JP2007212473A - Pattern measuring method and instrument, and pattern process control method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a pattern measuring technique capable of measuring nondestructively, accurately and quantitatively a cross-sectional shape, over from a normal taper to a reverse taper, even in any type of patterns. <P>SOLUTION: A distribution of a reflection electron or secondary electron intensity is processed from a control system of a scanning microscope and an adjacent terminal, and a shape of an area expressing the vicinity of an edge is digitalized to calculate a tapering tendency based on a result thereof. A shape of an area in the vicinity of a pattern edge is digitized, based on an image data of a sky photograph obtained by the scanning microscope, to evaluate the tapering tendency of the cross-sectional shape. The tendency of the edge in the reverse, vertical or normal taper, or the like, can be evaluated, based only a sky observation result. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to a pattern inspection technique, and more particularly to a technique for measuring a pattern shape of a fine pattern by nondestructive measurement using a scanning microscope or the like.

  In recent semiconductor manufacturing processes, it has become necessary to observe and quantify slight deterioration of the shape as the pattern is miniaturized. In the lithography process, the edge of the ideal resist pattern is perpendicular to the wafer surface, but in reality it has a shape such as a taper, reverse taper, and a bowl shape (T-shaped, so-called tee top) with only the surface portion protruding. Or

  There are two purposes for quantitatively evaluating such a cross-sectional shape and detecting an abnormality.

  First, if an abnormal cross-sectional shape appears, if it is overlooked and processed, there is a high possibility of a defective product. For example, when the pattern is tapered, defects such as disconnection occur due to insufficient strength against etching and ion implantation at the edge. In the case of a reverse taper or tee top, when observing the sky, it is blocked by the vicinity of the surface, and accurate dimension measurement cannot be performed. In addition, since the region exposed to ions and radicals differs depending on whether or not the vicinity of the surface of the resist pattern remains in the etching (initial stage) and when it does not remain, it is impossible to predict the finished dimensions. Therefore, in order to detect a defective pattern at an early stage and improve the yield, an inspection method for quantitatively evaluating the cross-sectional shape is required.

  Second, the deviation from the optimum value of the exposure condition can be estimated quantitatively by measuring the degree of the cross-sectional shape abnormality. If the focus or exposure amount at the time of exposure deviates from the optimum value, the pattern becomes a defective pattern. However, whether the problem is in the exposure amount or the focus only by dimensional measurement, or whether they are shifted from positive or negative. I do n’t know. However, when the focus shifts, a tapered shape often appears, and the taper tendency is correlated with the focus shift. Therefore, if the correspondence between the exposure amount or focus shift and the cross-sectional shape is quantitatively grasped, it can be determined how to correct the exposure condition from the observation image of the pattern on the wafer.

  A method for measuring a cross-sectional shape from observation with a scanning electron microscope (SEM) having a length measurement function, which is an effective means of pattern observation, has been proposed so far. For example, in Japanese Patent Application Laid-Open No. 07-027549, the energy of an irradiation electron beam is made higher than that of a conventional SEM, so that many secondary electrons are generated from a portion hidden in the sky observation, and the shape thereof is The method of obtaining is described. This method can measure a reverse taper shape. However, it has the following disadvantages.

  First, in ArF resists used for fine processing of 0.10 μm and later, pattern shrinkage due to high-energy electron beam irradiation is observed, and this method is not suitable. Second, even when observing patterns other than the ArF resist, if a high energy electron beam is used, the charge-up may increase. Third, if the average atomic number of the substances constituting the pattern is close, no contrast can be obtained.

  Japanese Patent Application Laid-Open No. 11-297264 describes a means of detecting reflected electrons and secondary electrons by classifying them according to their emission directions and predicting a three-dimensional structure from the results. The method has a drawback that the signal intensity is small compared to noise because the detector is close to the sample surface. Moreover, the reverse taper tendency cannot be detected.

  Recently, an SEM that can observe the side surface of a pattern by tilting an electron beam to be irradiated has been developed. However, even if this method is used, it is necessary to determine whether or not the edge of the obtained image is vertical.

  Next, as an image processing method for predicting a cross-sectional shape from an aerial photograph, for example, there are a method described in Japanese Patent Laid-Open No. 08-014836 and a method described in Japanese Patent Laid-Open No. 2000-269112. In these methods, the distribution of secondary electron intensity in the direction perpendicular to the pattern edge in the SEM image, so-called profile is analyzed. The former measures dimensions with multiple thresholds, and the latter uses a quadratic curve to approximate the profile of the bottom of the profile toward the underlying area, so that you can grasp the forward taper trend for each. become. However, in these methods, even if the edge is vertical, if the vicinity of the surface of the pattern is round, it may be difficult to distinguish from the taper, and it is impossible to detect the tendency of the reverse taper.

  Other examples include “Proceedings of IEE ESM I Advanced Semiconductor Manufacturing Conference” (Proc. IEEE / SEMI Advanced Semiconductor Manufacturing Conference (1998), pp259- 261) and Japanese Patent Laid-Open No. 02-91504, paying attention to a portion having a large secondary electron intensity corresponding to the vicinity of the pattern edge, and measuring the width of the region, the forward taper tendency is evaluated. There is also a method. However, with this method, even if the edge is vertical, it is not possible to distinguish between the width expansion when the side surface has roughness and the width expansion due to the forward taper. The reverse taper tendency cannot be evaluated.

  For these reasons, in order to correctly grasp the cross-sectional shape, conventionally, the pattern is divided and the cross-section is directly observed with an electron microscope. However, this is a destructive inspection. In addition, it is impossible to manually divide the part to be observed on the wafer by hand, so a pattern over an area of 1 mm or more is transferred and the wafer is divided by registering within that area. It is necessary to cut by.

  On the other hand, a method called Scatterometry has been developed in recent years. This method is described in detail in “Proceedings of SPIE 3998 (2000), pp147-157” as an example, and light is applied to a line and space pattern. The spectrum of the scattered light is measured, and information such as line width and pitch, line edge taper and corner roundness is obtained according to the characteristics of the spectrum. This is a non-destructive inspection and can be performed with a simpler system than an electron microscope.

  However, other than the periodic pattern cannot be measured. Further, even a periodic pattern requires an area of several tens of microns. Therefore, if the measurement target pattern is an isolated pattern or is periodic but exists in a narrow area (less than several tens of microns) on the wafer, the periodic pattern for performing this inspection is transferred onto the wafer. Need to be kept. Furthermore, it is necessary to take correspondence between the result of the periodic pattern obtained and the shape of the measurement target pattern.

  As described above, as a method for evaluating the cross-sectional shape of the resist, there are methods such as improvement of the hardware of the conventional length-measuring SEM, image analysis of the aerial photograph, cross-sectional shape observation, and spectrum analysis by Scatterometry.

  However, in the first method, there are hardware limitations and noise problems, which are expensive. Moreover, the reverse taper cannot be measured by the second method proposed so far. Even with a forward taper, it is difficult to distinguish from a vertical edge. The third method is a destructive inspection, and has a problem that a pattern transfer over an area of 1 mm or more or a large-scale apparatus for accurately cutting a target location is required. Further, the fourth method has a problem that it cannot measure a non-periodic pattern or a pattern in a relatively narrow area.

  Accordingly, an object of the present invention is to provide a pattern measurement technique capable of measuring the cross-sectional shape of any type of pattern from a forward taper to a reverse taper in a non-destructive, accurate and quantitative manner. .

  In the present invention, the above-mentioned means of image analysis of aerial photographs is used, but by extracting a band-like region representing the vicinity of the edge and quantifying not only the width of the region but also the shape characteristics, the taper tendency of the cross-sectional shape Calculate Hereinafter, an image obtained by observing a resist line pattern with an SEM will be described as an example.

  FIG. 1 is a schematic diagram of a two-dimensional image obtained by observation. The shading on the SEM image represents the detected secondary electron intensity, and the whitish part has a higher secondary electron intensity. In FIG. 1, all portions close to black are represented by diagonal lines. The detected secondary electron intensity is emitted from the sample surface to the inside as a result of the electrons emitted from the electron gun entering the sample, and is emitted outside the sample and collected by the applied voltage. This represents the amount of material taken into the detector. Therefore, the secondary electrons generated inside reach the sample surface, and the emitted secondary electrons have a high intensity and appear whitish in the vicinity of the edge side surface that tends to jump out. Hereinafter, this region is referred to as an edge region.

  A region adjacent to the edge region in the image is a region where a background appears and a region where a pattern exists. In FIG. 1, 101 indicates an edge region, 102 indicates a region where a background appears, and 103 indicates a region where a pattern exists. FIG. 2 shows an example of the profile of the secondary electron intensity distribution along the horizontal direction (x direction) in the two-dimensional image, that is, a profile. AA ′ in FIG. 1 corresponds to AA ′ on the horizontal axis in FIG. 2.

  Here, a point corresponding to the boundary of the edge region in the profile, that is, a boundary point is obtained. This boundary point may be obtained by a threshold method or may be obtained by a linear approximation method from the left and right slopes of the peak. FIG. 2 is an example obtained by the threshold method. Point P is a boundary point between the edge region and a region without a pattern (the background appears), and point Q is a boundary point between the edge region and the pattern region.

  The taper tendency of the cross section first appears at the distance PQ. This is shown in FIG. The width of the edge region is narrower as the reverse taper shape or the shape of the tee top becomes stronger. That is, the distance PQ is short. This can be explained as follows.

  When the electron beam is incident on the edge end, many secondary electrons generated inside are emitted from the side surface of the edge and collected as they are to reach the detector. However, when the electron beam is incident on the pattern area side slightly from the edge end, secondary electrons emitted from the side surface of the edge are hidden from the detector by the edge end if it is reversely tapered. Hard to reach. For this reason, the peak width of the profile is narrower than when the edge is vertical. Furthermore, since there are usually some unevenness on the side surface, the peak of the profile is blurred even at the vertical edge and the PQ is slightly longer. However, in the case of reverse taper, the unevenness on the side surface is hidden at the edge end, so it hardly contributes to the blurring of the peak. This effect makes it easier to detect a reverse taper shape. In the case of the forward taper shape, the PQ is long because of the long time of incidence on the edge side surface.

  However, as described above, in this method, it is necessary to consider the contribution of the edge unevenness to the edge width. The edge width is determined from both the blur of the profile peak due to the unevenness of the edge and the taper tendency, excluding the resolution of the apparatus. That is, the taper tendency cannot be accurately determined only by the value of the edge region width.

  The unevenness of the edge cannot be directly seen in the sky observation. However, when the unevenness of the side surface is large, the amount of fluctuation of the edge position measured in the sky photograph, so-called edge roughness, also increases. In the present invention, the size of the edge roughness is measured, the size is regarded as a measure of the unevenness of the side surface, and the taper tendency is evaluated from both the width of the edge region. This is shown in a simplified manner in FIG. In the direction of the arrow, the tendency to reverse taper or tee top becomes stronger.

  In the conventional method, the analysis of the line profile, which is one-dimensional information, is focused on, and the feature of the edge itself along the line direction, that is, the two-dimensional information is not considered. When the judgment is made based only on the width of the edge region without considering the edge roughness, it is impossible to distinguish between the case of the forward taper having a small roughness and the case of a slight reverse taper. This is the reason why the reverse taper tendency cannot be measured from the edge width until now.

  Second, it appears in the form of a set of boundary points in the edge region, the boundary line. The boundary point P between the edge region and the base region and the boundary point Q between the edge region and the pattern region are obtained from a sufficient number of profiles in the two-dimensional image, and the set is defined as the first and second boundary lines.

  When the reverse taper shape or the tendency of the tee top is strong, the unevenness of these two boundary lines is very similar, that is, the correlation coefficient is high. However, the correlation coefficient is close to 0 when the side surface is perpendicular to the ground or when it is forward tapered. This is because when the irradiated electron beam has a reverse taper, only the edge of the surface is reflected, whereas when it is vertical or forward taper, it is affected by the unevenness of the edge side surface. Therefore, the set of boundary points (boundary line) obtained is first approximated by an ideally shaped curve or straight line, and then the set of deviations between the approximate line and the boundary point is obtained as the unevenness of the boundary line. If the correlation coefficient of the unevenness of the book boundary is calculated, the inverse taper tendency is reflected in the value.

  Or the similarity of the unevenness | corrugation of two boundary lines can also be expressed by another method. The first boundary and the second boundary are obtained on one profile, and the difference between the positions is set as the width of the edge region in the profile. The width of the edge region is calculated for a plurality of profiles, and the distribution of these values is obtained. The variation in the width value is small when the correlation is large, and conversely large when the correlation is close to zero. Accordingly, the similarity can be expressed by obtaining the standard deviation of the distribution.

  Even in this method, it is possible to make an accurate determination by considering the edge roughness. When the reverse taper tendency of a fine pattern becomes stronger, the edge roughness tends to be larger than when the side surface is vertical. Further, even in a forward tapered pattern, the edge roughness tends to be larger than that in a vertical case. This situation is simplified and shown in FIG. In the direction of the arrow, the tendency to reverse taper or tee top becomes stronger.

  When performing the evaluation, the relationship between the edge roughness size and the edge region width, the correlation coefficient of the unevenness of the boundary line, the relationship between the edge roughness and the correlation coefficient, or a taper tendency from two or more of these. It is good to calculate one index to represent and use it as a guide. In addition, when there are a plurality of edges in an image, a more reliable result can be obtained by calculating this index for each edge and determining the overall tendency by taking the average.

  When this method is used, even when only the vicinity of the top of the pattern is round and the edge has a vertical or reverse taper tendency, the verticality or reverse taper tendency of the edge can be detected correctly. This is due to the following reason.

  First, when only the vicinity of the top of the pattern is rounded, the peak shape spreads on the point Q side but does not spread on the P side. Therefore, the distance PQ is not as large as in the case of the forward taper. Second, the edge roughness is calculated by regarding the normal point P as an edge. In other words, the roundness near the top does not affect the edge roughness. Therefore, if the evaluation is performed together with the value of the edge roughness, it becomes easier to distinguish the forward tapered shape from the case where only the top is rounded.

  In addition, more accurate results can be obtained by applying the above method to an observation image obtained by an observation apparatus having a beam tilt function. If the incident angle of the beam of light, electron beam, ion particle beam, etc. to the sample is changed by operating the beam lens system or the sample stage, and the index of taper tendency is calculated by taking in the image data each time, The relationship between the incident angle and the taper tendency is obtained, and it can be estimated how many times the edge side surface is deviated from the vertical in the case of reverse taper or forward taper.

  In the resist pattern, the difference in edge roughness due to differences in exposure and process conditions is such that the value obtained by measuring roughness near the bottom of the pattern is greater than the value obtained by measuring near the surface. large. Therefore, even if the tilt function is used not for changing the angle of the edge but for measuring the change in roughness with higher sensitivity, the taper tendency can be measured more accurately.

  Further, the taper tendency, ie, reverse taper, forward taper, or vertical, is determined by the above method, and if not vertical, the degree of taper or taper angle is obtained, and the pattern formation process is performed under the optimum conditions from the result. It is possible to estimate the deviation from the optimum value if it has not been performed. Thereby, for example, a focus shift in the lithography process can be detected, and it can be determined how much the focus is moved in the plus or minus direction to obtain the optimum value.

  In the above example, the case where the resist pattern is inspected is mainly described, but useful information can be obtained even when the present method is applied to the pattern of silicon, silicon oxide film, silicon nitride film, carbon, or wiring material. In particular, it is possible to detect the occurrence of a phenomenon in which the bottom of the pattern is bitten by the dry etching or the upper corner is dropped by observation of the sky.

  According to the present invention, it is possible to realize a pattern measurement technique that can measure the cross-sectional shape of any type of pattern from a forward taper to a reverse taper in a non-destructive, accurate and quantitative manner.

  Embodiments of the present invention will be described below with reference to the drawings. In the following description, the tee top shape is included in the expression reverse taper.

Example 1
A first embodiment of the present invention will be described with reference to FIGS. 2, 4 and 6 to 14. In this embodiment, an example will be described in which edge roughness and edge region width are calculated and the taper tendency of the edge is evaluated.

  FIG. 6 is a conceptual diagram showing the apparatus configuration of this embodiment, FIG. 7 is a flowchart showing the procedure of this embodiment, and FIGS. 8 and 9 are two-dimensional images of secondary electron intensity analyzed in this embodiment. FIG. 10 is a detailed diagram of the portion of the process shown in FIG. 7 for calculating the taper tendency index, FIG. 11 is a conceptual diagram showing the relationship between the profile, the edge point, and the edge region width, and FIG. 12 is the result obtained. 13 is a graph showing the edge roughness used for calculating the taper angle, the relationship between the edge region width and the taper angle, and FIG. 14 is a conceptual diagram of the pattern cross section showing the definition of the taper angle.

  Using the apparatus shown in FIG. 6, the tape edge tendency of the pattern edge was analyzed from the line edge roughness and the edge region width according to the procedure shown in FIG. First, as shown in step 701, scanning was performed from the control system 611 of the scanning electron microscope, and the sample 607 placed on the stage 608 in the microscope casing 601 was observed. The electron beam 603 emitted from the electron gun 602 of the scanning electron microscope irradiates the sample 607 on the stage 608 through the converging lens 604, the deflector 605, and the objective lens 606, and the secondary electrons 609 emitted from the sample 607. Was detected by detector 610.

  The acceleration voltage of the irradiation electron beam is desirably 1000 V or less so that the irradiation electron reflects information in the vicinity of the surface of the pattern. This is not the case when it is desired to change the approach distance of the electron beam to obtain information on a region that is slightly deeper than the surface, and observation at 800 to 10000 V is preferable. In addition, if the acceleration voltage is too low, the noise increases and the reproducibility of the measurement result is deteriorated. From that point, a voltage of 300 V or more is necessary. In this example, the voltage was set to 800 V in order to observe the vicinity of the surface.

  Edge taper tendencies can vary from place to place. In order to obtain an averaged value as much as possible, it is better to analyze a wide area. That is, it is desirable to observe at a low magnification. On the other hand, it is desirable to observe at a high magnification in order to measure a slight taper.

  The observation magnification is determined considering these two balances. In this embodiment, the obtained image data is composed of 512 data in both the scanning direction, that is, the horizontal direction and the vertical direction perpendicular thereto. When observed at 200,000 times, the visual field, that is, the scanning region was 675 nm in both the vertical and horizontal directions. From these values, the data interval was sufficiently small at about 1.318 nm, so observation was performed at 200,000 times.

  The sample 607 used has a resist line pattern formed by electron beam drawing on a silicon substrate. First, the sample 607 was placed on the stage 608 so that the line pattern was almost perpendicular to the scanning direction.

Next, the process proceeds to step 702, where a plurality of scans are performed, the measurement results of the secondary electron intensity generated from the sample 607 are integrated, and an average value is calculated. In order to measure edge roughness, it is necessary to determine the number of data accumulation (number of frames) so that data with sufficiently low noise can be obtained. In this example, the integration was performed 128 times in the observation of the magnification of 200,000 times and the current value of 4.0 pA.

  The two-dimensional secondary electron intensity distribution of the 512 × 512 array thus obtained was analyzed. This data was composed of an array of 512 values in the scanning direction, that is, the horizontal direction and the vertical direction perpendicular thereto, that is, a total of 512 × 512 numerical values. When observed at this magnification, the observation region, that is, the region scanned with the electron beam is 675 nm both vertically and horizontally, and the region represented by one numerical value has an area of about 1.318 nm square. In the following, the upper left corner of the screen is the origin, and the horizontal position is described as x and the vertical position as y. The data was converted from the value of the secondary electron intensity into pixel shading, and displayed as an image composed of 512 pixels in both the x and y directions on the screen of the operation terminal of the apparatus. FIG. 8 is a simplified representation of this image. In the figure, a hatched portion 801 indicates two line-shaped resist pattern portions, white portions 802 and 803, 804 and 805 indicate the vicinity of the left and right edges of the two lines, that is, edge regions, respectively, and horizontal stripe lines A portion 806 shown represents a base substrate.

  After stopping the subsequent irradiation of the electron beam with the electron beam, the secondary electron intensity distribution data is transferred to the adjacent computer 612 to finish step 702, and the program for calculating the taper tendency index according to the present invention is executed. I let you. First, noise reduction (step 703) was performed according to the following procedure.

  First, the data was divided into 512 sets of secondary electron intensity, ie, profiles, arranged in a line in the x direction. Each profile is the x dependence of the secondary electron intensity when y is constant, and the profile has a total number of pixels in the y direction, that is, 512. This data was subjected to noise reduction by the following procedure.

First, an averaging parameter k ₁ (natural number) and a smoothing parameter k ₂ (odd number) were given. When k ₁ is an even number, k ₁ ′ = k _1/2 and when it is an odd number, k ₁ ′ = (k ₁ −1) / 2. Further, k ₂ ′ = (k ₂ −1) / 2. The average of nk ₁ 'th to k ₁ profiles was taken as the averaged nth profile. Next, smoothing using a hamming window is performed for the area from pixel number mk ₂ ′ to m + k ₂ ′ in the averaged profile obtained in the above step, and after the m-th smoothing The value of In the case of data in which one pixel corresponds to a length from 0.8 nm to 2 nm, the averaging parameter k ₁ is preferably 4 or more and 11 or less, and the smoothing parameter k ₂ is preferably 3 or more and 11 or less. If both values are smaller than these values, noise cannot be sufficiently reduced, and if they are larger, edge roughness with a fine spatial period cannot be detected. In this embodiment, k ₁ = 4 and k ₂ = 3.

  Next, proceeding to step 704, some parameters were entered. The input contents here in this embodiment are selection of the display form of the result and input of the number of edges to be analyzed. The former is a selection of whether the calculated result is represented by a graph as shown in FIG. 4 or a numerical value that is an index of a taper tendency. In the present embodiment, the latter calculation of the taper tendency index was selected. The number of edges was input as 4, and a total of four edges on the left and right sides of the two lines in the image shown in FIG. 8 were analyzed.

  Next, for each edge, the interval of the profile for detecting the area and edge point of the image data used for the calculation of the line edge roughness and the edge area width is designated (step 705). Here, there are three points to be noted in calculating the roughness of the edge.

  First, since the roughness itself varies, it is necessary to calculate for a plurality of locations when calculating for a wide area or for a narrow area. In the present invention, it can be said that it is desirable to calculate for a region having a total length of at least 1 μm.

  Secondly, when calculated in a short region, long period roughness cannot be observed. Since the roughness calculated here has a meaning as an index of the unevenness of the edge side surface, it is sufficient to calculate in an area having a length in the depth direction of the edge side surface, that is, a length about the resist film thickness.

  Third, if the interval between the edge points for calculating the roughness is too large, the roughness with a fine period cannot be observed. In this example, the resist film thickness was 0.42 μm. Therefore, a calculation area is designated as shown in FIG.

  FIG. 9 is a conceptual diagram showing a state in which a calculation area is displayed on the image shown in FIG. In order to clarify the positional relationship with the edge region, the edge regions 802 to 805 are represented by diagonal lines. The designated calculation area is a rectangle 901-904. The number of pixels in the y direction of the region is 360 in all four places. As a result, the roughness is calculated for a total area of about 2 μm, and there is no problem with the first precaution. Moreover, since the length per place is about 0.5 μm, which is the same as the resist film thickness, the second problem does not occur. Furthermore, since the edge point detection for calculating the roughness was performed for every other selected profile, the edge point was obtained every about 2.6 nm, and because it was fine enough, there was a problem with the third point of caution. Absent.

  Here, the number of edge points in the calculation of the line edge roughness and the number of edge points in the calculation of the edge region width are the same, but they may not be the same depending on the performance of the computer and the allowable range of calculation time. However, the period of edge roughness often found in a fine pattern having a width of about 100 nm is generally in the region of 50 nm to 100 nm. In order to correctly measure the irregularities of such a period and measure the edge shape, it is desirable to set the interval between measurement points to 20 nm or less.

  Next, proceeding to step 706, the taper tendency was obtained. Specifically, edge roughness and edge region width were used. Details of this step are shown in FIG. First, in step 1001, it is determined whether parameter input in step 1002 is necessary. If the calculation is for the first line, parameters for edge point detection in roughness calculation are input (step 1002). Otherwise, since the parameters have already been entered, go to step 1003.

The contents to be input in step 1002 are selection of whether (1) edge point detection in roughness calculation or (2) edge region boundary point detection is performed by a linear approximation method or a threshold method, or Parameters in each method. The threshold method used here is generally known. From the threshold ratio p, the secondary electron intensity maximum value I _max, and the minimum value I _min , (I _max −I _min ) × p + I _{In this method} , the threshold value given by _min is calculated, and the point where the secondary electron intensity becomes the threshold value on the profile of FIG.

  If the threshold ratio in edge point detection is too small or too large, noise will increase and the actual dimensions will not be reflected. A value of 40-80% is good. Here, the threshold method with a threshold value of 70% is used. The parameters for calculating the boundary points of the edge region can also be performed by the linear approximation method or the threshold method. When the degree of image noise cannot be determined or when there is a lot of noise, the threshold method of 50 to 80% is preferable. When there is little noise, it is possible to measure with high accuracy by using the linear approximation method or by setting the threshold value low by the threshold method. In particular, the latter can detect a taper tendency with respect to an edge close to vertical. It is also possible to obtain highly reliable data by measuring with a plurality of threshold values. In this embodiment, the threshold method with a threshold value of 70% was used.

Next, proceeding to Step 1003, the edge roughness was calculated according to the following procedure. First, among the 360 profiles in the area 901, 180 profiles from the first, the third, and the 2n-1th (n = 1, 2, 3,... The secondary electron intensity maximum value I _max in the range of x was detected. This is shown in FIG.

The x-coordinate which gives a peak value and x _max, and an edge point R that secondary electron intensity is a threshold at a side close to the underlying substrate than x _max. This was done for 180 profiles to obtain ₁₈₀ edge points R ₁ , R ₂ ... R ₁₈₀ . Let the position coordinates of the point R _{i be} (x _i , y _i ). This set is approximated by a straight line x = ay + b by the method of least squares, and the difference Δx _i = a · y _i + b−x _i from this approximated line is obtained for 180 profiles, which is three times the standard deviation σ of the set, 3σ is the roughness of the edge.

Next, proceeding to step 1004, the edge region width was determined. Here, the boundary point outside the edge region, that is, the base substrate side may be obtained by the above process. The point thus obtained was designated as P. In this embodiment, since the threshold value for edge point detection for roughness calculation and the threshold value for edge region boundary detection are equal, the point R and the point P coincide. Inside, i.e. the resist side of the boundary point is a point Q become secondary electron intensity thresholds resist side than x _max. About 180 pieces of the profile detects the P and _{Q, P 1, P 2,} ..., Q 1, Q 2, ... and, calculates the average value of the distance PQ _i between P _i and Q _i, which edge region The width is w. This process is performed for all calculation regions.

  Next, the process proceeded to step 1005. Here, the next process is selected in accordance with the contents input in process 704. Since whether or not to calculate the value of the taper tendency index is input in step 704, the calculation process ends if one not to calculate is selected, and the process proceeds to step 707 in FIG. On the other hand, when the index is calculated from the calculation result, the process proceeds to step 1006, and the boundary line feature of the edge region is digitized.

  In this example, in the graph of edge roughness vs. edge region width shown in FIG. 12, a set of 3σ and w obtained in the above step (for example, a circle in FIG. 12) represents a region representing a vertical edge. (1) Evaluate whether the direction is shifted in the taper side or the reverse taper side, or (2) how much is shifted. Hereinafter, the simplest method used in this embodiment will be shown as an example.

即ち、Fは逆テーパであれば＋１、順テーパであれば−１の値となる。また、この点と前記直線との距離Lは次の式で表される。

テーパ傾向指標γをこの２つの値の積、即ち

とすればよい。本実施例で解析した例では、α＝２.５、β＝５.０であった（図１２中の1201）。また、ここで求めたエッジのテーパ傾向指標の値は４.６５であった。 First, the edge area width on the graph is represented by w, the edge roughness is represented by r, and the vertical edge area is simplified and represented by a straight line w = αr + β. When an edge region width w ₁ and edge roughness r ₁ are obtained as a result of analyzing an edge, a coefficient F representing the taper direction is determined by determining whether this point is above or below the straight line in the graph. Decide as follows.

That is, F has a value of +1 if it is a reverse taper and -1 if it is a forward taper. The distance L between this point and the straight line is expressed by the following equation.

The taper tendency index γ is the product of these two values, that is,

And it is sufficient. In the example analyzed in this example, α = 2.5 and β = 5.0 (1201 in FIG. 12). The edge taper tendency index obtained here was 4.65.

  Next, the process proceeded to Step 707. Whichever selection is made in step 1005, it is determined whether the calculation has been completed for all the edges selected here. In this example, four edges were selected, so the above process was repeated until all the edges were completed. However, the process 1002 was not performed after the second.

  Next, the results were displayed in step 708. In this example, four sets of 3σ and W were thus obtained. In the case of only the graph display, the analysis result of all edges is plotted on the edge roughness edge region width graph shown in FIG. At the same time, an approximate region on which the results of the taper, vertical, and reverse taper are plotted may be shown on this graph as shown in FIG. When the taper tendency index is calculated, the calculated value is displayed. A graph may be displayed at the same time. In this embodiment, since the latter was selected, index values related to four edges were displayed. The value of the index γ was 4.65, 5.85, 2.98, 4.57.

の領域にあれば、そのエッジは垂直と判定できることが分かっていた。このことから操作者によっても、これら４本のエッジはいずれも逆テーパであると判断できるが、本例においてはあらかじめこの数値を入力しておくことにより、画面にテーパ傾向を表示させた。その結果、ここでは全てについて逆テーパであるという表示が出た。 On the other hand, from the data collection result by direct observation of the cross section, in the analysis by the apparatus and parameters used in this example,

It was found that the edge can be determined to be vertical in the region of. From this, the operator can also determine that all of these four edges are inversely tapered, but in this example, by inputting this numerical value in advance, a taper tendency is displayed on the screen. As a result, the indication that all are reversely tapered appears here.

  It is also possible to obtain the result by taking the average of all the analyzed edges. When an abnormal taper tendency appears in the resist pattern, there is a problem in the process in many cases, and the tendency appears in a region having a certain extent. Therefore, it is possible to obtain a more reliable conclusion by calculating and determining the average value than calculating the taper tendency index by only a part of the observation image. In this example, a value of γ = 4.51 was obtained as the pattern tendency of the entire image. As an overall trend, it was concluded that the pattern analyzed here was inversely tapered.

  After obtaining the results as described above, the analysis was terminated and the observation was completed. Note that the method of calculating the taper tendency index by the mathematical formulas shown in (Equation 1) to (Equation 4) is an example. The order and coefficient values of the equation depend on the material of the pattern and the performance of the device, the value of the parameters in observation and calculation.

As a method of calculating the index in step 1006, in addition to the above example, an expression introducing a higher order term for r ₁ and w ₁ is used, or the values of r ₁ and w ₁ and the taper angle are made to correspond to each other. It can also be used as an index. An example of this is shown in FIG.

This relationship can be obtained by actually observing the sky and cross-sections of a large number of samples or by simulating SEM observation. In this example, actual observation was performed. If the values of r ₁ and w ₁ measured on such a graph are plotted, the taper angle can be calculated. It can be seen that the four edges analyzed in this example have a reverse taper of 2 ° to 4 °.

  Here, the term “taper angle” is defined as a deviation from a vertical edge as indicated by θ in FIG. 14, so that a positive taper is a reverse taper and a negative taper is a forward taper.

(Example 2)
A second embodiment of the present invention will be described with reference to FIG. 2, FIG. 6 to FIG. 9, and FIG.

  In the present embodiment, an example is shown in which the edge taper tendency is evaluated from the similarity between the shapes of two boundaries of the edge region, that is, the correlation coefficient. FIG. 15 shows details of a portion for calculating a taper tendency in the steps shown in FIG.

  In the method shown in Example 1, steps 701 to 703 are performed according to the procedure of FIG. 7 using the apparatus of FIG. 6, and the sample is observed to obtain the image data shown in FIG. It was.

  Next, proceeding to step 704, some parameters were entered. In this embodiment, the input content here is an input of the number of edges to be analyzed. In this example, 4 was input, and a total of four edges on the left and right sides of two lines in the image shown in FIG. 8 were analyzed.

  Next, the process proceeds to step 705, where the image data area used for calculation and the profile interval for detecting the boundary point of the edge area are designated for each edge. In this embodiment, the shape of the edge region boundary is digitized. That is, the unevenness of the edge region boundary must be input to the calculation over a sufficiently wide and sufficiently wide region. Therefore, it is necessary to pay attention in the present embodiment to exactly the same points as those noted in the roughness measurement in step 705 in the first embodiment. Here, the same parameters as in Example 1 were input. That is, the calculation is performed for the region shown in FIG.

  Next, proceeding to step 706, the taper tendency was obtained. Details of this step are shown in FIG. First, in step 1501, it is determined whether parameter input in step 1502 is necessary. If the calculation is for the first line, the edge region boundary point detection parameters are input (step 1502). Otherwise, since the parameters have already been entered, the process proceeds to step 1503. In step 1502, it is selected whether the edge region boundary point is detected by the linear approximation method or the threshold method, and parameters for each method are input. In the present embodiment, it is necessary to pay attention similar to that in the step 1002 in the first embodiment. In this embodiment, the threshold method with a threshold value of 70% was used.

Next, proceeding to step 1503, the points P and Q shown in FIG. 2 are detected for 180 profiles in the same manner as the procedure for obtaining P and Q in step 1004 of the first embodiment, and P ₁ , P ₂ ,. ₁ , Q ₂ ,..., And the sets {P _i } and {Q _i } are set as outer and inner boundary points.

Next, proceeding to step 1504, a correlation coefficient (similarity) was calculated. The point P _i and the point Q _i have the same y coordinate, but have different x coordinate values. Let this be x _Pi , x _Qi . First, the sets {P _i } and {Q _i } were approximated by two parallel curves or straight lines. “Parallel” as used herein means that one curve or straight line can be translated and superimposed on the other. Here, approximation was performed using a straight line, and the least square method was used for the approximation.

ここでσ_P、σ_Qは各々{Δx_Pi}、{Δx_Qi}の分布の標準偏差、また右辺分子は以下のように表される。

以上で、図１５に示された工程は終了し、工程707に進み、ここで選択したエッジ全てについて計算が終了したかを判定する。本実施例では４本のエッジを選択していたので、全てについて終了するまで上記の工程を繰り返した。ただし、２本目以降は工程1502は行わない。 Next, the difference of the x coordinate between the intersection of the approximate straight line obtained on the profile and the profile and the actual boundary point was obtained. This is expressed as Δx _Pi and Δx _Qi . This set of differences, {Δx _Pi }, {Δx _Qi }, is defined as the uneven shape of the outer boundary line and the inner boundary line. For all the calculated profiles, the correlation coefficient ρ is calculated from these values according to the following formula. Note that P and Q mean the outer edge and the inner edge.

Here, σ _P and σ _Q are the standard deviation of the distribution of {Δx _Pi } and {Δx _Qi }, respectively, and the right-hand side numerator is expressed as follows.

Thus, the process shown in FIG. 15 is completed, and the process proceeds to process 707, where it is determined whether the calculation has been completed for all the selected edges. In this example, four edges were selected, and thus the above process was repeated until all the edges were completed. However, the process 1502 is not performed for the second and subsequent lines.

の領域にあるエッジは逆テーパであることが分かっていた。本実施例で解析したエッジは全て逆テーパであることが分かった。また、実施例１工程708で行ったように、解析した画像データ１枚に関する値としてこれら４つの値の平均を表示して判断してもよい。 After performing each edge, the process proceeds to step 708 and the result is displayed. The values of ρ for the four edges analyzed in this example were 0.86, 0.91, 0.72, and 0.80 in order from the left side of the screen. On the other hand, from the data collection results by direct observation of the cross section, in the analysis by the apparatus and parameters used in this example,

It has been found that the edges in the region are inversely tapered. It was found that all the edges analyzed in this example were inversely tapered. Further, as performed in step 708 of the first embodiment, an average of these four values may be displayed as a value related to one piece of analyzed image data.

(Example 3)
A third embodiment of the present invention will be described with reference to FIG. 2, FIG. 7, and FIG.

  In this embodiment, the similarity between the shapes of two borders of an edge region is represented by variation in the value of the edge region width calculated from each profile, and an example in which the edge taper tendency is evaluated is shown.

According to the same procedure as in the first embodiment, two-dimensional secondary electron distribution data is obtained from steps 701 to 702, and noise reduction and the number of edges are obtained in steps 703 and 704. The result display method was entered. Next, as in Example 2, the points P and Q shown in FIG. 2 are detected for 180 profiles in steps 1501 to 1502 and 1503, and P ₁ , P ₂ ,..., Q ₁ , Q ₂ , ..., and the sets {P _i } and {Q _i } are set as the set of outer and inner boundary points.

Next, the process proceeds to step 1504. Here, the distance w _i between the points P _i and Q _i was calculated for 180 profiles, a set {w _i } was obtained, and the standard deviation σ _w of the distribution of this set was obtained.
After that, the process proceeds to Step 707, and calculation is performed for all the designated edges in the same manner as in Example 2. Then, the process proceeds to Step 708 and the result is displayed.

の領域にあるエッジは逆テーパであることが分かっていた。本実施例で解析したエッジは全て逆テーパであることが分かった。また、実施例１及び実施例２の工程708で行ったように、解析した画像データ１枚に関する値としてこれら４つの値の平均を表示して判断してもよい。 The values of σ _{w for} the four edges were 1.43, 1.28, 3.02, and 2.57. On the other hand, from the data collection results by direct observation of the cross section, in the analysis by the apparatus and parameters used in this example,

It has been found that the edges in the region are inversely tapered. It was found that all the edges analyzed in this example were inversely tapered. Further, as performed in step 708 of the first embodiment and the second embodiment, the average of these four values may be displayed and determined as a value relating to one piece of analyzed image data.

Example 4
A fourth embodiment of the present invention will be described with reference to FIGS. 5, 7, 8, 9, 10, and 16. FIG.

  In this embodiment, an example is shown in which the edge taper tendency is evaluated from the edge roughness and the similarity between the shapes of the two boundaries of the edge region. FIG. 16 is a graph showing the correspondence between the obtained results and the taper tendency.

  First, step 701 in FIG. 7 was executed in the same procedure as in Example 1, and data shown in FIG. 8 was obtained. Further, Steps 702 to 704 were performed in the same procedure as in Example 1, and four edges were selected as analysis targets, and both a graph and a taper tendency index γ were selected as a display format of the results. Further, the area shown in FIG. 9 was designated as a calculation area by the same procedure as in the first embodiment.

  Next, proceeding to step 706, the taper tendency was calculated. The details will be described below with reference to FIG. In this embodiment, roughness and the similarity between two edge region boundary lines are used. Steps 1001 and 1002 are the same as those shown in the first embodiment. In step 1002, detection parameters for edge points and edge boundary points are input. As in Example 1, both edge roughness detection and edge region boundary detection were performed by the threshold method with a threshold value of 70%.

  Proceeding to Step 1003, the edge roughness r (3σ) was calculated by the same procedure as in Example 1. Next, in step 1004, the characteristics of the boundary line of the edge region are digitized. In this embodiment, the correlation coefficient ρ between the boundary lines of the edge region is calculated by the procedure described in the second embodiment. Further, the process proceeds to Step 1005, and here, since the taper tendency index γ is included in the items to be output, the process proceeds to Step 1006 and γ is calculated. Details will be described below.

When the above calculation is performed on the observation image of the resist line pattern edge, the obtained 3σ and ρ pairs are distributed in a region 1601 indicated by hatching in FIG. Here, the horizontal axis r ′ represents the degree of edge roughness, and is an amount obtained by dividing r (unit: nm) by the reference edge roughness magnitude r ₀ (nm). The characteristics of this distribution are the following two points.

  (1) Within this region, the reverse taper tendency increases in the direction of the arrow. (2) However, when ρ is 0.2 or less, it may be determined that there is almost no correlation (not significantly different from 0). What is necessary is just to formulate these characteristics. As an example, there is a method of defining the taper tendency γ as follows.

ここで、式（数９）内に２、（数１０）内に３という係数がかかっているのは、実施例１で求めたテーパ傾向指標と値をほぼ同じ程度の大きさにするためである。上記の条件を用いて解析を行う場合、r₀の値として１０が適当であることが分かった。またこのときα＝０.８であった。図８中の一番左のエッジについて、この式を用いてテーパ傾向指標を計算したところ、γは２.１６であった。 Since the arrow 1602 is approximately on a straight line passing through the origin, it is assumed that ρ = αr ′. Since the reverse taper tendency increases as the distance from the origin increases on this straight line, the distance between the point (r ′, ρ) and the straight line passing through the origin and the straight line may be a reverse taper tendency. When ρ takes a value other than this, the taper tendency may be evaluated only by the degree of roughness. γ can be written as:

Here, the reason why the coefficient of 2 in Formula (Equation 9) and 3 in Formula 10 is applied is to make the taper tendency index obtained in Example 1 and the value approximately the same size. is there. When the analysis was performed using the above conditions, it was found that 10 was appropriate as the value of r ₀ . At this time, α = 0.8. With respect to the leftmost edge in FIG. 8, the taper tendency index was calculated using this equation, and γ was 2.16.

  Next, the process proceeded to step 707. In this embodiment, four edges were selected, and thus the above steps were repeated until the calculation was completed for all. However, in the calculation for the second and subsequent edges, step 1002 was not performed. Next, the results are shown in Step 708. When only the graph display is selected in step 704, only the graph is displayed, but since the taper tendency index is also calculated here, the calculated value is displayed. The index values were 2.16, 2.48, 2.30, 2.56.

  On the other hand, from the data collection results by direct observation of the cross section, in the analysis by the apparatus and parameters used in this example, as in Example 1, if γ satisfies the equation (Equation 4), the vertical is 1.2 or more. It was known that if there is a reverse taper, if it is -1.2 or less, it is a forward taper. From this, the operator can determine that all of these four edges are inversely tapered, but in this example, by inputting this numerical value in advance, a taper tendency is displayed on the screen. As a result, the indication that all are reversely tapered appears here.

  Further, as shown in Examples 1 and 2, it was also possible to obtain the result by taking the average of γ of all the analyzed edges. In this case, an averaged result is obtained for a wider area.

It was also possible to perform the evaluation using the standard deviation σ _w of the distribution of the edge region width obtained in Example 3 instead of ρ. If there is a distortion in the image itself SEM, also when the top of the line pattern is not rounded it is more accurate results using the sigma _w is obtained. However, in other cases, more accurate results can be obtained by using ρ.

  After obtaining the results as described above, the analysis was terminated and the observation was completed.

  In addition, the calculation method and determination method of the taper tendency parameter | index by numerical formula shown to (Equation 9) (Equation 10) are examples. The order and coefficient values of the equation depend on the pattern material and the performance of the device, the values of the parameters in observation and calculation.

(Example 5)
A fifth embodiment of the present invention will be described with reference to FIG.

  In this embodiment, an example in which an edge taper tendency index is obtained using a plurality of taper tendency calculation methods will be described. FIG. 17 shows the procedure of this embodiment.

  First, steps 1701 to 1703 were performed in the same procedure as in Example 1 to obtain data of an image including two line patterns shown in FIG. 8, that is, four edges, and noise was reduced. Next, in step 1704, the number of edges and the region used for calculation were input. Here again, the four edges shown in FIG. 9 and the region to be analyzed are designated in the same procedure as steps 704 and 705 of the first embodiment.

Next, in step 1705, the calculation method of the taper tendency index was selected from the following three. That is, (1) calculation of edge roughness and edge region width, (2) similarity between edge roughness and edge region boundary line, and (3) (1) and (2). When (2) or (3) is selected here, it is selected whether to use the correlation coefficient ρ for the similarity of the edge region boundary line or the standard deviation σ _w of the edge region width distribution. When (3) is selected, the weighted average of the taper tendency index calculated from (1) and (2) is calculated, and the weight is input. Here, (3) was selected, and the method of using the correlation coefficient ρ described in Example 4 was selected as the similarity of the boundary lines. When averaging, the result of (1) is averaged with a weight of 0.4, and the result of (2) is averaged with a weight of 0.6. The method (1) is accurate in detecting the forward taper, and (2) is accurate in detecting the reverse taper. Here, since the pattern pattern of the resist has a tendency to be slightly tee-topped, the ratio is set as described above.

４本のエッジに関する結果は、３.１６、３.８３、２.５７、３.３６であった。γの値が＋であり、絶対値が１.２以上であったので、これらのエッジは全て逆テーパであると判断された。工程1709にて、これらの結果を表示し、観察と解析を終了した。 Next, proceeding to step 1706, first, the taper tendency was calculated for the first edge. Details are described below. Seeking a tapered trend indicator by the first method shown in Example 1, which was used as a gamma _11. γ ₁₁ = 4.65. Next, the same edge, obtains a tapered trend indicator by the method shown in Example 4, which was used as gamma _12. γ ₁₂ = 2.16. Next, in step 1707, it is determined that the calculation has not been completed for all the edges, and the second edge is calculated. Similarly, the third and fourth calculations are performed to obtain γ ₂₁ , γ ₂₂ (second Tapered tendency index for edge), γ ₃₁ , γ ₃₂ (third), γ ₄₁ , γ ₄₂ (fourth). Next, proceeding to step 1708, these were averaged by the following equation. That is,

The results for the four edges were 3.16, 3.83, 2.57, 3.36. Since the value of γ was + and the absolute value was 1.2 or more, all of these edges were determined to be inversely tapered. In step 1709, these results were displayed, and observation and analysis were completed.

(Example 6)
A sixth embodiment of the present invention will be described with reference to FIGS.

  In this embodiment, an example is shown in which the taper angle of the edge is accurately obtained using a plurality of taper tendency calculation methods and an electron microscope having a beam tilt function. FIG. 18 is a flowchart showing the procedure of the present embodiment, FIG. 19 is an analysis result regarding the resist pattern edge obtained by this embodiment, and FIG. 20 is an analysis result regarding the reference data and resist pattern edge obtained by this embodiment. is there.

  In this embodiment, a scanning electron microscope in which the incident angle of the scanning electron beam with respect to the sample is variable was used. Here, the incident angle of the electron beam with respect to the sample, that is, the tilt angle, is defined to be positive when the electron beam is incident from the left to the right of the observer on the observation image. That is, when the left edge of the line in the image has a vertical shape, the tilt angle is positive when it is incident from the direction where it is observed as a forward taper. The direction is a negative tilt angle. If the left edge of the line in the image appears to be vertical in the positive tilt area, the edge is inversely tapered. The opposite is true for the right edge.

  First, the tilt angle is set to 0 °, and in step 1801, the sample is observed in the same procedure as in step 701 in the first embodiment, and the target pattern to be analyzed is determined. Here, the same pattern as in Example 1 was analyzed at the same observation magnification. Next, in step 1802, a region to be analyzed on the observation image is input. Specifically, the number of edges and the area of each edge used for calculation. Here, the same pattern is selected in the same procedure as steps 704 and 705 in Example 1, and all areas are set in the same manner. Next, in step 1803, the calculation method of the taper tendency index γ and various conditions in the calculation are set. Here, it was set in the same manner as in Step 1705 of Example 5.

  Next, in step 1804, conditions for acquiring image data are input. The contents are the number of data accumulations, whether to use autofocus or manually focus. Here, in order to obtain one image, data accumulation, that is, electron beam scanning is set to be performed 128 times, and the focus is automatically adjusted.

  Next, proceeding to step 1805, the minimum and maximum angles and angle increments for changing the tilt angle are input. The angles were entered here as -8, +8, and 2, respectively. As a result, the tilt angles for taking data are −8 °, −6 °, −4 °... + 6 °, + 8 °. After entering the numerical values, the measurement was started. Then, the process proceeds to Step 1806, and the tilt angle is first moved to the minimum value, that is, −8 °. Thereafter, in step 1807, the focus is automatically adjusted and the images are integrated. In addition, it was set so that the irradiation of the electron beam to the sample was stopped every time the designated number of times of scanning was completed.

  In the image obtained here, the analysis region set in step 1802 was also displayed on the screen at the same time. If the center of the pattern image is shifted due to the tilt and the designated area does not include an edge point or edge area, the analysis area can be input again at this stage. Here, the region setting OK is input and the process proceeds to step 1808 as it is. Here, the calculation described in the fifth embodiment is performed, and a simple average of four edges is taken as a taper tendency index γ. At this stage, that is, the value of γ at a tilt angle of −8 ° was −3.2.

  Next, proceeding to step 1809, since the tilt angle has not reached the set maximum value, it is increased by 2 ° to −6 °. Thereafter, the process proceeds to Step 1807, and the same calculation as in the case where the tilt angle is −8 ° is performed at the tilt angle −6 °, and the value of γ is obtained. This was repeated until the specified maximum tilt angle was reached. When calculation was performed at the set maximum tilt angle, the tilt angle automatically returned to 0 °.

  Next, in step 1810, the result was displayed. The graph obtained here is shown in FIG. What is necessary is just to obtain | require the intersection with (gamma) = 0 as the point where an edge is observed in a perpendicular shape. The angles of the intersections were approximately + 1.0 ° for both of the left edges, and −0.8 ° and −1.3 ° for the right edges. From this, it was found that the observed edge averaged a reverse taper shifted by about 1 ° from the vertical.

  As described above, when both the left edge, the right edge, and the right edge are placed in the image and analyzed simultaneously, even if the taper angle is small, the interval between the intersection points of γ = 0 in the graph of the left and right edges is the taper angle. Since it becomes a sum, it tends to be easier to detect except when the taper tendency of the left and right edges is opposite.

  Here, in advance, the sample of the line pattern having the reference vertical edge is observed, the reference data is taken and stored in the memory area, and the observation and the calculation of γ are performed in a short time using this. Was also possible. An example is described below.

  A first application example will be described. First, a silicon substrate was processed to create a line pattern having a vertical edge, and this was observed to obtain reference data indicated by a curve 2001 in FIG. The observation result regarding the edge having an arbitrary taper angle is considered to be obtained by translating this curve in the horizontal axis direction. Thereafter, when the pattern edge of the resist was analyzed, γ was first calculated at a tilt angle of −4 °, and a point 2002 in FIG. 20 was obtained. Therefore, the result obtained for this edge is predicted to be a curve 2001 translated to pass through the point 2002, that is, a broken line 2003, and measured with a tilt angle of + 1 °, + 2 °, + 3 °, As expected, it intersected with γ = 0 around + 2.5 °. Thereby, it turned out that it is a 2.5 degree reverse taper. By using this method, the observation and calculation time can be shortened and more detailed observation can be performed.

  In addition, as a method of using the reference data, there is a second application example in which the tilt function is not used during data measurement as described below. For example, when the curve 2001 of FIG. 20 is recorded in the memory area of the apparatus as reference data, a point 2004 is obtained by performing observation and calculation without using the beam tilt function, that is, at a tilt angle of 0 °. Accordingly, the result obtained for this edge is predicted to be a curve 2001 translated from point 2004, that is, a broken line 2003, and the intersection of the broken line 2003 and γ = 0 is obtained. Since the tilt angle at this intersection was + 2.5 °, this edge was found to be a reverse taper of 2.5 °. In this method, since the taper angle can be calculated only by using the tilt function when acquiring the first reference data, the time can be further reduced.

  The drawback of the above application is that the error may be large because there is only one measurement point. Therefore, it is more accurate to measure at two or more tilt angles, translate the reference curve so that it passes as close as possible to the measurement point (use the least squares method), and find the intersection with γ = 0. Results are obtained. For example, if measurement is performed with no beam tilt and the beam is tilted once and measured, two measurement points can be obtained, and a sufficiently accurate result can be obtained with one beam tilt.

  In addition, when there are a plurality of patterns to be measured and it is desired to increase the throughput, the measurement may be performed as follows. First, the taper angle or γ region to be measured particularly accurately is determined. Here, in order to accurately measure the vicinity of 0 °, it is assumed that particularly accurate measurement is performed for an edge having an absolute value of γ of 1.5 or less. First, the edge is observed without beam tilt, and γ is calculated. If the absolute value of γ is larger than 1.5, it is classified into the inverse taper or taper category at that stage, and the inspection for the edge is finished and the inspection for the next edge is started. If the absolute value of γ is 1.5 or less, the taper angle is accurately measured by the method using the beam tilt function, and after the tilt angle is returned to 0 °, the next edge inspection is performed. If a plurality of edges are inspected in this way, the time required for the inspection can be shortened.

(Example 7)
A seventh embodiment of the present invention will be described with reference to FIG.
In this embodiment, an example in which a focus shift at the time of exposure is measured by calculating a taper tendency index γ related to a resist line pattern edge will be described. FIG. 21 is a graph of the dependency of the taper tendency index obtained by this embodiment on the focus position.

  First, 11 patterns were exposed to a resist film on a silicon wafer using the same mask using a KrF excimer laser exposure apparatus. Each pattern has an exposure area of 1 cm in length and width on the wafer, and is aligned at 2 cm intervals in the vertical direction with the notch of the 8-inch wafer down, and the sixth exposure spot from the top is the center of the wafer. It was in. Of these spots, the patterns observed in this example were all line and space patterns with a pitch of 360 nm, and the patterns were transferred with a constant exposure amount so that the line width would be 180 nm if the focus was appropriate. The exposure spot at the center of the wafer is exposed at the focus position that is considered to be the best focus by the signal from the apparatus. With the notch of the wafer down, the focus is increased in increments of 0.05 μm as it goes upward. It was exposed so as to shift in the direction.

  The 11 exposure spots on the wafer were observed in order from the top using a scanning electron microscope, and the taper tendency index γ was calculated. The method described in Example 5 was used for the calculation method of γ. The result was as shown in the graph of FIG. The horizontal axis of the graph is the order when the spots are counted from the top with the notch down. If γ is between -1.2 and 1.2, the edge is almost vertical, and if it is less than -1.2, it is a forward taper. As the focus is closer to the optimum value, the edge is closer to the vertical, and the forward taper tendency becomes stronger as the focus is away from the optimum value. Depending on the exposure conditions, a reverse taper may appear instead of a forward taper when the focus deviates from the optimum value. In the result of this example, a forward taper appears. It is considered that the best focus is realized at the third to fifth spots from the top where the edges are vertical, particularly the fourth spot which is the center of these three spots.

  From this, it was found that the best focus was shifted in the positive direction from the current setting, and the amount was about 0.10 μm. Based on this information, the focus of the apparatus was shifted by 0.10 μm and set to an appropriate value. For this reason, it was possible to perform wafer exposure with the focus fixed at the optimum value thereafter.

  In order to obtain a more accurate value, the taper tendency may be digitized by the procedure described in the sixth embodiment and displayed as an angle.

  With this method, the focus setting of the apparatus can be performed quickly and accurately prior to exposure of a large amount of wafers, and the appearance rate of defective products due to focus shift can be reduced. Further, by performing this focus check at regular intervals, it is possible to further improve the throughput.

(Example 8)
An eighth embodiment of the present invention will be described with reference to FIGS. 22 shows the dependency of the size of the pattern to be inspected on the exposure amount and focus variation, FIG. 23 shows the dependency of the taper tendency index γ of the inspected pattern on the exposure amount and focus variation, and FIG. 24 is a graph of a part of FIG. It is a thing.

  In this embodiment, an example is shown in which feedback is applied to exposure conditions by observing a resist resist line pattern that has undergone a lithography process.

  First, reference data for associating exposure and focus fluctuations with changes in pattern dimensions and cross-sectional shapes is created according to the following procedure.

  First, a reference pattern is exposed to a wafer on which a resist film has been formed by changing the exposure amount and focus. The pattern of the reference data must be a pattern that also exists on the wafer to be inspected. Also, the smaller the size, the more likely it is subject to exposure and focus fluctuations. In addition, a line and space pattern in which a large number of edges can be simultaneously inserted into the field of view of an image is more desirable because a large amount of data can be obtained with a small number of images.

  Here, an ArF excimer laser exposure apparatus is used as an exposure apparatus, and a binary mask is used to project onto the wafer under the conditions of NA, that is, the numerical aperture of the exposure apparatus illumination system is 0.6 and the coherency is 0.7. A line and space pattern designed to have a line width and a space width of 0.11 μm, 0.12 μm, and 0.15 μm were transferred. Each dimensional pattern consists of 10 lines. The pattern used here spans an area of about 0.5 mm both vertically and horizontally. The above pattern was transferred in a matrix at intervals of 3 mm in both the vertical and horizontal directions by changing the exposure amount D in the horizontal direction and the focus F in the vertical direction with the notch or orientation flat of the wafer down. In this case, the difference between the maximum value and the minimum value of the exposure amount D and the focus F must be large enough to cover the amount of fluctuation that can occur in normal use.

In the resist film and exposure conditions used here, it has been known in advance that the optimum exposure amount of the 0.11 to 0.15 μm line and space pattern is 18 to 20 mJ / cm ² . To cover a variation of ± 20% with respect to this, from 14 mJ / cm ² to 24 mJ / cm ^2, was varied in 0.5 mJ / cm ² increments. For the focus F, the optimum value recognized by the exposure apparatus was set to 0, and the range of ± 0.8 μm was changed in increments of 0.1 μm. As a result, a reference sample wafer on which 17 vertical patterns and 21 horizontal patterns were transferred was produced.

  Second, the wafer is observed with an SEM, and the image data is analyzed and recorded in a storage area of the SEM used as an inspection apparatus. The contents of the analysis are the calculation of the line width W and the calculation of the taper tendency index γ performed on the image observed without using the beam tilt function. The SEM observation conditions of the sample were the same as in Example 1. The voltage was 800 V, the current value was 4.0 pA, the observation magnification was 200,000, the field of view was 675 nm in length and breadth, the number of pixels was 512 × 512, and the number of integrations was 128. In addition, when performing observation, a space that is the center of the 10 line patterns is always arranged at the center of the image so that the two lines enter the left and right objects in the image. Averaging and smoothing for noise reduction were also performed using the same method and parameters as in Example 1.

  Next, the line width was obtained for two lines in the image, and the average was taken as W. Γ was calculated by the method shown in Example 5. All parameters in the calculation are the same as the values shown in the fifth embodiment. As a result, the dependence of W and γ on the focus and the exposure amount was obtained.

  As a result, the focus dependence curve of W becomes a left and right object when F = 0.10 μm is the center, and γ is 0 when F = 0.10 μm at almost all exposure amounts, and the focus starts from here. It was found that the edge deviates from the vertical when the shift occurs. That is, the position that the apparatus recognizes as the best focus is actually +0.10 μm defocus.

  Therefore, the position defocused by -0.10 μm from the display of the device is redefined as the best focus, and the dependency on D of W and the defocus amount (deviation from the best focus), the dependency of γ on D and the defocus amount. The characteristics were recorded in a table and recorded in the storage area of the inspection SEM as reference data. As an example, the case of a 0.11 μm line and space is shown in FIGS. 22 and 23 below.

FIG. 23 and FIG. 24 show the pattern size and γ value in a matrix form when the exposure value (Dose) and the defocus value are given, respectively. When the exposure amount was 16.5 mJ / cm ² or less and when the absolute value of the defocus amount was larger than 0.5 μm, the pattern was not resolved. In the figure, cells without numerical values indicate that the pattern has not been resolved under the conditions. In particular, FIG. 24 shows the defocus dependence of γ when the exposure dose is 18, 20, 22, and 24 mJ / cm ² . Since the value of γ changes with defocusing, it can be used as an index of focus fluctuation.

Next, using the above data, the pattern after the lithography process in mass production was observed by the following procedure to detect a deviation from the optimum values of the exposure amount and focus. Since this inspection wafer contained a 0.11 μm line and space, this was used as an inspection pattern, and image data was acquired with the same method and parameters used during observation and analysis of the reference pattern to reduce noise. After doing so, W and γ were calculated. As a result, it was found that W = 122 nm and γ = 1.2. From the values of W and γ and the tables shown in FIGS. 22 and 23, it can be seen that the current exposure amount is 19.5 mJ / cm ² and the focus position is from −0.22 to −0.23 μm. Based on these results, the exposure amount and focus of the next wafer exposure were corrected.

  If only one exposure amount and defocus amount are not determined from the measurement result, the pattern of other sizes may be measured and compared with the corresponding reference data. The type and size of the reference pattern vary depending on the type of resist and the illumination conditions. In the above example, the line and space pattern is used. However, in the case of annular illumination, an isolated space and an isolated line may be used when the coherency is 0.6 or less.

  By using this method, when the exposure condition deviates from the optimum value, it can be detected and corrected accurately and quickly, and the yield is improved.

  As described above in detail, according to the present invention, it is possible to evaluate the tendency of edges such as reverse taper, vertical, forward taper, etc. from the shape of the pattern only from the sky observation result, and the cross-sectional shape by nondestructive inspection. Can be evaluated. Thereby, the time which evaluation requires can be shortened. Further, since it is not necessary to destroy the wafer, the cost can be reduced and the amount of waste can be reduced. Further, by applying this method to the management of a fine pattern processing step, the pattern transfer step can be controlled quickly and accurately, and the throughput and yield are improved.

  Although all of the above-described embodiments have been described for the observation of the two-dimensional distribution of secondary electrons with a scanning microscope using an electron beam, the secondary electrons emitted from the sample, such as reflected electrons, have been described. The present invention is applicable even when using a two-dimensional distribution of various particles, and even when using a scanning microscope using an ion particle beam, a charged particle beam such as ionizing radiation, and light. Applicable.

  The present invention is summarized as follows.

  (1) A band shape representing the vicinity of the edge of the pattern from two-dimensional distribution information of reflected light intensity, reflected electron intensity, or secondary electron intensity obtained by scanning the substrate on which the pattern is formed with a beam of light or charged particles. The pattern measuring method is characterized in that a taper tendency of the edge cross-sectional shape of the pattern with respect to the substrate is measured by extracting the region and digitizing the shape of the band-like region.

  (2) From the two-dimensional distribution information of reflected light intensity, reflected electron intensity or secondary electron intensity obtained by scanning a light or charged particle beam on the substrate on which the pattern is formed, the edge of the pattern and its vicinity are identified. Detecting a first boundary between an edge area including the area where the pattern does not exist and a second boundary between the edge area and the area where the pattern exists; the first boundary; A step of obtaining a width of the edge region from a difference in position from the boundary of the edge, a step of detecting an edge position of the pattern from the two-dimensional distribution information, and an edge roughness of the edge surface from the detected edge position. Calculating a size, and based on the width of the edge region and the edge roughness, the taper tendency of the cross-sectional shape of the edge of the pattern with respect to the substrate Pattern measurement method is characterized in that configured to measure.

  (3) From the reflected light intensity, reflected electron intensity or secondary electron intensity two-dimensional distribution information obtained by scanning a light or charged particle beam on the substrate on which the pattern is formed, the edge of the pattern and its vicinity are identified. A step of detecting a first boundary line between the edge region including the region where the pattern does not exist and a second boundary line between the edge region and the region where the pattern exists, and the detected first boundary line Obtaining a respective approximate line for the boundary line and the second boundary line; obtaining a difference between the first boundary line and the second boundary line; and the approximate line; and Based on the correlation coefficient based on the correlation coefficient, and obtaining a correlation coefficient representing the similarity of the shape between the first boundary line and the second boundary line in the edge region. Pa Pattern measurement method is characterized in that configured to measure a taper tends to said substrate N'ejji.

  (4) From the two-dimensional distribution information of reflected light intensity, reflected electron intensity or secondary electron intensity obtained by scanning the substrate on which the pattern is formed with light or a charged particle beam, the edge of the pattern and its vicinity are identified. Detecting a first boundary between an edge area including the area where the pattern does not exist and a second boundary between the edge area and the area where the pattern exists; the first boundary; A step of calculating a plurality of widths of the edge region from a difference in position with the boundary of the boundary, a step of calculating a distribution of the calculated width values of the edge regions of the plurality of locations, and a value of the width of the edge region And calculating the taper tendency of the pattern edge in the pattern cross-sectional shape with respect to the substrate based on the standard deviation. Pattern measurement method.

  (5) In the configuration of (3) or (4), a step of detecting an edge position of the pattern from the two-dimensional image information, and a size of edge roughness of the edge surface is calculated from the detected edge position. A pattern measuring method comprising the steps of:

  (6) From the reflected light intensity, reflected electron intensity or secondary electron intensity two-dimensional distribution information obtained by scanning a light or charged particle beam on the substrate on which the pattern is formed, the edge of the pattern and the vicinity thereof are identified. Detecting a first boundary between an edge region including the region where the pattern does not exist and a second boundary between the edge region and a region where the pattern exists, and the first boundary A step of obtaining the width of the edge region from the difference in position between the boundary and the second boundary, and an approximation line for each set of points representing the detected first boundary and the second boundary. Determining a difference between each set of points of the first boundary and the second boundary and the approximate line, and thereby the first boundary line and the second boundary line in the edge region And shape of From the step of obtaining a correlation coefficient representing similarity and the difference in position between the first boundary and the second boundary, the width of the edge region is obtained by calculating a plurality of widths of the edge region. , Calculating at least one of the steps of calculating the standard deviation, and detecting the edge position of the pattern from the two-dimensional distribution information to calculate the edge roughness of the edge surface; A pattern measuring method comprising:

  (7) In the configuration of (2), (3), or (4), an angle formed between a beam of light or charged particles emitted toward the substrate and the substrate is set to a predetermined value, A pattern measuring method configured to obtain the two-dimensional distribution information.

  (8) In the configuration of (7), the angle between the beam and the substrate is changed to obtain the two-dimensional distribution information, and at least the width of the edge region and the correlation coefficient obtained are Calculating an index representing a taper tendency of the pattern edge in the pattern cross-sectional shape with respect to the substrate from one or more quantities and the size of the edge roughness, and the width of the edge region, the correlation coefficient, and the A pattern measurement method characterized by displaying a relationship between at least one amount of indices representing a taper tendency and the angle.

  (9) A charged particle source, a charged particle beam emitted from the charged particle source, irradiating the sample through a converging lens, a deflector, and an objective lens to deflect and scan the sample, and the sample are mounted A stage, a detector for detecting the intensity of secondary electrons or reflected electrons emitted from the sample by the charged particle beam irradiation, a control system for controlling the deflection / scanning, and the obtained secondary electrons or reflected electrons Signal processing means for extracting a band-like area representing the vicinity of the edge of the pattern from the two-dimensional distribution information of the intensity, and quantifying the shape of the band-like area; A pattern measuring apparatus configured to measure a taper tendency.

  (10) From the two-dimensional distribution information of reflected light intensity, reflected electron intensity or secondary electron intensity obtained by scanning the substrate on which the pattern is formed with a beam of light or charged particles, the edge of the pattern and its vicinity are identified. Detecting a first boundary between an edge area including the area where the pattern does not exist and a second boundary between the edge area and the area where the pattern exists; the first boundary; A step of obtaining a width of the edge region from a difference in position from the boundary of the edge, a step of detecting an edge position of the pattern from the two-dimensional distribution information, and an edge roughness of the edge surface from the detected edge position. Based on the step of calculating the size, the width of the edge region, and the edge roughness, the taper tendency of the cross-sectional shape of the edge of the pattern to the substrate is measured. That comprises the steps, wherein a tapered trend measurement result, the pattern process control method characterized by being configured to control a step of transferring a desired pattern on the substrate.

  (11) Two-dimensional distribution information of reflected light intensity, reflected electron intensity, or secondary electron intensity obtained by observing a pattern formed on a substrate with a scanning microscope using light, electrons, ionizing radiation, or ion particle beams. To measure the angle of the edge of the pattern cross-sectional shape with respect to the substrate, that is, the taper tendency, and represents the region where the intensity of reflected light, reflected electrons, or secondary electrons is high in the two-dimensional plane, that is, the edge of the pattern and its vicinity. A step of detecting a boundary between a region, that is, an edge region and a region adjacent to the reflected light, a reflected electron, or a region where the intensity of secondary electrons is low, and a boundary between the edge region and a region where no pattern exists among the boundary of the edge region A set of points representing the point, that is, the first boundary and the point representing the boundary between the edge region and the region where the pattern exists Detecting a set, i.e., a second boundary, and calculating a width of an edge region from a difference in position between the first boundary and the second boundary, and detecting an edge position A taper tendency measuring method comprising: a step; and a step of calculating a roughness level of the edge from the detected edge position.

  (12) Two-dimensional distribution information of reflected light intensity, reflected electron intensity, or secondary electron intensity obtained by observing a pattern formed on a substrate with a scanning microscope using light, electrons, ionizing radiation, or ion particle beams To measure the angle of the edge of the pattern cross-sectional shape with respect to the substrate, that is, the taper tendency, and represents the region where the intensity of reflected light, reflected electrons, or secondary electrons is high in the two-dimensional plane, that is, the edge of the pattern and its vicinity. A step of detecting a boundary between a region, that is, an edge region and a region adjacent to the reflected light, a reflected electron, or a region where the intensity of secondary electrons is low, and a boundary between the edge region and a region where no pattern exists among the boundary of the edge region A set of points representing the point, that is, the first boundary and the point representing the boundary between the edge region and the region where the pattern exists Detecting a set, that is, a second boundary; obtaining an approximate line for each detected boundary; and obtaining a set of differences between the approximate line and each point representing the boundary, ie, fluctuation of the boundary, for each boundary. And a step of obtaining a correlation coefficient between the fluctuation of the first boundary and the fluctuation of the second boundary.

  (13) Two-dimensional distribution information of reflected light intensity, reflected electron intensity, or secondary electron intensity obtained by observing a pattern formed on a substrate with a scanning microscope using light, electrons, ionizing radiation, or ion particle beams. Is a method of measuring the angle of the edge of the pattern cross-sectional shape with respect to the substrate, that is, a taper tendency, and represents a region where the intensity of reflected light, reflected electrons, or secondary electrons is high in the two-dimensional plane, that is, the edge of the pattern and its vicinity. A step of detecting a boundary between a region, that is, an edge region and a region adjacent to the reflected light, a reflected electron, or a region where the intensity of secondary electrons is low, and a boundary between the edge region and a region where no pattern exists among the boundary of the edge region A set of points representing the point, that is, the first boundary and the point representing the boundary between the edge region and the region where the pattern exists A step of detecting a set, that is, a second boundary; a step of calculating a plurality of edge region widths from the positions of these boundaries; and a step of obtaining a distribution of edge region width values calculated in the step. And a step of obtaining the standard deviation from the distribution of the values of the width of the edge region.

  (14) The taper tendency measurement method according to (12) to (13), including a step of detecting an edge position, and a step of calculating a roughness level of the edge from the detected edge position. A taper tendency measuring method characterized.

  (15) In the taper tendency measuring method according to (1) to (4), the width of the edge region with respect to the observed edge, the correlation coefficient between the fluctuation of the first boundary and the fluctuation of the second boundary, A taper tendency characterized by calculating one or more standard deviations in the distribution of width values of the edge region and the edge roughness and calculating an index representing the taper tendency of the edge from these values. Measurement method.

  (16) The taper tendency measuring method according to any one of (1) to (5) above, wherein light, electrons, ionizing radiation, or ion particle beams emitted toward a substrate for observing a pattern formed on the substrate, A taper tendency measuring method characterized in that after setting an angle with a substrate to a desired angle, two-dimensional distribution information of reflected light intensity, reflected electron intensity, or secondary electron intensity is obtained.

  (17) The taper tendency measuring method according to (16), wherein two-dimensional distribution information of reflected light intensity, reflected electron intensity, or two-dimensional electron intensity is obtained for two or more values as the angle. Trend measurement method.

  (18) The taper tendency measuring method according to any one of (6) to (7), wherein light, electrons, ionizing radiation, or ion particle beams emitted toward the substrate in order to observe a pattern formed on the substrate, By changing the angle with the substrate, two-dimensional distribution information of reflected light intensity, reflected electron intensity, or secondary electron intensity is repeatedly obtained, and the width of the edge region, the fluctuation of the first boundary, and the fluctuation of the second boundary. The relationship between the angle and one or more of the correlation coefficient, the index value indicating the taper tendency calculated from one or both of them and the magnitude of the roughness, and the angle is displayed as a table or a graph. A taper tendency measuring method characterized by the above.

  (19) The taper tendency measurement method according to (8), wherein an angle of the edge with respect to the ground, that is, a taper angle is calculated from the obtained table or graph.

  (20) In the step of processing a substrate by transferring a desired pattern to the substrate, the shape of the pattern formed on the substrate is measured, and the actual value of the variable condition in the pattern transfer or substrate processing step is determined from the feature. A method for calculating a deviation from an optimum value, wherein the taper angle evaluation method of (1) to (9) is used.

  (21) A charged particle beam source, a charged particle optical system that irradiates a sample with a charged particle beam source emitted from the charged particle beam source through a focusing lens, a deflector, and an objective lens, and deflects and scans the sample. A stage to be mounted; a detector for detecting the intensity of secondary electrons or reflected electrons emitted from the sample by the charged particle beam irradiation; and a control system for controlling the deflection / scanning. And a signal processing means for obtaining a width or shape of an area representing edge roughness and edge vicinity of the pattern from the two-dimensional distribution of the intensity of the secondary electrons or reflected electrons.

The schematic diagram which shows the example of the two-dimensional image of the pattern obtained by SEM observation. The figure which shows the example of the cross-sectional profile obtained by SEM observation. The conceptual diagram which shows the relationship between a cross-sectional profile signal and an edge area | region. The figure showing the relationship between the width | variety of a roughness and an edge area | region, and a taper tendency. The figure showing the relationship between the correlation of roughness and the boundary line of an edge area | region, and a taper tendency. The conceptual diagram which shows the apparatus structure of the 1st Example of this invention. The figure which shows the procedure of the 1st, 2nd, 3rd Example of this invention. The conceptual diagram which shows the example which imaged the two-dimensional part of the secondary electron intensity analyzed in the 1st Example of this invention. The conceptual diagram explaining the example which imaged the two-dimensional part of the secondary electron intensity analyzed in the 1st Example of this invention. The figure which shows a part of procedure of the 1st Example of this invention in detail. The conceptual diagram which shows the relationship between a cross-sectional profile, an edge point, and edge area width. The figure showing the result obtained by the 1st Example of this invention. The figure used for taper angle calculation in the 1st example of the present invention. The conceptual diagram of the pattern cross section which shows the definition of the taper angle used in the Example of this invention. The figure which shows a part of procedure of the 2nd and 3rd Example of this invention in detail. The figure which shows the correspondence of the calculation result obtained by the 4th Example of this invention, and a taper tendency. The figure which shows the procedure of the 5th Example of this invention. The figure which shows the procedure of the 6th Example of this invention. The figure which shows the beam tilt angle and taper tendency which were obtained by the 6th Example of this invention. The figure showing the relationship between the data for a reference in the 6th Example of this invention, and a measurement result. The figure showing the taper tendency obtained by the 7th Example of this invention. The figure which shows the reference data of the pattern dimension obtained by the 8th Example of this invention. The figure which shows the reference data of the taper tendency obtained by the 8th Example of this invention. The figure which shows the defocus dependence of the taper tendency obtained by the 8th Example of this invention.

Explanation of symbols

  101 ... A region showing the vicinity of the edge of a line in the image, 102 ... A region where the background portion in the image is exposed and looks dark, 103 ... A region where the line pattern in the image exists and looks dark, 601 ... Scanning electron Case of line microscope, 602 ... electron gun, 603 ... electron beam, 604 ... converging lens, 605 ... deflector, 606 ... objective lens, 607 ... sample, 608 ... stage, 609 ... secondary electron, 610 ... detector, 611 ... Control system of scanning electron microscope, 612 ... Computer for inspection, 701 ... Pattern observation, 702 ... Incorporation of secondary electron intensity distribution data, 703 ... Noise reduction by image processing, 704 ... Number of edges, Result output format Input, 705 ... Calculation area designation, 706 ... Calculation of taper tendency, 707 ... Judgment whether or not calculation has been completed for all edges, 708 ... Result display, 801 ... Registry pattern in the image exists and appears dark , 802 ... First line in the image Area indicating the vicinity of the left edge, 803 ... Area indicating the vicinity of the right edge of the first line in the image, 804 ... Area indicating the vicinity of the second line left edge in the image, 805 ... Second area in the image 806... A region indicating the vicinity of the right edge of the line, 806... A region where the background portion in the image is exposed and appearing dark, 901... A calculation region designated for performing analysis on the left edge of the first line, 902. A calculation area designated to perform analysis on the right edge of the second line, 903... A calculation area designated to perform analysis on the left edge of the second line, 904... To perform analysis on the right edge of the second line. 1001 ... determining the necessity of inputting numerical values for parameters, 1002 ... inputting numerical values, 1003 ... calculating edge roughness, 1004 ... quantifying features of edge region boundary shape, 1005 ... tapering tendency Calculate index γ Whether or not, 1006 ... γ is calculated, 1201 ... A straight line representing a vertical edge in the graph of edge roughness vs. edge region width, 1202 ... A point representing the roughness and edge region width of a line edge obtained from actual image data, 1401 ... Registration pattern, 1402 ... Pattern of pattern, 1501 ... Judgment of necessity of inputting numerical value of parameter, 1502 ... Input of numerical value, 1503 ... Detection of boundary point of edge region, 1504 ... Similar boundary shape of edge region 1601 ... Area where the actual measurement result of the degree of roughness and correlation coefficient is distributed, 1602 ... An arrow indicating the direction of transition from the forward taper to the reverse taper in the area in the graph, 1701 ... Pattern observation, 1702 ... Acquisition of secondary electron intensity distribution data, 1703 ... Noise reduction by image processing, 1704 ... Input of number of edges and area to be analyzed, 1705 ... Selection of calculation method and parameters for calculation Setting, 1706 ... Calculate index of taper tendency, 1707 ... Determine whether calculation is completed for all edges, 1708 ... Calculate average of index, 1709 ... Display result, 1801 ... Pattern observation, 1802 ... Number of edges and analysis 1803 ... Set the observation condition when acquiring image data, 1805 ... Tilt angle input, 1806 ... Beam tilt to the minimum value, 1807 ... Image data with focus Integration, 1808 ... Taper tendency index γ calculation, 1809 ... Judgment whether the tilt angle reaches the maximum value of the input range, 1810 ... Result display, 2001 ... Standard obtained by performing beam tilt on the standard sample Reference curve indicating a taper tendency index, 2002, 2004: Points indicating results obtained from actual samples, 2003: Curve obtained by translating the reference curve from one measurement result.

Claims (9)

Two-dimensional distribution of signals obtained by detecting charged particles secondary emitted from the sample or light reflected from the sample by irradiating the sample with the pattern formed with a charged particle beam or light A two-dimensional distribution data acquisition device for acquiring data;
In a measurement apparatus comprising a computer that processes the two-dimensional intensity distribution data,
The computer extracts a band-like region representing the vicinity of the edge of the pattern from the two-dimensional distribution data,
An apparatus for measuring a taper tendency of the edge cross-sectional shape of the pattern with respect to the substrate by digitizing the shape of the extraction region. Two-dimensional distribution of signals obtained by detecting charged particles secondary emitted from the sample or light reflected from the sample by irradiating the sample with the pattern formed with a charged particle beam or light A two-dimensional distribution data acquisition device for acquiring data;
In a measurement apparatus comprising a computer that processes the two-dimensional intensity distribution data,
The computer includes edge point data corresponding to a first boundary defining a band-like region representing the vicinity of an edge of the pattern, and edge point data corresponding to a second boundary defining the band-like region, Extracted from the two-dimensional intensity distribution data;
Calculating a difference between the data of the edge point of the first boundary and the data of the edge point of the second boundary, and a correlation function;
A measuring apparatus comprising a function of measuring a taper tendency of the pattern based on the difference and the correlation function. The measuring device according to claim 1,
The computer
Extracting edge point data corresponding to the first boundary defining the band-shaped region and edge point data corresponding to the second boundary defining the band-shaped region from the two-dimensional intensity distribution data,
The difference between the edge point data of the first boundary and the edge point data of the second boundary, the edge roughness of the edge point data of the first boundary, and the edge roughness of the edge point data of the second boundary are calculated. And
A measuring apparatus for measuring a taper tendency of the pattern from the difference and edge roughness. The measuring device according to claim 1,
The computer uses the two-dimensional intensity distribution data of edge point data corresponding to a first boundary defining the band-shaped region and edge point data corresponding to a second boundary defining the band-shaped region. Extracted from
The computer
The correlation function between the edge point data of the first boundary and the edge point data of the second boundary, the edge roughness of the edge point data of the first boundary, and the edge roughness of the edge point data of the second boundary Calculate
A measuring apparatus for measuring a taper tendency of the pattern from the correlation function and edge roughness. The measuring device according to any one of claims 1 to 4,
The two-dimensional distribution data acquisition apparatus has a function of tilting the charged particle beam or light to irradiate the sample. In the measuring device according to claim 5,
The computer
Calculate the taper tendency from the two-dimensional distribution data obtained by irradiating the charged particle beam or light to the sample while changing the tilt angle,
A measuring apparatus for calculating the tilt angle dependence of the taper tendency. In the measuring device according to any one of claims 1 to 4,
The taper tendency is classified into three types of cross-sectional shapes of pattern edges: vertical, forward taper, reverse taper, and tee top. In the measuring device according to any one of claims 1 to 7,
A measuring apparatus comprising a display screen on which a measured taper tendency or a tilt angle dependency of a taper tendency is displayed. In the measuring device according to any one of claims 1 to 8,
A measuring apparatus using a scanning electron microscope as the two-dimensional distribution data acquiring apparatus.

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