公开(公告)号：US20230343547A1

公开(公告)日：2023-10-26

申请号：US18013605

申请日：2020-07-16

Applicant: Hitachi High-Tech Corporation

Inventor： Miki AOYAGI ,  Masumi SHIRAI ,  Kei SAKAI

IPC: H01J37/22

CPC classification number: H01J37/222

Abstract: The purpose of the present disclosure is to provide a technology for calculating a machine difference correction coefficient more efficiently with high accuracy. A defect inspection device according to the present disclosure calculates a machine difference correction coefficient for correcting a difference in the feature amount of a reference sample between devices, and when a machine difference variation coefficient indicating the change over time in the feature amount of a calibration member is outside a threshold range, recalculates the machine difference correction coefficient by using the feature amount of the calibration member.

公开(公告)号：US20220130638A1

公开(公告)日：2022-04-28

申请号：US17501249

申请日：2021-10-14

Applicant: Hitachi High-Tech Corporation

Inventor： Keiichiro HITOMI ,  Kenji TANIMOTO ,  Yusuke ABE ,  Takuma YAMAMOTO ,  Kei SAKAI ,  Satoru YAMAGUCHI ,  Yasunori GOTO ,  Shuuichirou TAKAHASHI

IPC: H01J37/22 ,  H01J37/147 ,  H01J37/21

Abstract: Provided is a charged particle beam device capable of focusing with high accuracy even when a charged particle beam has a large off-axis amount. The charged particle beam device generates an observation image of a sample by irradiating the sample with a charged particle beam, and includes: a deflection unit that inclines the charged particle beam; a focusing lens that focuses the charged particle beam; an adjustment unit that adjusts a lens strength of the focusing lens based on an evaluation value calculated from the observation image; a storage unit that stores a relationship between a visual field movement amount and the lens strength; and a filter setting unit that calculates the visual field movement amount based on an inclination angle of the charged particle beam and the relationship, and sets an image filter to be superimposed on the observation image based on the calculated visual field movement amount.

公开(公告)号：US20250014858A1

公开(公告)日：2025-01-09

申请号：US18710251

申请日：2021-11-29

Applicant: HITACHI HIGH-TECH CORPORATION

Inventor： Tomoaki YAMAZAKI ,  Kei SAKAI

IPC: H01J37/21 ,  H01J37/153 ,  H01J37/22 ,  H01J37/26 ,  H01J37/28

Abstract: Provided is a correction method capable of reducing defocus in an image caused by variations in height of a semiconductor pattern by image processing performed after imaging. This correction method for correcting an image includes: acquiring a target image 801 in which a semiconductor pattern having a plurality of areas the height of which varies step-wisely is imaged; storing a plurality of correction coefficients C1 and the like for correcting the respective areas of the acquired target image 801; and correcting the respective areas of the target image 801 using the stored plurality of correction coefficients C1 and the like.

公开(公告)号：US20230314128A1

公开(公告)日：2023-10-05

申请号：US18127858

申请日：2023-03-29

Applicant: Hitachi High-Tech Corporation

Inventor： Masaya GOTO ,  Kei SAKAI ,  Satoru YAMAGUCHI ,  Junichi KAKUTA

IPC: H01J37/28 ,  G01B21/30

CPC classification number: G01B21/30 ,  H01J37/28 ,  H01J2237/0437 ,  H01J2237/24592 ,  H01J2237/2817

Abstract: A processing system and a charged particle beam apparatus for the purpose of determining the degree of growth or the presence or absence of a defect in an epitaxial layer grown in a groove or a hole such as between inner spacers from an image of the groove or the hole are proposed. In a processing system including a computer system, the computer system calculates a distance and a brightness value related to a layer between a plurality of structures from a signal profile in accordance with one direction on a two-dimensional plane related to the layer, which is obtained by irradiating the layer with an electron beam, and determines or outputs a state of the layer based on the distance and the brightness value.

公开(公告)号：US20220165537A1

公开(公告)日：2022-05-26

申请号：US17449286

申请日：2021-09-29

Applicant: Hitachi High-Tech Corporation

Inventor： Motonobu HOMMI ,  Satoru YAMAGUCHI ,  Kei SAKAI ,  Hiroshi NISHIHAMA

IPC: H01J37/28 ,  H01J37/22 ,  H01J37/244

Abstract: To shorten a time required for evaluation of a recipe while suppressing an increase in a data amount. A charged particle beam device includes a microscope that scans a charged particle beam on a sample, detects secondary particles emitted from the sample, and outputs a detection signal and a computer system that generates a frame image based on the detection signal and processes an image based on the frame images. The computer system calculates a moment image between a plurality of the frame images, and calculates a feature amount data of the frame image based on a moment.

公开(公告)号：US20230095456A1

公开(公告)日：2023-03-30

申请号：US17909876

申请日：2020-03-30

Applicant: Hitachi High-Tech Corporation

Inventor： Daisuke BIZEN ,  Kei SAKAI ,  Junichi KAKUTA ,  Masumi SHIRAI ,  Minoru YAMAZAKI

IPC: H01J37/22 ,  H01J37/28 ,  H01J37/244 ,  G06T7/13

Abstract: Roughness measurement corrects a machine difference utilizing first PSD data indicating power spectral density of a line pattern measured for a line pattern formed on a wafer for machine difference management by a reference machine in roughness index calculation and second PSD data indicating power spectral density of a line pattern measured for the line pattern formed on the wafer for machine difference management by a correction target machine are used to obtain a correction method for correcting the power spectral density of the second PSD data to the power spectral density of the first PSD data, power spectral density of a line pattern is measured as third PSD data from a scanning image of the line pattern, and corrected power spectral density obtained by correcting the power spectral density of the third PSD data by the obtained correction method is calculated.

公开(公告)号：US20220319804A1

公开(公告)日：2022-10-06

申请号：US17597266

申请日：2019-08-23

Applicant: Hitachi High-Tech Corporation

Inventor： Masaki SUGIE ,  Kei SAKAI

IPC: H01J37/22 ,  H01J37/244 ,  H01J37/28

Abstract: The present invention enables an overlay error between processors to be measured from a pattern image, the SN ratio of which is low. To this end, the present invention forms a secondary electron image 200 from a detection signal of a secondary electron detector 107, forms a reflected electron image 210 from a detection signal of a reflected electron detector 109, creates a SUMLINE profile 701 that is obtained by adding luminance information in the reflected electron image along the longitudinal direction of a line pattern, and calculates an overlay error of a sample by using position information about an upper layer pattern detected from the secondary electron image and position information about a lower layer pattern that is detected by using an estimation line pattern 801 estimated on the basis of the SUMLINE profile from the reflected electron image.

公开(公告)号：US20220277434A1

公开(公告)日：2022-09-01

申请号：US17634805

申请日：2019-08-30

Applicant: HITACHI HIGH-TECH CORPORATION

Inventor： Ryou YUMIBA ,  Kei SAKAI ,  Satoru YAMAGUCHI

IPC: G06T7/00 ,  G06V10/774 ,  G06T7/11 ,  G06V10/82 ,  G06T7/66 ,  G06V10/764 ,  G06V10/72 ,  G01N21/95

Abstract: The present invention proposes a technique for enabling the execution of measurement processing without referring to a design drawing for which it is difficult to adjust or obtain parameters for image processing that requires knowhow. This measurement system according to the present disclosure refers to a learning model generated on the basis of teaching data, which is generated from a sample image of a semiconductor, and the sample image, generates a region-segmented image from an input image (measurement subject) of a semiconductor having a predetermined structure, and uses the region-segmented image to perform image measurement. Here, the teaching data is an image in which labels, which include a structure of the semiconductor in the sample image, are assigned to each pixel of the image, and the learning model includes parameters for deducing teaching data from the sample image (see indicator 1).