# US 2022/0034653 A1 · Pattern shape evaluation device, pattern shape evaluation system, and pattern shape evaluation method > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2022/0034653 A1 - Document ID: US20220034653A1 - Status: Published application - Kind: A1 - Application number: 17/277,395 - Filed: 2019-05-29 - Published: 2022-02-03 - Earliest claimed: 2018-09-25 - Assignees: Hitachi High-Tech Corporation - Applicants: Hitachi High-Tech Corporation - Inventors: Atsuko Shintani; Takahiro Kawasaki; Kazuhisa Hasumi; Masami Ikota; Hiroki Kawada - Web page: https://patentgrep.com/patent/US20220034653A1 ## CPC - G01B 15/04: for measuring contours or curvatures - G06T 7/13: Edge detection - G01B 15/08: for measuring roughness or irregularity of surfaces - G01N 23/2251: using incident electron beams, e.g. scanning electron microscopy [SEM] - G06T 7/0006: {using a design-rule based approach} - H01J 37/28: with scanning beams {(H01J37/268, H01J37/292, H01J37/2955 take precedence)} - G01N 21/956: Inspecting patterns on the surface of objects {(contactless testing of electronic circuits G01R31/308; testing currency G07D; manufacturing processes per se of semiconductor devices implementing a measuring step H10P74/20)} - G06T 2207/10061: from scanning electron microscope - G06T 2207/30148: Semiconductor; IC; Wafer - H01J 2237/2817: Pattern inspection - G01B: MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL - G01N: INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES (measuring or testing apparatus or processes other than immunoassay, involving enzymes or microorganisms C12M, C12Q) - H01J: ELECTRIC DISCHARGE TUBES OR DISCHARGE LAMPS (spark-gaps H01T; electric arc lamps H05B31/00; particle accelerators H05H) ## Abstract Line-edge roughness or line width roughness is evaluated while preventing influence of noise caused by a device or an environment. Therefore, an averaged signal profile 405 in which a moving average of S pixels (S is an integer greater than 1) is taken in a Y direction is obtained from a signal profile showing a secondary electron signal amount distribution in an X direction with respect to a predetermined Y coordinate obtained from a top-down image, an edge position 406 of a line pattern is extracted based on the averaged signal profile, and a noise floor height is calculated based on a first power spectral density 407 of LER data or LWR data based on the extracted edge position and a second power spectral density 409 of a rectangular window function corresponding to the moving average of the S pixels. ## Claims ### Claim 1 A pattern shape evaluation device configured to evaluate a shape of a line pattern formed on a sample, the pattern shape evaluation device comprising: a processor; a memory; and an edge extraction program and a pattern shape evaluation program which are read into the memory and executed by the processor, wherein the edge extraction program includes an edge position extraction unit configured to extract an edge position of the line pattern from a top-down image of the line pattern, the pattern shape evaluation program includes a noise floor calculation unit, a longitudinal direction of the line pattern in the top-down image is defined as a Y direction and a direction perpendicular to the longitudinal direction is defined as an X direction, the edge position extraction unit obtains an averaged signal profile obtained by performing a moving average of S pixels (S is an integer greater than 1) in the Y direction on a signal profile showing a secondary electron signal amount distribution in the X direction with respect to a predetermined Y coordinate obtained from the top-down image, and extracts the edge position of the line pattern based on the averaged signal profile, and the noise floor calculation unit calculates a noise floor height based on a first power spectral density of LER data or LWR data based on the edge position extracted by the edge position extraction unit and a second power spectral density of a rectangular window function corresponding to the moving average of the S pixels. ### Claim 2 (depends on 1) The pattern shape evaluation device according to claim 1, wherein the signal profile is a distribution of gray scale of pixels in the X direction with respect to the predetermined Y coordinate in the top-down image. ### Claim 3 (depends on 1) The pattern shape evaluation device according to claim 1, wherein the LER data obtains an approximate straight line that approximates an edge of the line pattern, and is a set of distances between the edge position of the line pattern at each Y coordinate and the approximate straight line, and the LWR data calculates an average value of local widths of the line pattern, and is a set of differences between a local width of the line pattern at each Y coordinate and the average value. ### Claim 4 (depends on 1) The pattern shape evaluation device according to claim 1, wherein the pattern shape evaluation program includes an index value calculation unit, and the index value calculation unit calculates an index value of a shape of the line pattern by integrating a power spectral density obtained by subtracting the noise floor height from a third power spectral density obtained by dividing the first power spectral density by the second power spectral density. ### Claim 5 (depends on 1) The pattern shape evaluation device according to claim 1, wherein the pattern shape evaluation program includes a method selection unit, and the method selection unit selects one of a first method using one S value or a second method using a plurality of S values. ### Claim 6 (depends on 5) The pattern shape evaluation device according to claim 5, wherein when the method selection unit selects the first method, the noise floor calculation unit defines a noise floor region in a spatial frequency region in which a magnitude of the second power spectral density does not become equal to or less than a predetermined value with respect to a third power spectral density obtained by dividing the first power spectral density by the second power spectral density, and sets an average value of the third power spectral density in the noise floor region as a noise floor height. ### Claim 7 (depends on 5) The pattern shape evaluation device according to claim 5, wherein when the method selection unit selects the second method, the edge position extraction unit obtains the averaged signal profile for each of the plurality of S values, and extracts the edge position of the line pattern based on each of a plurality of averaged signal profiles, the second power spectral density is a power spectral density in which power spectral densities of a plurality of rectangular window functions corresponding to a moving average of the S pixels with respect to a plurality of S values are connected so that a value in each spatial frequency becomes a maximum value of the power spectral densities of the plurality of rectangular window functions, and the first power spectral density is a power spectral density in which power spectral densities of a plurality of LER data or LWR data based on the edge position extracted by the edge position extraction unit with respect to the plurality of S values are connected in accordance with a value of S of the second power spectral density at each spatial frequency. ### Claim 8 (depends on 7) The pattern shape evaluation device according to claim 7, wherein the noise floor calculation unit defines a noise floor region with respect to a third power spectral density obtained by dividing the first power spectral density by the second power spectral density, and sets an average value of the third power spectral density in the noise floor region as a noise floor height. ### Claim 9 (depends on 7) The pattern shape evaluation device according to claim 7, wherein 2 and 3, or 3, 4, and 5 are used as the plurality of S values. ### Claim 10 (depends on 1) A pattern shape evaluation system comprising: an electron microscope configured to image a top-down image; a storage device configured to store the top-down image captured by the electron microscope; and a pattern shape evaluation device according to claim 1, the pattern shape evaluation device being connected to the storage device, wherein the pattern shape evaluation device reads the top-down image stored in the storage device to evaluate a shape of the line pattern captured in the top-down image. ### Claim 11 A pattern shape evaluation method for evaluating a shape of a line pattern formed on a sample with a pattern shape evaluation device by using a top-down image of the line pattern, the method comprising: defining a longitudinal direction of the line pattern as a Y direction and a direction perpendicular to the longitudinal direction as an X direction in the top-down image; extracting an edge position of the line pattern from the top-down image; obtaining an averaged signal profile obtained by performing a moving average of S pixels (S is an integer greater than 1) in the Y direction on a signal profile showing a secondary electron signal amount distribution in the X direction with respect to a predetermined Y coordinate obtained from the top-down image, and extracting the edge position of the line pattern based on the averaged signal profile; and calculating a noise floor height based on a first power spectral density of LER data or LWR data based on the edge position of the extracted line pattern and a second power spectral density of a rectangular window function corresponding to the moving average of the S pixels. ### Claim 12 (depends on 11) The pattern shape evaluation method according to claim 11, wherein an index value of a shape of the line pattern is calculated by integrating a power spectral density obtained by subtracting the noise floor height from a third power spectral density obtained by dividing the first power spectral density by the second power spectral density. ### Claim 13 (depends on 11) The pattern shape evaluation method according to claim 11, wherein one of a first method using one S value and a second method using a plurality of S values is selectable. ### Claim 14 (depends on 13) The pattern shape evaluation method according to claim 13, wherein when the first method is selected, a noise floor region is defined in a spatial frequency region in which a magnitude of the second power spectral density does not become equal to or less than a predetermined value with respect to a third power spectral density obtained by dividing the first power spectral density by the second power spectral density, and an average value of the third power spectral density in the noise floor region is set as a noise floor height. ### Claim 15 (depends on 13) The pattern shape evaluation method according to claim 13, wherein when the second method is selected, the averaged signal profile for each of the plurality of S values is obtained, and an edge position of the line pattern is extracted based on each of a plurality of averaged signal profiles, the second power spectral density is a power spectral density in which power spectral densities of a plurality of rectangular window functions corresponding to a moving average of the S pixels with respect to a plurality of S values are connected so that a value in each spatial frequency becomes a maximum value of the power spectral densities of the plurality of rectangular window functions, and the first power spectral density is a power spectral density in which power spectral densities of a plurality of LER data or LWR data based on the edge position of the extracted line pattern with respect to the plurality of S values are connected in accordance with a value of S of the second power spectral density at each spatial frequency. ### Claim 16 (depends on 15) The pattern shape evaluation method according to claim 15, wherein a noise floor region is defined with respect to a third power spectral density obtained by dividing the first power spectral density by the second power spectral density, and an average value of the third power spectral density in the noise floor region is set as a noise floor height.