公开(公告)号：US20240331115A1

公开(公告)日：2024-10-03

申请号：US18577678

申请日：2022-06-02

Applicant: ASML Netherlands B.V.

Inventor： Haoyi LIANG ,  Zhichao CHEN ,  Lingling PU ,  Fang-Cheng CHANG ,  Liangjiang YU ,  Zhe WANG

IPC: G06T5/80 ,  G06T7/00 ,  G06T7/33

CPC classification number: G06T5/80 ,  G06T7/001 ,  G06T7/337 ,  G06T2207/10061 ,  G06T2207/20081 ,  G06T2207/30148

Abstract: An improved systems and methods for correcting distortion of an inspection image are disclosed. An improved method for correcting distortion of an inspection image comprises acquiring an inspection image, aligning a plurality of patches of the inspection image based on a reference image corresponding to the inspection image, evaluating, by a machine learning model, alignments between each patch of the plurality of patches and a corresponding patch of the reference image, determining local alignment results for the plurality of patches of the inspection image based on a reference image corresponding to the inspection image, determining an alignment model based on the local alignment results, and correcting a distortion of the inspection image based on the alignment model.

公开(公告)号：US20220245840A1

公开(公告)日：2022-08-04

申请号：US17659467

申请日：2022-04-15

Applicant: ASML Netherlands B.V.

Inventor： Wei FANG ,  Lingling PU

IPC: G06T7/33 ,  G06T7/73 ,  G06T7/13 ,  G06T7/00 ,  H01L21/67 ,  H01L21/66

Abstract: A method for aligning a wafer image with a reference image, comprising: searching for a targeted reference position on the wafer image for aligning the wafer image with the reference image; and in response to a determination that the targeted reference position does not exist: defining a current lock position and an area that encloses the current lock position on the wafer image; computing an alignment score of the current lock position; comparing the alignment score of the current lock position with stored alignment scores of positions previously selected in relation to aligning the wafer image with the reference image; and aligning the wafer image with the reference image based on the comparison.

公开(公告)号：US20220237759A1

公开(公告)日：2022-07-28

申请号：US17567847

申请日：2022-01-03

Applicant: ASML Netherlands B.V.

Inventor： Lingling PU ,  Wei FANG ,  Nan ZHAO ,  Wentian ZHOU ,  Teng WANG ,  Ming XU

IPC: G06T7/00 ,  G06T7/60

Abstract: Systems and methods for optimal electron beam metrology guidance are disclosed. According to certain embodiments, the method may include receiving an acquired image of a sample, determining a set of image parameters based on an analysis of the acquired image, determining a set of model parameters based on the set of image parameters, generating a set of simulated images based on the set of model parameters. The method may further comprise performing measurement of critical dimensions on the set of simulated images and comparing critical dimension measurements with the set of model parameters to provide a set of guidance parameters based on comparison of information from the set of simulated images and the set of model parameters. The method may further comprise receiving auxiliary information associated with target parameters including critical dimension uniformity.

公开(公告)号：US20240062362A1

公开(公告)日：2024-02-22

申请号：US18268953

申请日：2021-12-08

Applicant: ASML Netherlands B.V.

Inventor： Zhe WANG ,  Liangjiang YU ,  Lingling PU

IPC: G06T7/00 ,  G06T11/00

CPC classification number: G06T7/001 ,  G06T11/00 ,  G06T2207/20084 ,  G06T2207/20081 ,  G06T2207/30148 ,  G06T2207/10061

Abstract: An improved systems and methods for generating a synthetic defect image are disclosed. An improved method for generating a synthetic defect image comprises acquiring a machine learning-based generator model; providing a defect-free inspection image and a defect attribute combination as inputs to the generator model; and generating by the generator model, based on the defect-free inspection image, a predicted synthetic defect image with a predicted defect that accords with the defect attribute combination.

公开(公告)号：US20240046620A1

公开(公告)日：2024-02-08

申请号：US18365134

申请日：2023-08-03

Applicant: ASML Netherlands B.V.

Inventor： Wentian ZHOU ,  Liangjiang YU ,  Teng WANG ,  Lingling PU ,  Wei FANG

IPC: G06V10/774 ,  G06T7/00 ,  G06F18/214 ,  G06V10/776 ,  G06V10/98

CPC classification number: G06V10/774 ,  G06T7/0006 ,  G06F18/214 ,  G06V10/776 ,  G06V10/993 ,  G06T2207/10061 ,  G06T2207/20081 ,  G06T2207/30148

Abstract: Disclosed herein is a method of automatically obtaining training images to train a machine learning model that improves image quality. The method may comprise analyzing a plurality of patterns of data relating to a layout of a product to identify a plurality of training locations on a sample of the product to use in relation to training the machine learning model. The method may comprise obtaining a first image having a first quality for each of the plurality of training locations, and obtaining a second image having a second quality for each of the plurality of training locations, the second quality being higher than the first quality. The method may comprise using the first image and the second image to train the machine learning model.

公开(公告)号：US20220301811A1

公开(公告)日：2022-09-22

申请号：US17633176

申请日：2020-08-20

Applicant: ASML Netherlands B.V.

Inventor： Wei FANG ,  Lingling PU ,  Bo WANG ,  Zhonghua DONG ,  Yongxin WANG

IPC: H01J37/22 ,  H01J37/244 ,  H01J37/28 ,  G01N23/2251 ,  G06T5/00 ,  G06T5/50

Abstract: An improved apparatus and method for enhancing an image, and more particularly an apparatus and method for enhancing an image through cross-talk cancellation in a multiple charged-particle beam inspection are disclosed. An improved method for enhancing an image includes acquiring a first image signal of a plurality of image signals from a detector of a multi-beam inspection system. The first image signal corresponds to a detected signal from a first region of the detector on which electrons of a first secondary electron beam and of a second secondary electron beam are incident. The method includes reducing, from the first image signal, cross-talk contamination originating from the second secondary electron beam using a relationship between the first image signal and beam intensities associated with the first secondary electron beam and the second secondary electron beam. The method further includes generating a first image corresponding to first secondary electron beam after reduction.

公开(公告)号：US20210350507A1

公开(公告)日：2021-11-11

申请号：US17308835

申请日：2021-05-05

Applicant: ASML Netherlands B.V.

Inventor： Wei FANG ,  Ruochong FEI ,  Lingling PU ,  Wentian ZHOU ,  Liangjiang YU ,  Bo WANG

IPC: G06T5/00 ,  G06T5/50 ,  G06T7/10

Abstract: An improved method and apparatus for enhancing an inspection image in a charged-particle beam inspection system. An improved method for enhancing an inspection image comprises acquiring a first image and a second image of multiple stacked layers of a sample that are taken with a first focal point and a second focal point, respectively, associating a first segment of the first image with a first layer among the multiple stacked layers and associating a second segment of the second image with a second layer among the multiple stacked layers, updating the first segment based on a first reference image corresponding to the first layer and updating the second segment based on a second reference image corresponding to the second layer, and combining the updated first segment and the updated second segment to generate a combined image including the first layer and the second layer.

公开(公告)号：US20250104210A1

公开(公告)日：2025-03-27

申请号：US18716123

申请日：2022-11-18

Applicant: ASML Netherlands B.V.

Inventor： Lingling PU ,  Hongquan ZUO

IPC: G06T7/00 ,  G06N3/0455

Abstract: Systems and methods for training a machine learning model for defect detection include obtaining training data including an inspection image of a fabricated integrated circuit (IC) and design layout data of the IC, and training a machine learning model using the training data. The machine learning model includes a first autoencoder and a second autoencoder. The first autoencoder includes a first encoder and a first decoder. The second autoencoder includes a second encoder and a second decoder. The second decoder is configured to obtain a first code outputted by the first encoder. The first decoder is configured to obtain a second code outputted by the second encoder.

公开(公告)号：US20250005739A1

公开(公告)日：2025-01-02

申请号：US18710127

申请日：2022-10-18

Applicant: ASML Netherlands B.V.

Inventor： Shengcheng JIN ,  Lingling PU ,  Liangjiang YU

IPC: G06T7/00 ,  G06T3/14 ,  G06T5/60 ,  H01J37/22 ,  H01J37/28

Abstract: Apparatuses, systems, and methods for providing beams for defect detection and defect location identification associated with a sample of charged particle beam systems. In some embodiments, a method may include obtaining an image of a sample; determining defect characteristics from the image; generating an updated image based on the determined defect characteristics and the image; and aligning the updated image with a reference image.

公开(公告)号：US20240331132A1

公开(公告)日：2024-10-03

申请号：US18577684

申请日：2022-06-03

Applicant: ASML Netherlands B.V.

Inventor： Haoyi LIANG ,  Yani CHEN ,  Ming-Yang YANG ,  Yang YANG ,  Xiaoxia HUANG ,  Zhichao CHEN ,  Liangjiang YU ,  Zhe WANG ,  Lingling PU

IPC: G06T7/00 ,  G01N23/2251 ,  G06T7/73

CPC classification number: G06T7/001 ,  G01N23/2251 ,  G06T7/0006 ,  G06T7/74 ,  G01N2223/6116 ,  G06T2200/24 ,  G06T2207/10061 ,  G06T2207/20081 ,  G06T2207/30148

Abstract: Systems and methods for detecting a defect on a sample include receiving a first image and a second image associated with the first image; determining, using a clustering technique, N first feature descriptor(s) for L first pixel(s) in the first image and M second feature descriptor(s) for L second pixel(s) in the second image, wherein each of the L first pixel(s) is co-located with one of the L second pixel(s), and L, M, and N are positive integers; determining K mapping probability between a first feature descriptor of the N first feature descriptor(s) and each of K second feature descriptor(s) of the M second feature descriptor(s), wherein K is a positive integer; and providing an output for determining whether there is existence of an abnormal pixel representing a candidate defect on the sample based on a determination that one of the K mapping probability does not exceed a threshold value.