Pattern measuring device, program for pattern measurement, and pattern measuring method
Patent Information
- Application Number
- JP2023170150
- Authority / Receiving Office
- JP · JP
- Patent Type
- Applications
- Current Assignee / Owner
- Filing Date
- 2023-09-29
- Publication Date
- 2026-08-25
AI Technical Summary
Existing mode measurement devices are difficult to accurately measure the center-to-center distance when forming patterns using self-assembly lithography (DSA) methods, especially when image processing errors or pattern structure periods are broken.
A mode measurement device is designed, including a dimensional measurement unit, an outlier value removal unit and a representative value determination unit. By performing statistical outliers on the dimension values measured by multiple measurements and at least two outliers removed, ensuring that the outliers caused by measurement errors and pattern structure are removed, thereby calculating representative dimension values with high accuracy.
Through multiple statistical outliers processing, measurement errors and mode structure outliers can be effectively removed, the accuracy and reliability of mode measurements can be improved, and the accuracy of representative dimension values can be ensured.
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Abstract
Description
[Technical field]
[0001] The present invention relates to a pattern measuring device, a pattern measuring program, and a pattern measuring method. [Background technology]
[0002] In recent years, in the field of semiconductor manufacturing, research has been progressing on microfabrication technology that forms patterns using a method called self-organization lithography (DSA).
[0003] One possible device for evaluating the formed pattern is shown in Patent Document 1. The pattern measuring device in Patent Document 1 determines the center-to-center distance between adjacent holes or dots in a captured image of a pattern (e.g., a hole pattern or a dot pattern) formed by the DSA method, and sets the arithmetic average value of the determined center-to-center distance as a reference value for the center-to-center distance.
[0004] However, since the center-to-center distance is calculated by processing the captured image, outliers may be included due to improper image processing, making it impossible to calculate the center-to-center distance with high accuracy. Also, when a defect occurs in the formation of a pattern using the DSA method, such as the collapse of a periodic structure, outliers may be included, making it impossible to calculate the center-to-center distance with high accuracy. [Prior art documents] [Patent documents]
[0005] [Patent Document 1] JP 2017-67443 A Summary of the Invention [Problem to be solved by the invention]
[0006] Therefore, the present invention has been made to solve the above-mentioned problems, and it is an object of the present invention to measure the dimensions of a pattern with high accuracy by using statistical outlier processing. [Means for solving the problem]
[0007] That is, the pattern measuring device of the present invention is a pattern measuring device that measures the dimensions of a pattern formed on a sample, and is characterized in that it comprises a dimension measuring unit that measures the dimensions of the pattern, an outlier removal unit that performs statistical outlier processing at least twice on a plurality of dimension values measured by the dimension measuring unit, and a representative value determination unit that determines a representative dimension value of the pattern from one or more of the dimension values from which outliers have been removed by the outlier removal unit.
[0008] In such a pattern measuring device, statistical outlier processing is performed at least twice on the multiple dimension values measured by the dimension measuring unit, so that outliers due to measurement errors in the dimension measuring unit or outliers due to the structure of the pattern can be suitably removed, and the representative dimension value of the pattern can be obtained with high accuracy. In addition, because outliers are removed from the multiple dimension values by statistical outlier processing, the reliability or objectivity of the obtained representative dimension value can be guaranteed.
[0009] As a specific embodiment of the statistical outlier processing, it is preferable that the outlier removal unit performs the outlier processing at least twice, in which a value outside the interquartile range for the plurality of dimension values is set as an outlier. Here, a value outside the interquartile range is a value smaller than 1.5 times "first quartile - interquartile range" and a value larger than 1.5 times "third quartile + interquartile range." Note that 1.5 times can be changed.
[0010] As a specific embodiment of the statistical outlier processing, it is desirable that the outlier removal unit mainly removes outliers due to measurement errors of the dimension measurement unit in a first round of the outlier processing, and mainly removes outliers due to the structure of the pattern in a second round of the outlier processing.
[0011] As a specific embodiment of the dimension measuring unit, it is preferable that the dimension measuring unit measures the dimensional values of the pattern by image recognition of a captured image of the sample.
[0012] It is desirable that the dimension measuring section measures the dimension values of the pattern that is included in the entire captured image or in 90% or more of the captured image. With this configuration, it is possible to increase the number of data points for the pattern dimensional values, thereby improving the reliability or objectivity of the representative dimensional values obtained from them.
[0013] As a specific embodiment for determining the representative dimension value, it is preferable that the representative value determination unit calculates an arithmetic average of the plurality of dimension values from which outliers have been removed, and sets the calculated representative dimension value as the representative dimension value.
[0014] The pattern measurement apparatus of the present invention desirably measures the dimensions of a pattern formed by self-organization of a polymer.
[0015] It is also desirable that the pattern has a plurality of holes or dots formed periodically, and that the dimension measuring unit measures the center-to-center distance between adjacent holes or dots, or the diameter of the holes or dots.
[0016] Furthermore, a pattern measurement program according to the present invention is a pattern measurement program for measuring dimensions of a pattern formed on a sample, characterized in that the program has a computer function as a dimension measurement unit that measures the dimensions of the pattern, a function as an outlier removal unit that performs statistical outlier processing at least twice on a plurality of dimension values measured by the dimension measurement unit, and a function as a representative value determination unit that determines a representative dimension value of the pattern from one or more dimension values from which outliers have been removed by the outlier removal unit.
[0017] Furthermore, a pattern measurement method according to the present invention is a pattern measurement method for measuring a dimension of a pattern formed on a sample, which is characterized in that the dimensions of the pattern are measured, statistical outlier processing is performed at least twice on a plurality of measured dimension values, and a representative dimension value of the pattern is obtained from one or more of the dimension values from which the outliers have been removed. Effect of the Invention
[0018] In this way, according to the present invention, the pattern dimensions can be measured with high accuracy using statistical outlier processing. [Brief description of the drawings]
[0019] [Figure 1] 1 is a schematic diagram showing a configuration of a pattern measuring device according to an embodiment of the present invention; [Diagram 2] 1A is a diagram showing a captured image obtained by image recognition of a pattern according to the embodiment, and FIG. [Diagram 3] In the same embodiment, (a) raw data of the dimensional value distribution, (b) data after the first outlier processing in the dimensional value distribution, and (c) data after the second outlier processing in the dimensional value distribution. [Figure 4] 4 is a flowchart of a pattern measuring method according to the embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS
[0020] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of a pattern measuring device according to the present invention will be described below with reference to the drawings. In addition, in any of the drawings shown below, for the purpose of easy understanding, some parts are omitted or exaggerated in schematic form as appropriate. The same components are denoted by the same reference numerals and the description thereof is omitted as appropriate.
[0021] <Configuration of Pattern Measuring Apparatus 100> The pattern measuring device 100 according to this embodiment measures the dimensions of a pattern formed by utilizing the self-organization of a polymer by, for example, a self-organizing lithography method (DSA method). Here, the formed pattern may be a hole pattern in which a plurality of holes are periodically formed, or a dot pattern in which a plurality of dots are periodically formed.
[0022] Specifically, as shown in FIG. 1, the pattern measuring device 100 includes a dimension measuring unit 2 that measures the dimensions of a pattern, an outlier removing unit 3 that performs statistical outlier processing on a plurality of dimension values L measured by the dimension measuring unit 2, and a representative dimension value L of the pattern from the plurality of dimension values L from which outliers have been removed by the outlier removing unit 3. 0 and a representative value determining unit 4 for determining a representative value.
[0023] In this embodiment, the dimension measurement unit 2, outlier removal unit 3, and representative value determination unit 4 are configured by a computer having a CPU, memory, input / output interface, AD converter, output means such as a display 101, input means such as a keyboard, etc., and the functions of these units are realized by the CPU and peripheral devices working together based on a pattern measurement program stored in the memory. The functions of the dimension measurement unit 2, outlier removal unit 3, and representative value determination unit 4 may each be realized by a separate computer.
[0024] Each of parts 2 to 4 will be described in detail below. The dimension measuring unit 2 measures the dimensional values of a plurality of patterns (holes or dots) by image recognition of a captured image of the sample W. The dimension measuring unit 2 of this embodiment measures the center-to-center distance L (see FIG. 2) of the plurality of patterns (holes or dots). The captured image is captured by an imaging device 200 such as a scanning electron microscope.
[0025] Specifically, the dimension measuring unit 2 extracts the centers of multiple patterns (holes or dots) included in the entire captured image. Here, as shown in Fig. 2, the dimension measuring unit 2 detects the contours of each of the multiple patterns (holes or dots) and extracts the center coordinates of the circumscribing circle or inscribing circle of the contour.
[0026] Then, the dimension measuring unit 2 determines, for example, the distance between each of the extracted centers and three adjacent centers (center-to-center distance L). Note that, for example, the dimension measuring unit 2 may determine, for each of the extracted centers, the distance between each of the extracted centers and one or more adjacent centers (center-to-center distance L).
[0027] In the pattern shown in FIG. 2, holes or dots are formed in a roughly hexagonal close-packed lattice pattern, and the distance between six adjacent centers (center-to-center distance L) may be obtained. However, if the pattern structure is irregular and obtaining the distance between the six centers (center-to-center distance L) results in a lot of noise, it may be possible to obtain the distance between each extracted center and five or fewer adjacent centers (center-to-center distance L).
[0028] The outlier removal unit 3 executes statistical outlier processing for the multiple dimensional values L measured by the dimension measurement unit 2. The outlier processing of this embodiment treats values outside the interquartile range for the multiple dimensional values L as outliers. Here, a value outside the interquartile range is a value smaller than 1.5 times the "first quartile - interquartile range" and a value larger than 1.5 times the "third quartile + interquartile range." Note that 1.5 times can be changed.
[0029] Specifically, the outlier removal unit 3 executes statistical outlier processing at least twice. There is an advantage to performing outlier processing on the dimension values of a pattern formed by DSA as in this embodiment. That is, since the pattern is formed by DSA, there are parts where the periodic structure is distorted and holes are not clearly formed. By removing the dimension values L of such parts as outliers, it is possible to obtain a representative dimension value L that is highly accurate and likely. 0 , that is, L when the synthesis reaction is successful 0 can be easily found.
[0030] Here, the outlier removal unit 3 performs a first outlier processing on the multiple dimension values L measured by the dimension measurement unit 2 (see FIG. 3(b)). The outlier removal unit 3 also performs a second outlier processing on the multiple dimension values L from which the outliers have been removed by the first outlier processing (see FIG. 3(c)). In the first outlier processing, outliers due to measurement errors by the dimension measurement unit 2 are primarily removed. In the second outlier processing, outliers due to the pattern structure are primarily removed.
[0031] The representative value determination unit 4 determines a representative dimension value L of the pattern from the plurality of dimension values L from which the outliers have been removed by the outlier removal unit 3. 0 Specifically, the representative value determination unit 4 calculates a representative dimension value L by averaging the multiple dimension values L from which the outliers have been removed by the above two outlier processing operations. 0 Let us assume that.
[0032] In this embodiment, the center-to-center distance L obtained by the dimension measuring unit 2 from the captured image is the number of pixels. The representative value determining unit 4 calculates the average of the multiple dimension values L from which the outliers have been removed, and multiplies the average value by a conversion value per pixel to obtain the representative dimension value L. 0 The actual center distance (nm) is calculated as follows. Here, the conversion value per pixel is obtained in nm per pixel from the scale displayed in the captured image. Specifically, the vertically long rectangle is image-recognized to obtain the coordinates of all the scale marks. The number of pixels from the right-most coordinate to the left-most coordinate of the scale mark is obtained, and the conversion value is calculated by dividing the scale mark size (for example, 500 nm) by this value. The scale mark size may also be obtained by image recognition.
[0033] <Pattern measurement method> First, the sample W on which the pattern P is formed by the DSA method is imaged by the imaging device 200 such as a scanning electron microscope (step S1).Then, the captured image is input to the pattern measuring device 100 (step S2).
[0034] The input captured image is subjected to image recognition by the dimension measuring unit 2, and the dimensions (center-to-center distance L) of a plurality of patterns (holes or dots) are measured (step S3).
[0035] Then, the multiple dimensional values L measured by the dimension measuring unit 2 are input to the outlier removing unit 3. Then, the outlier removing unit 3 performs a first outlier processing on the multiple dimensional values L (step S4), and performs a second outlier processing on the multiple dimensional values L from which the outliers have been removed by the first outlier processing (step S5).
[0036] The plurality of dimension values L after the above two outlier processing steps are input to a representative value determination unit 4. The representative value determination unit 4 uses the plurality of dimension values L from which the outliers have been removed to determine a representative dimension value L of the dimensions (center-to-center distance L) of the plurality of patterns (holes or dots). 0 is determined (step S6).
[0037] In addition, the captured image, the captured image with image recognition (such as an image with a circumscribed circle or an inscribed circle recognized), and the determined representative dimension value L 0 etc. can be displayed on the display 101 etc. of the pattern measuring device 100.
[0038] <Effects of this embodiment> As described above, according to the pattern measuring device 100 of the present embodiment, the statistical outlier processing is performed at least twice on the multiple dimension values L measured by the dimension measuring unit 2, so that outliers due to the measurement error of the dimension measuring unit 2 or outliers due to the structure of the pattern can be suitably removed, and the representative dimension value L of the pattern P can be obtained. 0 In addition, by performing statistical outlier processing, outliers are removed from the multiple dimension values L, so the obtained representative dimension value L 0 The reliability or objectivity of the information can be guaranteed.
[0039] <Other embodiments> In the above embodiment, the center-to-center distance L is obtained as the dimension of the pattern P, but other dimensions may be obtained. For example, the dimension measuring unit 2 may obtain the circumscribing circle or inscribing circle of the pattern (hole or dot), and then the radius of the pattern (hole or dot) may be measured from the circumscribing circle, inscribing circle, or a circle between the circumscribing circle and the inscribing circle. In this case, the representative value determining unit 4 determines a representative value of the radius of the pattern (hole or dot) from a plurality of dimension values from which outliers have been removed by the outlier removing unit 3. In addition, both the center-to-center distance L and the radius of the pattern P are measured as the dimensions of the pattern P, and the representative dimension value L is obtained. 0 Alternatively, both the representative value of the radius and the representative value of the radius may be determined.
[0040] Further, the outlier remover 3 in the above embodiment executes the outlier processing twice, but may execute it three or more times.
[0041] Furthermore, the outlier remover 3 in the above embodiment performs the same outlier processing twice, but the first outlier processing and the second outlier processing may be different.
[0042] Moreover, in the above embodiment, the dimensions of the pattern P formed by the DSA method are measured, but the dimensions of other patterns P may also be measured.
[0043] In the above embodiment, the dimension measuring unit 2 measures the dimension of the pattern P on a pixel basis, but the actual dimension value may be converted using the nm conversion value of the pixel value. In this case, the representative value determining unit 4 does not need to convert to the actual dimension value using the nm conversion value.
[0044] In addition, various modifications and combinations of the embodiments may be made without departing from the spirit of the present invention. [Explanation of symbols]
[0045] 100 Pattern measuring device W... Sample P···Pattern 2. Dimension measurement section 3. Outlier removal 4. Representative value determination section
Claims
1. A pattern measuring device for measuring the dimensions of a pattern formed on a sample, A dimension measuring unit for measuring the dimensions of the aforementioned pattern, An outlier removal unit that performs statistical outlier processing at least twice on a plurality of dimensional values measured by the dimensional measuring unit, A pattern measuring device comprising: a representative value determination unit that determines a representative dimensional value of the pattern from one or more dimensional values from which outliers have been removed by the outlier removal unit.
2. The pattern measuring device according to claim 1, wherein the outlier removal unit performs a process at least twice to treat values that fall outside the interquartile range of the plurality of dimensional values as outliers.
3. The outlier removal unit, In the first outlier processing step, the primary purpose is to remove outliers caused by measurement errors in the dimension measuring unit. The pattern measuring device according to claim 1 or 2, wherein in the second outlier processing, outliers due to the structure of the pattern are mainly removed.
4. The pattern measuring device according to claim 1 or 2, wherein the dimension measuring unit measures the dimensional values of the pattern by image recognition of the captured image of the sample.
5. The pattern measuring device according to claim 4, wherein the dimension measuring unit measures the dimension values of the pattern that are included in the whole or 90% or more of the captured image.
6. The pattern measuring device according to claim 1 or 2, wherein the representative value determination unit obtains the representative dimension value by adding and averaging a plurality of the dimension values from which outliers have been removed.
7. The pattern measuring device according to claim 1 or 2, wherein the pattern is formed by the self-assembly of a polymer.
8. The aforementioned pattern is formed by the periodic formation of multiple holes or dots. The pattern measuring device according to claim 1 or 2, wherein the dimension measuring unit measures the distance between the centers of adjacent holes or dots, or the diameter of the holes or dots.
9. A pattern measurement program for measuring the dimensions of a pattern formed on a sample, It functions as a dimension measuring unit for measuring the dimensions of the aforementioned pattern, The function of the outlier removal unit is to perform statistical outlier processing at least twice on multiple dimensional values measured by the dimension measuring unit, A pattern measurement program that provides a computer with a function as a representative dimension value determination unit that determines a representative dimension value of the pattern from one or more of the dimension values from which outliers have been removed by the outlier removal unit.
10. A pattern measurement method for measuring the dimensions of a pattern formed on a sample, The dimensions of the aforementioned pattern are measured, Perform statistical outlier handling on multiple measured dimensional values at least twice. A pattern measurement method for determining a representative dimensional value of a pattern from one or more dimensional values from which outliers have been removed.