JP2011196728A - Inspection device and inspection method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an inspection device and an inspection method, capable of accurately determining changes in dimension and position of a pattern formed in an object to be inspected.SOLUTION: In the inspection method of illuminating a sample in which a pattern is formed with light, obtaining an optical image by forming an image of the sample on an image sensor, and determining that the optical image has a defect when the difference in dimension of pattern between the optical image and a reference image exceeds a predetermined range, at least one of a change in intensity of the light with time and a change in sensitivity of an image sensor with time is obtained, a relationship between this change with time and a change in the difference in dimension of pattern with time is determined, and the difference in dimension of pattern is corrected. It is preferred that the change in sensitivity with time of the image sensor is determined by moving the image sensor to the other pattern provided in the sample for each predetermined time while obtaining an optical image of whole sample by relatively moving the image sensor with respect to the sample.

Description

  The present invention relates to an inspection apparatus and an inspection method, and more particularly to an inspection apparatus and an inspection method used for dimensional inspection of a pattern formed on an inspection target such as a mask.

  In recent years, the circuit line width required for a semiconductor element has become increasingly narrower as the large scale integrated circuit (LSI) is highly integrated and has a large capacity. The semiconductor element uses an original pattern pattern (a mask or a reticle, which will be collectively referred to as a mask hereinafter) on which a circuit pattern is formed, and the circuit is exposed and transferred onto a wafer by a reduction projection exposure apparatus called a stepper. Manufactured by forming. For manufacturing a mask for transferring such a fine circuit pattern onto a wafer, an electron beam drawing apparatus capable of drawing the fine pattern is used. Attempts have also been made to develop a laser beam drawing apparatus for drawing using a laser beam. The electron beam drawing apparatus is also used when drawing a circuit pattern directly on a wafer.

  Yield improvement is indispensable for the manufacture of LSIs that require a large amount of manufacturing costs. On the other hand, recent typical logic devices are required to form a pattern having a line width of several tens of nanometers. Here, as a major factor for reducing the yield, there are mask pattern defects and variations in process conditions during exposure transfer. Until now, with the miniaturization of the LSI pattern dimension formed on a semiconductor wafer, it has been performed to absorb the variation margin of process conditions by increasing the dimensional accuracy of the mask. For this reason, in mask inspection, the dimensions that must be detected as pattern defects are miniaturized, and it is necessary to detect position errors of extremely small patterns. For this reason, high inspection accuracy is required for an inspection apparatus for inspecting the dimensions of a transfer mask used in LSI manufacturing.

  As a method for detecting a pattern defect, there are a die-to-die inspection method and a die-to-database inspection method. The die-to-die inspection method compares the same patterns of chips with different masks when a plurality of chips having the same pattern configuration are arranged in a part or the whole of the same mask. Inspection method. According to this method, since the mask patterns are directly compared, highly accurate inspection can be performed with a relatively simple apparatus configuration. However, it is impossible to detect a defect that exists in common in both patterns to be compared. On the other hand, the die-to-database inspection method is an inspection method in which reference data generated from design pattern data used for mask manufacture is compared with an actual pattern on the mask. Since a mechanism for generating a reference image is required, the apparatus becomes large, but a strict comparison with design pattern data can be performed. This method can be used only when there is only one chip transfer area in one mask.

  In die-to-database inspection, light emitted from a light source is irradiated onto a mask to be inspected via an optical system. The mask is placed on a table, and light irradiated as the table moves scans the mask. The light transmitted or reflected through the mask forms an image on the image sensor via the lens, and the optical image captured by the image sensor is sent to the comparison unit as measurement data. In the comparison unit, the measurement data and the reference data are compared according to an appropriate algorithm. If these data do not match, it is determined that there is a defect (see, for example, Patent Document 1).

  In a conventional inspection apparatus, it is determined whether a mask pattern image obtained by capturing an optical image with an image sensor is correct. However, in recent masks that have been miniaturized, the reference accuracy and inspection apparatus generated based on design pattern data can be reduced by increasing the required accuracy for the line width of the mask pattern and the gap distance between adjacent patterns. It is difficult to determine whether or not the image is a defect only by comparison with the photographed pattern image. Specifically, there is a problem that the measurement data varies due to the change in the intensity of the measurement light and the change in the sensitivity of the image sensor when an optical image is captured, and an accurate difference from the reference data cannot be obtained.

  For example, Patent Document 2 discloses a method for obtaining a difference between these pattern dimensions by comparing an optical image with a reference image. In Patent Document 2, an inspection region is formed by dividing a pattern formed on a mask, and the line width data for each pixel is compared by comparing the line width data for each pixel captured in the sensor data for each inspection region. Find the difference. The frequency of the obtained line width difference is tabulated, and an average value is calculated from the tabulated result to obtain an inspection value. Then, the inspection value is compared with a threshold value set from the reference data. According to this method, since the line width inspection is determined by obtaining the average value of the differences in the line widths calculated in a certain inspection region, it is possible to reduce the variation that has occurred when obtaining each pixel. .

  Further, in Patent Document 3, a dimensional difference between an optical image and a reference image is obtained, the optical image is divided into a plurality of measurement regions, and dimensional errors are totaled for each block. Remove block aggregation results. Then, a correction value of the optical image is obtained, the optical image is corrected based on the correction value, and the mask pattern is inspected by comparing the corrected optical image with the reference image. According to this method, even if a defective part such as a chip is present in the pattern, the total result in which the defective part is present is removed, so that the reliability with respect to the pattern dimension difference between the optical image and the reference image can be improved. it can.

JP 2008-112178 A Japanese Patent No. 3824542 Japanese Patent No. 3732794 Specification

  However, Patent Documents 2 and 3 do not describe or suggest a problem in which measurement data fluctuates due to a change in the intensity of measurement light or a change in sensitivity of the image sensor when an optical image is captured. Therefore, the difference between the optical image and the reference image cannot be obtained accurately, and it cannot be accurately determined whether or not the defect is a defect. The present invention has been made in view of these points. That is, the object of the present invention is to accurately determine the variation in the size and position of the pattern formed on the inspection object even if the intensity of the measurement light or the sensitivity of the image sensor changes when taking an optical image. And an inspection method are provided.

  Other objects and advantages of the present invention will become apparent from the following description.

A first aspect of the present invention is an inspection apparatus that illuminates a sample on which a pattern is formed, forms an image of the sample on an image sensor, and inspects the dimensions of the pattern formed on the sample.
A part for obtaining an optical image of a sample from an image sensor;
Comparing the optical image with the reference image, and having a portion that determines a defect when the dimensional difference of the pattern in these images exceeds a predetermined range,
The part that is determined to be a defect is a part that acquires the apparent dimensional difference of the pattern from the optical image and the reference image,
A portion for obtaining a temporal variation of at least one of light intensity and image sensor sensitivity;
A portion for obtaining a relationship between temporal variation of at least one of light intensity and image sensor sensitivity and temporal variation of a dimensional difference between patterns;
And a portion for obtaining a true dimensional difference of the pattern by subtracting a temporal variation of the dimensional difference of the pattern from the apparent dimensional difference.

  In the first aspect of the present invention, the reference image is a reference image created from pattern design data or an optical image of the same pattern as the pattern in a region different from the optical image on the sample.

The second aspect of the present invention illuminates a sample on which a pattern is formed, forms an image of the sample on an image sensor to obtain an optical image, and compares the optical image with a reference image to obtain these images. In the inspection method for determining a defect when the dimensional difference in the pattern exceeds a predetermined range,
It is characterized in that at least one temporal variation of the light intensity and the image sensor sensitivity is acquired, and the relationship between the temporal variation and the temporal variation of the pattern dimension difference is obtained to correct the pattern dimension difference. It is what.

In other words, the second aspect of the present invention can be expressed as follows.
That is, in an inspection method in which a sample on which a pattern is formed is illuminated with light, an image of the sample is formed on an image sensor via an optical system, and the dimensions of the pattern formed on the sample are inspected.
Obtaining an optical image of the sample from the image sensor;
Comparing an optical image with a reference image to obtain an apparent dimensional difference of patterns in these images;
Obtaining a temporal variation of at least one of light intensity and image sensor sensitivity;
Obtaining a relationship between temporal variation of at least one of light intensity and image sensor sensitivity and temporal variation of a dimensional difference between patterns;
Obtaining the true dimensional difference of the pattern by subtracting the temporal variation of the dimensional difference of the pattern from the apparent dimensional difference;
And a step of determining a defect when the true dimensional difference exceeds a predetermined range.

  In the second aspect of the present invention, by moving the image sensor relative to the sample, the image sensor is placed in another pattern provided in the sample every predetermined time while acquiring an optical image of the entire sample. It is preferable to move the image sensor to obtain a temporal variation in sensitivity of the image sensor.

  In the second aspect of the present invention, the reference image is a reference image created from pattern design data, or an optical image of the same pattern as the pattern in a region different from the optical image on the sample.

  ADVANTAGE OF THE INVENTION According to this invention, the inspection apparatus and the inspection method which can obtain | require the fluctuation | variation of the dimension of the pattern formed in the test object and a position correctly are provided.

It is a block diagram of the inspection apparatus in this Embodiment. It is a conceptual diagram which shows the flow of the data in this Embodiment. It is a figure explaining a filter process. It is a figure explaining the acquisition procedure of mask measurement data. It is an example which shows a time-dependent change of the light intensity detected with the image sensor. It is explanatory drawing of the method of calculating | requiring a true pattern dimension error measured value. It is a figure which shows a mode that the conventional pattern dimension error measured value changes for every measurement. FIG. 8 is a diagram obtained by re-plotting the apparent pattern dimension error measurement value of FIG. It is a figure explaining operation | movement of the comparison circuit in this Embodiment.

  FIG. 1 is a configuration diagram of an inspection apparatus according to the present embodiment. In this embodiment mode, a mask used in a photolithography method or the like is an inspection target.

  As illustrated in FIG. 1, the inspection apparatus 100 includes an optical image acquisition unit A and a control unit B.

  The optical image acquisition unit A includes a light source 103, an XYθ table 102 that can move in the horizontal direction (X direction, Y direction) and the rotation direction (θ direction), an illumination optical system 170 that constitutes a transmissive illumination system, and magnification optics. A system 104, a photodiode array 105, a sensor circuit 106, a laser length measurement system 122, and an autoloader 130 are included.

  In the control unit B, a control computer 110 that controls the entire inspection apparatus 100 is provided with a position circuit 107, a comparison circuit 108, a reference circuit 112, a development circuit 111, and an autoloader control circuit 113 via a bus 120 serving as a data transmission path. Are connected to a table control circuit 114, a magnetic disk device 109 as an example of a storage device, a magnetic tape device 115, a flexible disk device 116, a CRT 117, a pattern monitor 118, and a printer 119. The XYθ table 102 is driven by an X-axis motor, a Y-axis motor, and a θ-axis motor controlled by the table control circuit 114. As these motors, for example, step motors are used.

  Design pattern data serving as database-based reference data is stored in the magnetic disk device 109, read out as the inspection progresses, and sent to the development circuit 111. In the development circuit 111, the design pattern data is converted into image data (bit pattern data). Thereafter, this image data is sent to the reference circuit 112 and used to generate a reference image to be a standard image.

  In FIG. 1, constituent components necessary for the present embodiment are illustrated, but other known components necessary for inspecting the mask may be included. In this embodiment, a die-to-database inspection method is taken as an example, but a die-to-die inspection method may be used. In this case, one optical image of the same pattern in a different area in the mask is handled as a reference image.

  FIG. 2 is a conceptual diagram showing the flow of data in the present embodiment.

  As shown in FIG. 2, CAD data 401 created by a designer (user) is converted into design intermediate data 402 in a hierarchical format such as OASIS. The design intermediate data 402 stores design pattern data created for each layer and formed on each mask. Here, in general, the inspection apparatus 100 is not configured to directly read OASIS data. That is, unique format data is used for each manufacturer of the inspection apparatus 100. Therefore, the OASIS data is input to the inspection apparatus 100 after being converted into format data 403 unique to each inspection apparatus for each layer. The format data 403 can be data unique to the inspection apparatus 100, but may be data compatible with the drawing apparatus.

  The format data 403 is input to the magnetic disk device 109 of FIG. That is, the design pattern data used when forming the pattern of the photomask 101 is stored in the magnetic disk device 109.

  The figure included in the design pattern is a basic figure of a rectangle or a triangle. The magnetic disk device 109 includes information such as coordinates (x, y) at the reference position of the graphic, side length, graphic code serving as an identifier for distinguishing graphic types such as a rectangle and a triangle, and each pattern graphic. Graphic data defining the shape, size, position, etc.

  Furthermore, a set of figures existing in a range of about several tens of μm is generally called a cluster or a cell, and data is hierarchized using this. In the cluster or cell, arrangement coordinates and repeated description when various figures are arranged alone or repeatedly at a certain interval are also defined. The cluster or cell data is further arranged in a strip-shaped region called a frame or stripe having a width of several hundreds μm and a length of about 100 mm corresponding to the total length of the photomask in the X direction or Y direction. .

  The input design pattern data is read from the magnetic disk device 109 by the development circuit 111 through the control computer 110.

  The expansion circuit 111 expands the design pattern to data for each graphic, and interprets a graphic code, a graphic dimension, and the like indicating the graphic shape of the graphic data. Then, binary or multivalued design image data is developed as a pattern arranged in a grid having a grid with a predetermined quantization size as a unit. The developed design image data calculates the occupancy ratio of the figure in the design pattern for each area (square) corresponding to the sensor pixel. And the figure occupation rate in each pixel becomes a pixel value.

  The design pattern data converted into binary or multi-value image data (design image data) as described above is then sent to the reference circuit 112. In the reference circuit 112, an appropriate filter process is performed on the design image data which is the image data of the transmitted graphic.

  FIG. 3 is a diagram for explaining the filter processing.

  The mask measurement data 404 as an optical image obtained from the sensor circuit 106, which will be described later, is blurred due to the resolution characteristics of the optical system, the aperture effect of the photodiode array, or the like, in other words, a spatial low-pass filter acts. Is in a state. Therefore, it is possible to match the mask measurement data 404 by filtering the bit pattern data that is the image data on the design side, in which the image intensity (light / dark value) is a digital value. In this way, a reference image to be compared with the mask measurement data 404 is created.

  Next, a method for obtaining the mask measurement data 404 will be described with reference to FIGS.

  In FIG. 1, the optical image acquisition unit A acquires an optical image of the photomask 101, that is, mask measurement data 404. Here, the mask measurement data 404 is an image of a mask on which a figure based on the figure data included in the design pattern is drawn. A specific method for acquiring the mask measurement data 404 is as follows, for example.

  A photomask 101 to be inspected is placed on an XYθ table 102 provided so as to be movable in a horizontal direction and a rotation direction by motors of XYθ axes. Then, light is emitted from the light source 103 disposed above the XYθ table 102 to the pattern formed on the photomask 101. More specifically, the photomask 101 is irradiated with the light beam emitted from the light source 103 via the illumination optical system 170. Below the photomask 101, an enlargement optical system 104, a photodiode array 105, and a sensor circuit 106 are arranged. The light that has passed through the photomask 101 forms an optical image on the photodiode array 105 via the magnifying optical system 104. Here, the magnifying optical system 104 may be configured such that the focus is automatically adjusted by an automatic focusing mechanism (not shown). Further, although not shown, the inspection apparatus 100 irradiates light from below the photomask 101, guides the reflected light to the second photodiode array via the magnifying optical system, and collects the transmitted light and the reflected light simultaneously. It may be configured.

  FIG. 4 is a diagram for explaining a procedure for acquiring the mask measurement data 404.

  As shown in FIG. 4, the inspection area is virtually divided into a plurality of strip-like inspection stripes 20 having a scan width W in the Y direction, and each of the divided inspection stripes 20 is continuously scanned. Thus, the operation of the XYθ table 102 is controlled, and an optical image is acquired while moving in the X direction. An image having a scan width W as shown in FIG. 4 is continuously input to the photodiode array 105. When an image in the first inspection stripe 20 is acquired, an image having a scan width W is continuously input to the second inspection stripe 20 in the same manner while the XYθ table 102 is moved in the opposite direction. The third inspection stripe 20 is acquired while moving in the direction opposite to the direction in which the image in the second inspection stripe 20 is acquired, that is, in the direction in which the image in the first inspection stripe 20 is acquired. In this way, it is possible to shorten a useless processing time by continuously acquiring images.

  The pattern image formed on the photodiode array 105 is photoelectrically converted and then A / D (analog-digital) converted by the sensor circuit 106. The photodiode array 105 is provided with an image sensor. An example of the image sensor is a TDI (Time Delay Integration) sensor. For example, the pattern of the photomask 101 is imaged by the TDI sensor while the XYθ table 102 continuously moves in the X-axis direction.

  The XYθ table 102 is driven by a table control circuit 114 under the control of the control computer 110, and can be moved by a drive system such as a three-axis (XY-θ) motor that drives in the X, Y, and θ directions. It has become. For example, a step motor is used as the X-axis motor, the Y-axis motor, and the θ-axis motor. The movement position of the XYθ table 102 is measured by the laser length measurement system 122 and sent to the position circuit 107. The photomask 101 on the XYθ table 102 is automatically conveyed from the autoloader 130 driven by the autoloader control circuit 113, and is automatically discharged after the inspection is completed.

  The mask measurement data 404 output from the sensor circuit 106 is sent to the comparison circuit 108 together with data indicating the position of the photomask 101 on the XYθ table 102 output from the position circuit 107. The mask measurement data 404 is, for example, 8-bit unsigned data and represents the brightness gradation of each pixel. Further, the reference image described above is also sent to the comparison circuit 108.

  In the comparison circuit 108, the mask measurement data 404 sent from the sensor circuit 106 and the reference image generated by the reference circuit 112 are compared using an appropriate comparison determination algorithm. The comparison is performed using only a transmission image, only a reflection image, or an algorithm that combines transmission and reflection. A plurality of algorithms are selected according to the nature of the defect. A threshold value is set for each algorithm, and an algorithm having a reaction value exceeding the threshold value is detected as a defect. In this case, first, a temporary threshold is set for the algorithm, and a defect inspection result performed based on this threshold is reviewed in a review process described later. When this process is repeated and it is determined that sufficient defect detection sensitivity is obtained, the provisional threshold is determined as the algorithm threshold.

  As a result of the comparison, when the difference between the mask measurement data 404 and the reference image exceeds the threshold value, the portion is determined as a defect. If it is determined as a defect, the coordinates, the mask measurement data 404 and the reference image that are the basis for the defect determination are stored in the magnetic disk device 109 as a mask inspection result 405.

  The mask inspection result 405 is sent to a review device 500 that is an external device of the inspection device 100. The review is an operation in which the operator determines whether the detected defect is a problem. The review device 500 displays an image of a defective portion of the mask while moving the table on which the mask is placed so that the defect coordinates of each defect can be observed. At the same time, these are displayed side by side on the screen so that the determination conditions for defect determination and the optical image and reference image that are the basis for determination can be confirmed. By displaying the defect on the mask and the ripple state on the wafer transfer image side by side in the review process, it becomes easy to determine whether or not the mask pattern should be corrected. In general, a reduction projection of about 1/4 is performed from the mask to the wafer, so this scale is also taken into consideration when displaying them side by side.

  All the defects detected by the inspection apparatus 100 are determined by the review apparatus 500. The determined defect information is returned to the inspection apparatus 100 and stored in the magnetic disk device 109. When at least one defect to be corrected is confirmed by the review apparatus 500, the mask is sent to the correction apparatus 600 that is an external apparatus of the inspection apparatus 100 together with the defect information list 406. In the case of a pattern defect, the correction method differs depending on whether the defect type is a convex defect or a concave defect. Therefore, the defect information list 406 includes defect types including irregularities and defect coordinates. For example, it is attached whether the shading film is to be cut or compensated, and the pattern data cut out for recognizing the pattern of the portion to be corrected by the correction device. Here, the above-described mask measurement data 404 can be used as the pattern data.

  Note that the inspection apparatus 100 itself may have a review function. In this case, the mask inspection result 405 is displayed on the CRT 117 of the inspection apparatus 100 or a screen of a separately prepared computer together with the accompanying information for defect determination.

  In the review process, the defect is displayed on the monitor based on the data created from the inspection result, and the operator determines whether this is a really problematic defect and classifies the defect. Specifically, a comparison image is generated from an optical image that is measurement data and a reference image, and defects displayed on the comparison image are reviewed by an operator. Pixel data in these images is expressed by gradation values for each pixel. That is, each pixel is given any value from 0 gradation to 255 gradation from a color palette having 256 gradation values, thereby displaying a drawing pattern or a defect.

  The optical image is an image obtained by capturing an actually drawn pattern, and the cross section of the pattern edge does not usually have an ideal shape as defined by the drawing data. For example, even if the cross-sectional shape of the pattern is rectangular in the drawing data, the actual pattern often takes a gentle taper shape. For this reason, the gradation value gradually changes near the pattern edge. Therefore, in the defect determination process, it is necessary to define where the pattern edge is. For example, a portion where the gradation value greatly varies is used as a pattern edge, and the distance between adjacent pattern edges is compared between the optical image and the reference image. The difference between these distances is defined as a pattern dimension error measurement value (ΔCD).

  However, if the intensity of the measurement light at the time of capturing an optical image changes or the sensitivity of the image sensor changes, the gradation value changes and the position of the pattern edge changes. Then, since the distance between the pattern edges in the optical image varies, the pattern dimension error measurement value changes.

  In this embodiment, the true pattern dimension error measurement value (ΔCD) is obtained by obtaining the variation of the measurement value due to the above factors and subtracting this from the apparent pattern dimension error measurement value (ΔCDe). Hereinafter, a specific method for calculating ΔCD will be described.

  The sensitivity of the image sensor changes with time, and the change appears as a change in light intensity (light quantity) detected by the image sensor. FIG. 5 is an example showing a temporal change in light intensity detected by the image sensor. For example, in the process of acquiring an optical image while continuously scanning in the X direction and the −X direction as described with reference to FIG. 4, such a relationship is used for measuring the light intensity provided in the mask substrate every predetermined time. It is calculated | required by moving to this pattern and measuring the light intensity in this pattern.

  In the example of FIG. 5, the amount of light detected with the passage of time decreases. That is, the light intensity (I) decreases as time (t) elapses. In some cases, the light intensity decreases with the passage of time, or the increase and decrease are mixed.

  In the case of the example in FIG. 5, the relationship between time (t) and light intensity (I) can be approximated by equation (1). In addition, you may fit by a polynomial according to a case.

  Further, assuming that the amount of variation in the dimensional difference due to the elapse of time (t) is ΔCD ′ (t), this value is expressed by Expression (2).

  Substituting equation (1) into equation (2) yields equation (3).

  The true pattern dimension error measurement value ΔCD is equal to the apparent pattern dimension error measurement value ΔCDe minus the amount of change in dimension difference (ΔCD ′ (t)) due to the passage of time (t). That is, ΔCD is expressed by equation (4).

  Since ΔCDe and I (t) are obtained by measurement, if constants A and B are known, ΔCD can be obtained. The above relationship will be described more specifically with reference to FIG.

  In FIG. 6, (a) and (b) are schematic views of the same mask. The first number of the subscript indicates the row number, the second number indicates the column number, and the third number indicates the number of measurements of the same mask. The patterns drawn on the reference numeral 111 and the reference numeral 112 are the same, but the reference numeral 111 indicates that the dimension is measured for the first time, and the reference numeral 112 indicates that after a predetermined time from the first measurement, It shows that the dimension is measured for the second time. Similarly, reference numeral 121 and reference numeral 122, reference numeral 211 and reference numeral 212, reference numeral 221 and reference numeral 222 are the same pattern, and the pattern shown in (a) is measured for the first time. The dimension measurement is performed for the second time for the pattern (b) corresponding to.

  For example, since the code 111 and the code 112 measure the dimension of the same pattern, the pattern dimension error measurement value should be essentially the same. Therefore, when the code 111 is measured and the code 112 is measured after a lapse of a predetermined time, if there is a difference between these measured values, it is assumed that the cause is a change in intensity of the image sensor.

ΔCD ′ (t), which is the variation amount of ΔCD, is expressed by equation (2). Therefore, in the example of FIG. 6, a value (A (average value)) obtained by averaging the constants A in each of the four patterns is expressed by Expression (5). In the equation (5), for example, ΔCDe ₁₁₂ is an apparent pattern dimension error measurement value 112, and ΔCDe ₁₁₁ is an apparent pattern dimension error measurement value 111. By taking these differences, the change in dimensional error over time in the same pattern, that is, ΔCD ′ (t) is obtained. In Formula (5), for example, I ₁₁₂ is the light intensity indicated by reference numeral 112, and I ₁₁₁ is the light intensity indicated by reference numeral 111. By taking these differences, a change in light intensity with time in the same pattern is required.

  Further, from the equation (2), B = ΔCD ′ (t) −A × I (t). Therefore, in the example of FIG. 6, a value (B (average value)) obtained by averaging the constants B in each of the four patterns is expressed by Expression (6).

  The constant A and the constant B are obtained as described above.

Furthermore, the above is generalized as follows. If the temporal variation of ΔCD is ΔCD ′ _{i, j} (t) for the pattern at coordinates (i, j), this value is expressed by equation (7).

A and B are determined from equation (7). When the variation at time t is replaced with the variation of different measurement times, the constant A (average value) and the constant B (average value) are expressed by equations (8) and (9), respectively, when the number of measurements is two. . In equations (8) and (9), n _i represents the number of rows and n _j represents the number of columns.

  FIG. 7 shows how the conventional pattern dimension error measurement value changes for each measurement. In addition, the horizontal axis of FIG. 7 represents the measurement location. As can be seen from this figure, if the measurement points are the same, the pattern dimension error measurement values should be essentially the same, but the first, second, and third measurement values are all different values. Yes. Specifically, the value of the pattern dimension error measurement value decreases as the number of measurements increases. This is presumably because the temporal variation is included in the pattern dimension error measurement value due to the sensitivity variation of the image sensor. That is, the pattern dimension error measurement value in FIG. 7 is an apparent value (ΔCDe), and it is necessary to exclude the temporal variation (ΔCD ′ (t)) of the pattern dimension error measurement value from this value.

  FIG. 8 is a re-plot of the apparent pattern dimension error measurement value (ΔCDe) shown in FIG. 7 except for the dimensional difference variation (ΔCD ′ (t)) due to the passage of time (t). It is. According to FIG. 8, even if the number of times of measurement changes, the pattern dimension error measurement value hardly changes. That is, this value can be said to be a true pattern dimension error measurement value. When a true pattern dimension error measurement value is obtained, the electron beam lithography apparatus is adjusted and the lithography process is reviewed so that the difference between this value and the pattern dimension design value falls within an allowable range.

  The operation of the comparison circuit will be described with reference to FIG. In addition, it has shown that the part which attached | subjected the same code | symbol as FIG. 1 is the same.

  The mask measurement data output from the sensor circuit 106 is sent to the comparison circuit 108 together with data indicating the mask position on the XYθ table 102 output from the position circuit 107. Further, the design pattern data subjected to the filter processing by the reference circuit 112 is sent to the comparison circuit 108 as a reference image. The comparison circuit 108 compares the mask measurement data sent from the sensor circuit 106 with the reference image generated by the reference circuit 112.

  As shown in FIG. 9, the comparison circuit 108 includes a pattern recognition unit 108a, a dimension measurement unit 108b, a dimension error determination unit 108c, and a threshold variable setting unit 108d.

  The pattern recognition unit 108a differentiates the design pattern data and recognizes the edge direction of the design pattern in the design pattern data. More specifically, the edge direction of the design pattern is recognized by searching for a pair of adjacent pixels (edge pairs) at each edge portion at both ends in the width direction of the design pattern. Therefore, the pattern recognition unit 108a includes a scanning unit, a search unit, and an edge direction recognition unit.

  The scanning unit scans the entire design pattern by moving the measurement window in the X direction and the Y direction. The measurement window is composed of N × N pixels, for example, 15 × 15 pixels, 17 × 17 pixels, or 19 × 19 pixels.

  The search means searches from the target pixel Q, which is the center pixel of the measurement window, in four directions of ± 45 ° with respect to the X direction, the Y direction, and the XY direction (eight directions considering the + direction and the − direction). Do.

  The edge direction recognition means detects a search direction in which a pair of pixels is present from the search results in the eight directions, and recognizes that the edge direction of the design pattern is in a direction orthogonal to the search direction. For example, if pixels corresponding to edge points are detected at both ends of the design pattern by searching in the X direction, these pixels are used as edge pairs. Then, the direction orthogonal to the X direction which is the search direction, that is, the Y direction is recognized as the edge direction of the pattern.

  The dimension measuring unit 108b shown in FIG. 9 detects each edge point at both ends of the design pattern with sub-pixels based on each pixel value of the edge pair detected by the edge direction recognition means. And the dimension of the width direction of a design pattern is detected from these edge points. In other words, the dimension measuring unit 108b detects an edge point at a sub-pixel using a predetermined threshold for a profile of pixel values in the width direction of the design pattern whose edge direction is recognized.

  The dimension measuring unit 108b reads the mask measurement data, and calculates the dimension in the width direction of the mask measurement data from the edge part at the same position as the edge part where the dimension in the width direction is calculated by the design pattern. For this reason, the dimension measurement unit 108b includes a profile acquisition unit, an edge point detection unit, a first width dimension calculation unit, and a second width dimension calculation unit.

  The profile acquisition means has a function of obtaining a profile of the pixel value in the width direction of the design pattern at the edge portion where the edge direction is recognized.

  The edge point detection means has a function of detecting each edge point at both ends of the design pattern with a sub-pixel using a predetermined threshold for the profile acquired by the profile acquisition means. Edge points are detected as follows. For example, in the design pattern data, when a point where the pixel value changes between “200” and “0” is an edge point, the edge point is detected using a threshold value. At this time, there are a case where the brightness of a specific pixel matches the threshold and a case where there is a threshold between the brightness of two pixels. For the dimensions in the X direction and the Y direction, there are combinations of a plurality of edge pairs, which are stored as templates composed of pixels around both opposing edges. An edge pair is recognized when the edge patterns of both edges become similar patterns opposite to each other.

  The first width dimension calculating unit has a function of calculating the dimension in the width direction of the design pattern from each edge point detected by the edge point detecting unit.

  The second width dimension calculating unit has a function of receiving the mask measurement data and calculating the dimension in the width direction in the mask measurement data at the same position as the pixel position of the edge pair detected by the edge direction recognition unit.

  The dimensional error determination unit 108c shown in FIG. 9 determines the quality of the pattern formed on the mask based on the width direction dimension of the design pattern acquired by the dimension measurement unit 108b and the width direction dimension of the mask measurement data. I do. For this reason, the dimensional error determination unit 108c includes a dimensional error calculation unit and a determination unit.

  The dimension error calculation means calculates a pattern dimension error measurement value from the difference between the dimension in the width direction of the design pattern and the dimension in the width direction of the mask measurement data. In the present embodiment, the correlation between the temporal variation of the sensitivity of the image sensor and the temporal variation of the pattern dimension error measurement value is obtained. Specifically, while measuring the pattern dimension error measurement value, the light intensity in the pattern for measuring the light intensity change of the image sensor is measured at regular intervals, and the pattern dimension error measurement value is calculated from the temporal variation. Find time variation. Then, the true pattern dimension error measurement value is obtained by subtracting the temporal variation of the obtained pattern dimension error measurement value from the apparent pattern dimension error measurement value. As a result, it is possible to accurately obtain variations in the dimensions and positions of the pattern formed on the mask.

  The determination unit determines that the measured value of the pattern dimension error is outside the allowable range when the measured value exceeds the offset value. That is, this pattern is determined as a defect when it is larger than the plus threshold or smaller than the minus threshold.

  The threshold value variable setting unit 108d shown in FIG. 9 creates a frequency distribution of pattern dimension error measurement values, and variably sets the threshold value or the offset value based on the frequency distribution. This is because an error occurs in the design pattern data in the course of the arithmetic processing in the development circuit 111 of FIG. 1, the pattern shape of the mask measurement data is reduced due to the white / black background, or becomes nonlinear as the shape becomes smaller. This is because the shape changes. That is, it is necessary to correct the threshold value and the offset value according to such a change.

  The threshold variable setting unit 108d includes a frequency distribution creating unit and a variable setting unit.

  The frequency distribution creating means creates a frequency distribution of pattern dimension error measurement values. The threshold value needs to be set larger as the line width of the pattern formed on the mask becomes smaller or the contact pattern becomes smaller. Therefore, when the dimension measuring unit 108b measures the pattern dimension, the threshold variable setting unit 108d creates a frequency distribution of pattern dimension error measurement values using a normal mask pattern. The shape deviation of the design pattern is obtained using the created frequency distribution.

  The variable setting means variably sets the threshold value or the offset value based on the frequency distribution created by the frequency distribution creating means. In the design pattern data, since the amount of positional deviation varies depending on the white / black background of the design pattern, the variable setting means determines a plurality of offset values in accordance with the background level. Furthermore, since the variation corresponding to the line width of the pattern is also known from the frequency distribution, a plurality of threshold values are determined according to the dimensions of the design pattern.

  As described above, in the present embodiment, first, the correlation between the fluctuation of the sensitivity of the image sensor and the fluctuation of the pattern dimension error measurement value is obtained. Specifically, while measuring the pattern dimension error measurement value, the light intensity in the pattern for measuring the light intensity change of the image sensor is measured at regular intervals, and the pattern dimension error measurement value is calculated from the temporal variation. Find fluctuations. Then, the true pattern dimension error measurement value is obtained by subtracting this value from the apparent pattern dimension error measurement value. As a result, it is possible to accurately obtain variations in the dimensions and positions of the pattern formed on the mask.

  Note that, as described above, the variation factor of the apparent pattern dimension error measurement value also includes a change in the intensity of the measurement light when an optical image is captured. Therefore, this variation is correlated with the variation of the pattern dimension error measurement value. It is preferable to consider the relationship. Furthermore, it is more preferable to take into account other fluctuation factors.

  The present invention is not limited to the above-described embodiment, and various modifications can be made without departing from the spirit of the present invention.

  In the above embodiments, descriptions of parts that are not directly required for the description of the present invention, such as the device configuration and control method, are omitted. However, the required device configuration and control method may be appropriately selected and used. Needless to say, you can. In addition, all pattern inspection apparatuses or pattern inspection methods that include elements of the present invention and whose design can be changed as appropriate by those skilled in the art are included in the scope of the present invention.

DESCRIPTION OF SYMBOLS 20 Inspection stripe 100 Inspection apparatus 101 Photomask 102 XY (theta) table 103 Light source 104 Expansion optical system 105 Photodiode array 106 Sensor circuit 107 Position circuit 108 Comparison circuit 108a Pattern recognition part 108b Dimension measurement part 108c Dimension error determination part 108d Threshold variable setting part 109 Magnetic disk device 110 Control computer 111 Development circuit 112 Reference circuit 113 Autoloader control circuit 114 Table control circuit 115 Magnetic tape device 116 Flexible disk device 117 CRT
118 Pattern Monitor 119 Printer 120 Bus 122 Laser Length Measurement System 130 Autoloader 170 Illumination Optical System 401 CAD Data 402 Design Intermediate Data 403 Format Data 404 Mask Measurement Data 405 Mask Inspection Result 406 Defect Information List 401 Wafer Transfer Simulator 500 Review Device 600 Correction Device

Claims (5)

In an inspection apparatus that illuminates a sample on which a pattern is formed, forms an image of the sample on an image sensor, and inspects the dimensions of the pattern formed on the sample.
A portion for obtaining an optical image of the sample from the image sensor;
Comparing the optical image with a reference image, and determining a defect when a dimensional difference of the pattern in these images exceeds a predetermined range;
The part to be determined as the defect is a part for obtaining an apparent dimensional difference of the pattern from the optical image and the reference image,
Acquiring at least one temporal variation of the light intensity and the sensitivity of the image sensor;
A portion for acquiring a relationship between a temporal variation of at least one of the light intensity and the sensitivity of the image sensor and a temporal variation of a dimensional difference of the pattern;
An inspection apparatus comprising: a portion for obtaining a true dimensional difference of the pattern by subtracting a temporal variation of the dimensional difference of the pattern from the apparent dimensional difference.   The reference image is a reference image created from design data of the pattern, or an optical image of the same pattern as the pattern in a region different from the optical image on the sample. The inspection device described in 1. The sample on which the pattern is formed is illuminated with light, an image of the sample is formed on an image sensor to obtain an optical image, and the optical image is compared with a reference image, and the dimensional difference of the pattern in these images is found. In an inspection method for determining a defect when a predetermined range is exceeded,
Acquire at least one temporal variation of the light intensity and the sensitivity of the image sensor, and determine the relationship between the temporal variation and the temporal variation of the dimensional difference of the pattern to correct the dimensional difference of the pattern. Inspection method characterized by performing.   By moving the image sensor relative to the sample, the image sensor is moved to another pattern provided in the sample every predetermined time while acquiring an optical image of the entire sample, 4. The inspection method according to claim 3, wherein a temporal variation in sensitivity of the image sensor is obtained.   The reference image is a reference image created from design data of the pattern or an optical image of the same pattern as the pattern in a region different from the optical image on the sample. Or the inspection method of 4.

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