150 matches the pattern on the SEM image with the corresponding CAD pattern. More specifically, the arithmetic system 150 superimposes the SEM image and the CAD pattern created from the design data, and creates a gray level profile of the SEM image within a range set starting from the edge of the CAD pattern. The edge of the pattern on the SEM image is determined from the gray level profile, and the matching position where the bias value between the determined edge position and the edge of the corresponding CAD pattern is minimized is determined.

In step 4, the arithmetic system 150 creates a gray level histogram in the target region TR located in the interest region ROI set in the SEM image and inside or outside the CAD pattern. Whether the target area TR is located inside or outside the CAD pattern is set in advance in the recipe based on factors such as the shape and type of the CAD pattern. In one embodiment, the arithmetic system 150 creates a gray level histogram in the target region located within the region of interest ROI set in the SEM image and inside the CAD pattern, and further in the SEM image. A gray level histogram may be created in the target region located within the region of interest ROI set to and outside the CAD pattern.

In step 5, the arithmetic system 150 counts the number of peaks in the histogram. The arithmetic system 150 may compare the peak value with the threshold value and count the number of peaks having a value larger than the threshold value.
In step 6, the arithmetic system 150 determines that the matching is successful if the number of peaks is one, and determines that the matching is unsuccessful if the number of peaks is two or more.

In step 7, if the matching fails, the arithmetic system 150 changes the relative position of the pattern on the image and the corresponding CAD pattern. The arithmetic system 150 rematches the pattern on the SEM image with the corresponding CAD pattern, and further creates a gray level histogram in the target region TR again.

The arithmetic system 150 changes the relative position of the pattern on the image and the corresponding CAD pattern until it determines that the matching is successful (that is, until only one peak appears in the histogram), and on the SEM image. The step of rematching the pattern with the corresponding CAD pattern and the step of recreating the gray level histogram in the target region TR are repeated. Each time matching is performed, the position of the edge of the pattern on the SEM image and the matching position where the bias value between the edge of the corresponding CAD pattern is minimized are determined.

FIG. 30 is a schematic diagram showing an embodiment of the configuration of the arithmetic system 150. The arithmetic system 150 includes a storage device 162 that stores programs and data, and a CPU (central processing unit) or GPU (graphic processing unit) that performs arithmetic according to instructions included in the program stored in the storage device 162. A processing unit 163, an input device 170 for inputting data, programs, and various information to the storage device 162, an output device 190 for outputting processing results and processed data, the Internet, a local area network, and the like. A communication device 195 for connecting to a communication network is provided.

The storage device 162 includes a main storage device 162A that can be accessed by the processing device 163, and an auxiliary storage device 162B that stores data and programs. The main storage device 162A is, for example, a random access memory (RAM), and the auxiliary storage device 162B is a storage device such as a hard disk drive (HDD) or a solid state drive (SSD).

The input device 170 includes a keyboard and a mouse, and further includes a recording medium reading device 182 for reading data from the recording medium and a recording medium port 184 to which the recording medium is connected. The recording medium is a computer-readable recording medium that is a non-temporary tangible object, and is, for example, an optical disk (for example, CD-ROM, DVD-ROM) or a semiconductor memory (for example, a USB flash drive or a memory card). is there. Examples of the recording medium reading device 182 include an optical drive such as a CD-ROM drive and a DVD-ROM drive, and a memory reader. An example of the recording medium port 184 is a USB port. The program and / or data stored in the recording medium is introduced into the arithmetic system 150 via the input device 170 and stored in the auxiliary storage device 162B of the storage device 162. The output device 190 includes a display screen 165 and a printing device 192.

The arithmetic system 150 consisting of at least one computer operates according to the instructions included in the program electrically stored in the storage device 162. That is, the arithmetic system 150 matches the pattern on the image with the corresponding CAD pattern, and is within the region of interest set in the image and within the target region located inside or outside the CAD pattern. A gray-level histogram of is created, and if the number of peaks appearing in the histogram is one, the step of determining that the matching is successful is performed.

The program for causing the arithmetic system 150 to execute these steps is recorded on a computer-readable recording medium which is a non-temporary tangible object, and is provided to the arithmetic system 150 via the recording medium. Alternatively, the program may be input from the communication device 195 to the arithmetic system 150 via a communication network such as the Internet or a local area network.

The above-described embodiment is described for the purpose of allowing a person having ordinary knowledge in the technical field to which the present invention belongs to carry out the present invention. Various modifications of the above embodiment can be naturally made by those skilled in the art, and the technical idea of the present invention can be applied to other embodiments. Therefore, the present invention is not limited to the described embodiments, but is construed in the broadest range according to the technical idea defined by the claims.

The present invention can be used as a method for matching a pattern formed on the surface of a sample such as a wafer or a glass substrate with a CAD pattern created from pattern design data.

50 Scanning electron microscope 111 Electron gun 112 Condensing lens 113 X deflector 114 Y deflector 115 Objective lens 116 Lens control device 117 Deflection control device 118 Image acquisition device 120 Sample chamber 121 Sample stage 122 Stage control device 124 Wafer 130 Secondary electron detection Instrument 131 Reflected electron detector 140 Wafer transfer device 150 Computational system 161 Database 162 Storage device 163 Processing device 165

Display screen

200, 300, 400, 500, 600

SEM image

205, 305, 405,505,605 Pattern 210 on the image, 310,410,510,610 CAD pattern ROI area of interest TR target area

Claims

Matching the pattern on the image with the corresponding CAD pattern,
Create a gray-level histogram within the region of interest set in the image and within the target region located inside or outside the CAD pattern.
A pattern matching method for determining that the matching is successful when the number of peaks appearing in the histogram is one.
The pattern matching method according to claim 1, wherein the value of the peak is larger than a preset threshold value.
The pattern matching method according to claim 1 or 2, wherein the region of interest surrounds at least one part of the pattern on the image.
The pattern matching method according to any one of claims 1 to 3, wherein the CAD pattern is a repeating pattern.
When a plurality of peaks appear in the histogram, the relative positions of the pattern on the image and the corresponding CAD pattern are changed, and matching between the pattern on the image and the corresponding CAD pattern is performed again. The pattern matching method according to any one of claims 1 to 4, wherein the gray level histogram in the target area is recreated.
Until it is determined that the matching is successful, the step of changing the relative position between the pattern on the image and the corresponding CAD pattern, and the matching between the pattern on the image and the corresponding CAD pattern are performed again. The pattern matching method according to claim 5, wherein the step and the step of recreating the gray level histogram in the target area are repeated.
The pattern matching method according to any one of claims 1 to 6, further comprising a step of displaying the image and the region of interest on a display screen.
The pattern matching method according to claim 7, further comprising a step of displaying the histogram on the display screen.
Matching the pattern on the image with the corresponding CAD pattern,
Create a gray-level histogram within the region of interest set in the image and within the target region located inside or outside the CAD pattern.
A computer-readable recording medium containing a program for causing a computer to perform a step of determining that the matching was successful when the number of peaks appearing in the histogram is one.