JP4021084B2 - Electron microscope and inspection method - Google Patents

Description

[0001]
BACKGROUND OF THE INVENTION
The present invention relates to an electron microscope and an inspection method for inspecting pattern defects and foreign matter or storing observation information on a fine pattern such as an LSI wafer, TFT, or mask.
[0002]
[Prior art]
With the recent progress of semiconductor manufacturing technology, in semiconductor device manufacturing inspection, defects and foreign substances that need to be inspected (hereinafter, defects and foreign substances are collectively referred to simply as defects) are miniaturized, and an optical microscope is used. It is difficult to detect or observe defects. Therefore, conventionally, in high-resolution observation of defects, the defect occurrence location is specified in advance using a defect inspection device (or foreign matter inspection device), and based on information such as the coordinate origin and defect coordinates provided by the defect inspection device, High-resolution observation of defects is performed using an electron microscope with a coordinate function. Japanese Patent Laid-Open No. 9-139406 is a patent that takes these systemizations into consideration. In this electron microscope system, the field of view of the electron microscope is moved based on the defect information provided by the inspection apparatus, and the obtained secondary electron image for inspection and the reference obtained from the equivalent in-chip coordinates of the adjacent chip. Pattern matching, difference processing, and the like are performed between a total of three images including two secondary electron images, and defects are automatically detected as singular points.
[0003]
[Problems to be solved by the invention]
In order to observe defects with high resolution using the electron microscope system described above, it is necessary to specify a defect position in advance using a defect inspection apparatus. Also, when inspecting a minute defect that cannot be detected by an optical defect inspection apparatus in the manufacturing process of a semiconductor device, or when it is necessary to inspect only a certain position on a substrate of a semiconductor device, The defect occurrence location cannot be specified, and the observation field of the electron microscope is moved to a specific area to be inspected by a human, and the defect is visually detected and observed. In such a case, there is a problem that automatic observation as in the above-described system cannot be performed because the defect is not identified by the defect inspection apparatus.
[0004]
The present invention has been made in view of such problems of the prior art, and is capable of automatically performing defect detection and high-resolution observation without the need to specify a defect position using an inspection apparatus in advance. It is an object to provide a microscope and an inspection method.
The present invention also provides an electron microscope that enables defect detection and high-resolution observation in an inspection region without irradiating a reference region other than the inspection region on the sample with an unnecessary electron beam and damaging it, and The purpose is to provide an inspection method.
[0005]
[Means for Solving the Problems]
The present inventors can regard a defect of a pattern constituted by repeating the same fine pattern, such as a semiconductor memory formed on a semiconductor wafer, or a foreign substance attached to the pattern as a periodic pattern disturbance. Focusing on what can be done, the present invention has been achieved.
[0006]
That is, the electron microscope of the present invention automatically detects an inspection point registration means for registering the inspection position of the sample to be inspected on the electron microscope and an abnormal part of the inspection image captured at the registered inspection position as a singular point. Singular point automatic detection means, and observation processing means for obtaining information about the singular points detected by the singular point automatic detection means. The inspection image is captured using secondary electrons, reflected electrons, or secondary electrons and reflected electrons emitted from the sample by electron beam irradiation. The electron microscope may include visual field automatic setting means for automatically setting a microscope visual field region based on prior information regarding the abnormal part. Here, the prior information regarding the abnormal part includes inspection coordinates, a generated defect size, a minimum defect detection size, a defect category, a cluster, a generated process name, and the like. Of these pieces of prior information, the inspection coordinates are used to set the field of view of the electron microscope. In addition, the generated defect size, minimum defect detection size, category, cluster, etc. are used to set the field of view of the electron microscope, so that singularity automatic detection can be performed by selecting only an arbitrary generation process, size, cluster, etc. Also used for.
[0007]
The observation processing means may have a function of storing observation information and incidental information about the detected singular point. Here, the observation information refers to image information, and the incidental information includes the size and area of defects and foreign matter, the projection length in the X direction, the projection length in the Y direction, and the category.
The observation processing means can also have a function of changing the observation conditions of the electron microscope based on the detection result by the singular point automatic detection means. With this function, for example, the observation magnification of the electron microscope can be changed so that the whole can be observed according to the size, distribution, and spread of the detected singular points. For example, when the detected singular points are widely distributed, the observation magnification is lowered so that the whole is in the visual field.
[0008]
The singularity automatic detection means can detect the singularity using the period information of the pattern formed on the sample to be inspected. Further, the singularity automatic detection means can detect the singularity by detecting the disturbance of the periodic pattern formed on the sample to be inspected.
More specifically, the singularity automatic detection means creates a plurality of partial images obtained by dividing the inspection image by one or more periods of the pattern using the period information of the pattern formed on the inspection sample. It is possible to detect a singular point by performing a difference process between corresponding small regions between a plurality of partial images.
[0009]
Alternatively, the singularity automatic detection means divides the inspection image into a plurality of partial images of the same size, and within each partial image, a small pattern separated by one or more periods of the pattern formed on the sample to be inspected. Difference processing between regions is performed to obtain a sum of differences, and a singular point can be detected as a singular point existing in a partial image in which the sum of the differences is maximized.
[0010]
In the electron microscope, the small region may be composed of one pixel or a plurality of pixels. The electron microscope may be a scanning electron microscope, but may be other types of electron microscopes such as a transmission type and a scanning transmission type.
Further, the inspection method of the present invention is an inspection method for detecting a singular point of a sample to be inspected in which a periodic pattern is formed. By using pattern periodic information, pattern disturbance is detected, and the pattern is disturbed. The position is detected as a singular point.
[0011]
The inspection method of the present invention is also an inspection method for detecting a singular point on an inspection image obtained by imaging an inspection sample on which a periodic pattern is formed with an electron microscope. A plurality of partial images divided by a plurality of periods are created, and a singular point is detected by performing a difference process between corresponding small regions between the plurality of partial images.
[0012]
The inspection method of the present invention is also an inspection method for detecting singular points on an inspection image obtained by imaging an inspection sample on which a periodic pattern is formed with an electron microscope. In each partial image, a difference process between small regions separated by one cycle or a plurality of cycles of the pattern formed on the sample to be inspected is performed to obtain the sum of the differences. A singular point exists in the partial image having the maximum sum.
[0013]
In the inspection method, the small area may be composed of one pixel or a plurality of pixels.
The present invention does not require information on the occurrence of defects or foreign matter by the defect inspection apparatus or foreign substance inspection apparatus, and detects defects in the periodic pattern in the electron microscope image (inspection image) of the inspection area on the sample. And the location of foreign objects. As described above, since the abnormal portion of the pattern is detected as a singular point only from the electron microscope image of the inspection region, a reference image to be compared with the electron microscope image of the inspection region is not required. Accordingly, since it is not necessary to irradiate the region on the sample other than the region to be inspected with the electron beam in order to acquire the reference image, it is possible to minimize damage to the sample due to the electron beam irradiation.
[0014]
In one embodiment of the present invention, for example, a defect existing on a semiconductor wafer is taken into a computer with an optimal inspection and observation magnification of a secondary electron image in an arbitrary area on the wafer, and a design rule is obtained from the taken secondary electron image. By using the detection method using pattern period information configured on the wafer, etc., the location of the defect is automatically detected as a singular point, and the singular point is automatically observed at the optimum magnification. Is stored as electronic information. Thereby, it becomes possible to automatically perform defect detection (including foreign matter detection) or observation from observation to image storage in an arbitrary region on the sample to be inspected.
[0015]
DETAILED DESCRIPTION OF THE INVENTION
Embodiments of the present invention will be described below with reference to the drawings. Hereinafter, a defect inspection of a memory pattern formed on a semiconductor wafer will be described as an example. However, the present invention is not limited to the pattern defect on the semiconductor wafer, but can of course be applied to the inspection of a defect or a foreign substance on an arbitrary sample to be inspected having a periodic pattern.
[0016]
FIG. 1 is a block diagram showing the configuration of an electron microscope according to the present invention. The electron microscope 4 includes an inspection point registration unit 1, a singular point automatic detection unit 2, and a singular point information processing / observation processing unit 3. The electron microscope 4 can typically be a scanning electron microscope, but may be other types of electron microscopes such as a transmission type and a scanning transmission type. The operator of the electron microscope registers the inspection point on the semiconductor wafer to be inspected on the electron microscope by the inspection point setting means 1. The electron microscope 4 automatically moves the visual field to the registered inspection point. Then, the singular point automatic detection means 2 automatically detects singular points (defects and foreign matters), and the information processing / observation processing means 3 processes the image information of the detected singular points.
[0017]
The information processing / observation processing means 3 acquires and stores an electron microscope image of the detected singular point, the size, area, X-direction projection length, and Y-direction projection length of the singular point from the acquired image information. Processing for acquiring and storing incidental information such as a category is performed. The information processing / observation processing means 3 also observes observation conditions such as the observation magnification of the electron microscope 4 so that the whole can be observed according to the size, distribution and spread of the singular points detected by the singular point automatic detection means 2. To change. Note that the inspection point to be registered in the electron microscope may be determined using information on defective foreign matter coordinates obtained by using the abnormal part inspection apparatus.
[0018]
FIG. 2 is a flowchart for explaining a processing procedure of an example of defect detection and high-resolution observation processing according to the first embodiment of the present invention. First, the sample is aligned with the electron microscope sample stage based on the design data or the coordinate information provided by the abnormal part inspection apparatus (S11). Next, inspection points are registered on the electron microscope (S12). Inspection points are registered by creating a map of a semiconductor wafer on an electron microscope and registering coordinate data of inspection points by an operator, or by registering coordinates obtained from an abnormal part inspection apparatus.
[0019]
FIG. 3 is a diagram illustrating an example of an inspection point registration screen. A method for registering and setting inspection points will be described with reference to FIG. A wafer map 32 of a semiconductor wafer to be inspected is created in an inspection point setting window 37 of the electron microscope, and an inspection chip 33 on the map 32 is designated. In the figure, the inspection chip 33 is shaded and the non-inspection chip 34 is displayed in white. Further, the inspection coordinates (X, Y) in the inspection chip 33 are input to the in-chip coordinate value input area 35, and the inspection point is registered in the electron microscope with the inspection point setting button 36. The inspection coordinates in the inspection chip 33 may be set using a mouse cursor or the like on the image while looking at the image of the chip of the electron microscope. In this case, the coordinates in the inspection chip are automatically set. The inspection point registration method is not limited to the method shown in FIG. 3, and any method may be used as long as the coordinates can be set.
[0020]
Returning to FIG. 2, when a pattern is observed on a substrate to be inspected with an electron microscope, such as a semiconductor wafer in the course of manufacturing, the equivalent in-chip coordinates of the chip adjacent to the chip including the inspection point or in the adjacent cell The field of view of the electron microscope is moved to the reference point with the coordinates in the equivalent cell of (2) as the reference point (S13), and the secondary electron image is taken in the electronic computer as the reference image (S14). The observation magnification of the electron microscope automatically sets the observation magnification at which the minimum defect size desired by the operator can be detected because the minimum detectable defect size depends on the observation magnification of the electron microscope. Also, if the inspection point is a coordinate obtained from the abnormal part inspection device, the coordinate error of the inspection device, the coordinate error of the electron microscope, and the maximum magnification that allows the coordinate error between the inspection device and the electron microscope are set. For example, in the case of a large-size defect, the maximum magnification is changed so that the defect fits in the image. Alternatively, if the category indicating the type of defect, such as a scratch, peel, or foreign object, is a densely distributed category such as a scratch, if the same category exists in an arbitrarily set peripheral area, the defect existing area is It is possible to change to the included magnification.
[0021]
Next, the field of view of the electron microscope is moved to the inspection point registered on the electron microscope (S15). Thereafter, a secondary electron image of the inspection point is captured as an inspection image at the same observation magnification as that at the time of acquiring the reference image (S16), and image comparison is performed between the two images by a pattern matching method or the like, and a singular point (defect ) Is specified (S17). In the subsequent determination of step 18, if a singular point is detected, the detected point is set as the observation center, set to the maximum observable magnification, and information processing / observation processing of the singular point such as image storage and length measurement is performed. (S19). The observation magnification at this time can be set to a preset observation magnification. Thereafter, the observation image at the optimum magnification is stored on the electronic computer as electronic information. In addition to the image, it is possible to simultaneously store incidental information such as the size of the detected singular point (defect) and the projection length (horizontal direction and vertical direction).
[0022]
If the presence of a singular point cannot be confirmed in the process of step 17, the process proceeds from step 18 to step 20 to determine whether or not to re-inspect the inspection point. Whether the re-inspection is performed may be determined by the operator each time, or the re-inspection may be performed all the time. Which mode is selected can be set in advance. In the case of re-examination, the process returns from step 20 to step 13 to acquire the reference image and the inspection image again and automatically detect the singularity. At this time, the chip for acquiring the reference image may be changed to another chip. If re-inspection is not performed, the process proceeds from step 20 to step 21 as it is. Before proceeding from step 20 to step 21, an inspection image in which no singular point is recognized may be stored so that re-checking can be performed later. If desired by the operator, the reference image is stored together with the inspection image.
[0023]
Next, proceeding to step 21, it is determined whether or not the inspection point where the singular point detection has just been performed is the last inspection point registered in step 12, and the processing from step 13 is performed until the inspection is completed for all inspection points. repeat. Here, the reference image and the inspection image are not necessarily a secondary electron image, and may be a reflected electron image, or may be a mixed image of reflected electrons and secondary electrons. The singular point automatic detection process executed in step 17 is not limited to the pattern matching process between two images, and any method can be used as long as the pattern singular point can be automatically detected.
[0024]
Next, a second embodiment of the present invention will be described with reference to FIGS. FIG. 4 is a diagram for explaining an automatic detection process for a singular point according to this embodiment, and FIG. 5 is a flowchart showing a process flow. In the second embodiment, an abnormal part in which the periodicity of a pattern is disturbed is detected automatically as a singular point from only an inspection image without using a reference image. Registration of inspection points is performed as described above with reference to FIG.
[0025]
The semiconductor memory formed on the semiconductor wafer is configured by repeating the same pattern as schematically shown in FIG. In the automatic detection of singular points of the present embodiment, the position information of the inspection points set in advance as described above is read (FIG. 5, S31), and the field of view of the electron microscope is moved to one of the inspection points (S32). ), An inspection image (secondary electron image) 17 of the inspection point is captured on the electronic computer (S33). Now, it is assumed that the defect 18 exists in the inspection image 17 as schematically shown in FIG. Next, as shown in FIG. 4B, the inspection image is divided into a large number of small regions 19 (S34). The small area 19 may be composed of one pixel, or one small area 19 may be composed of a plurality of pixels. When one small region is configured by a plurality of pixels, for example, one small region can be configured by m × m pixels, but the shape of the small region is not necessarily square. Further, it is not necessary to determine the size and shape of the small region 19 in particular in association with the pattern period of the semiconductor memory. Each small area 19 is quantified by a gray level value obtained by dividing the image density (secondary electron intensity) of the small area into an arbitrary gradation (S35).
[0026]
Next, as shown in FIG. 4C, the inspection image 17 is divided into windows 20 having the same shape including an appropriate number of small regions 19 (S36). Then, based on the repetition information (period information) of the pattern formed on the semiconductor wafer such as the design rule, as shown in FIG. Calculate the difference in gray level values. At this time, it is preferable that the window 20 includes a repeating pattern of two cycles or more. Thus, in each window 20, the sum of the differences in gray level values between the small areas separated by one period in the window is calculated (S37). The processing in step 37 is performed until it is determined in step 38 that the processing has been completed for all windows.
[0027]
If there is no defect in the inspection image 17, the same image, that is, a small area 19 having the same gray level appears every window in the window 20. Therefore, the difference in gray level value between the small areas is ideal. Thus, it becomes 0. On the other hand, if there is a defect in the inspection image 17, the gray level of the small areas 19 separated by one period in the window 20 is different, and thus the difference in gray level values between the small areas 19 increases. Therefore, the window showing the feature that the sum of the differences in gray level values between the small areas is the largest is regarded as a defective window, and the center of the electron microscope field of view is moved to the center of the singular window (S39). Is changed to an optimum magnification capable of capturing the image, an observation process is performed as shown in FIG. 4E, and the image is stored (S40). At this time, information processing for acquiring supplementary information about the singular point such as the size, area, X-direction projection length, Y-direction projection length, and category of the singular point is performed, and the result is stored together with the image. May be. Thereafter, it is determined whether or not the inspection point is the last inspection point read in step 31 (S41). If there is an inspection point that has not been inspected, the process returns to step 32 to be the next inspection point. Move the field of view and perform the same process.
[0028]
Note that the distance between the small regions 19 that take the gray level value difference within the window 20 is not necessarily limited to one period, and may be any period such as two periods or three periods within a range not exceeding the size of the window 20. It can be set.
The singularity automatic detection method of the present embodiment can be similarly applied to automatic inspection of unprocessed semiconductor wafers by arbitrarily setting the period. Further, the inspection image 17 is not necessarily a secondary electron image, and may be a reflected electron image, a mixed image of reflected electrons and secondary electrons, or the like.
[0029]
Next, a third embodiment of the present invention will be described with reference to FIG. The third embodiment is an embodiment in which a plurality of windows are created from an inspection image based on periodic information of a pattern formed on a semiconductor wafer such as a design rule, and a singular point is automatically detected. The inspection points to be inspected of the semiconductor wafer are set on the electron microscope, for example, as described in FIG.
[0030]
As in the previous embodiment, the secondary electron image at the inspection point of the semiconductor memory pattern formed on the wafer is captured as an inspection image 17 on the electronic computer, and the inspection image is obtained from one pixel or a certain number of pixels. After being divided into a large number of small regions 19, the secondary electron intensity of each small region 19 is quantified by a gray level value obtained by dividing the small region 19 into arbitrary gradations. Next, a plurality of windows 31a and 31b divided from the inspection image 17 in arbitrary cycle units are created. Since the windows 31a and 31b are created based on the same period, the same pattern exists at the corresponding position of each window, and it is not necessary to perform alignment such as pattern matching before the difference processing. Therefore, the gray level value difference process is performed between the corresponding small areas 19 of the windows 31a and 31b, and the small area having the largest difference is detected as a singular point. Thereafter, the center of the electron microscope field of view is moved to the detected singular point, the observation magnification is changed to the optimum magnification, an electron microscope image is acquired, and the acquired observation image is stored on the electronic computer as electronic information. At this time, information processing for acquiring supplementary information about the singular point such as the size, area, X-direction projection length, Y-direction projection length, and category of the singular point is performed, and the result is stored together with the image. May be.
[0031]
In the third embodiment, when the difference processing between the two windows 31a and 31b is performed, it is possible to specify a small area having a large difference, but which window has a singular point (defect) exists. It cannot be specified. However, when combined with the second embodiment that detects the presence or absence of a singular point in a window by taking the sum of the differences in gray level values between corresponding small regions separated by one cycle or several cycles within one window, It can be determined that there is a singular point on the window side showing the feature that the sum of the differences of the gray level values between the regions is the largest. As described above, when the third embodiment and the second embodiment are combined, the number of windows required for specifying a singular point (defect) is at least two. Thereby, it is possible to acquire an image with the defect centered on the screen with higher accuracy than in the case of the second embodiment alone.
[0032]
The detection method of the third embodiment is also effective for automatic observation and automatic inspection of an unprocessed semiconductor wafer by arbitrarily setting the period. Further, the inspection image does not need to be a secondary electron image, and may be a reflected electron image, a mixed image of a reflected electron and a secondary electron image, or the like.
[0033]
【The invention's effect】
According to the present invention, it is possible to automatically perform processing from detection or observation of foreign matter and defects in an arbitrary region to image storage.
Further, by detecting a singular point from a single inspection image without using a reference image, it is possible to prevent the sample from being irradiated with an electron beam and the number of stage movements.
[Brief description of the drawings]
FIG. 1 is a block diagram showing a configuration of an electron microscope according to the present invention.
FIG. 2 is a flowchart of an example of defect detection and high-resolution observation processing according to the first embodiment of the present invention.
FIG. 3 is a diagram showing an example of an inspection point registration screen.
FIG. 4 is a diagram for explaining a method for automatically detecting a singular point according to a second embodiment of the present invention.
FIG. 5 is a flowchart showing a process flow of a second embodiment.
FIG. 6 is a diagram for explaining a method for automatically detecting a singular point according to a third embodiment of the present invention.
[Explanation of symbols]
DESCRIPTION OF SYMBOLS 1 ... Inspection point setting means, 2 ... Singular point automatic detection means, 3 ... Singular point information processing and observation processing means, 4 ... Electron microscope, 17 ... Inspection image, 18 ... Defect, 19 ... Small area, 20 ... Window, 31a, 31b ... window, 32 ... wafer map, 33 ... inspection chip, 34 ... non-inspection chip, 35 ... in-chip coordinate input area, 36 ... inspection point setting step, 37 ... inspection point setting window

Claims (3)

Inspection point setting means for registering the electron microscope field of view at the inspection position on the specimen to be inspected, and automatically moving the visual field to the registered inspection position and automatically detecting the abnormal part of the inspection image captured at the inspection position as a singular point Singular point automatic detection means for automatically detecting, and observation processing means for obtaining information about the singular points detected by the singular point automatic detection means ,
The singular point automatic detection means divides the inspection image into a plurality of partial images of the same size, and is separated by one period or a plurality of periods of a pattern formed on the sample to be inspected in each partial image. An electron microscope characterized by performing a difference process between small regions to obtain a sum of differences, and detecting a singular point as a singular point existing in a partial image in which the sum of the differences is maximized .   In an inspection method for detecting a singular point on an inspection image obtained by imaging an inspection sample on which a periodic pattern is formed with an electron microscope, the inspection image is divided into a plurality of partial images of the same size, In the partial image, a difference image between small areas separated by one cycle or a plurality of cycles of the pattern formed on the specimen to be inspected is obtained to obtain the sum of the differences, and the partial image in which the sum of the differences is maximized An inspection method characterized by detecting a singular point assuming that a singular point exists in the inside. The inspection method according to claim 2, wherein the small area includes a plurality of pixels.

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