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    OBTAINING A PARAMETER CHARACTERIZING A FABRICATION PROCESS
    1.
    发明申请
    OBTAINING A PARAMETER CHARACTERIZING A FABRICATION PROCESS 有权

    公开(公告)号：US20250021020A1

    公开(公告)日：2025-01-16

    申请号：US18712057

    申请日：2022-11-03

    Applicant: ASML Netherlands B.V.

    Inventor： Patrick Philipp HELFENSTEIN ,  Sandy Claudia SCHOLZ ,  Loes Frederique VAN RIJSWIJK ,  Scott Anderson MIDDLEBROOKS

    IPC: G03F7/00

    Abstract: A measurement process is performed for each of a plurality of locations on a product of a fabrication process at which a parameter of interest characterizing the fabrication process is believed to be nominally the same, to derive measured signals for each location including at least one image. A dimensional reduction method is applied to a dataset of the measured signals, to obtain components of the dataset, including components indicative of variation between the images. For at least one of these components, one or more associated ones of the measured signals are identified, comprising at least one set of corresponding pixels in the respective images for the plurality of locations. The contribution of the identified measured signals in the dataset is reduced or eliminated to obtain a processed signal, and the parameter of interest is obtained from the processed signal.

    SYSTEM AND METHOD FOR GENERATING PREDICTIVE IMAGES FOR WAFER INSPECTION USING MACHINE LEARNING
    3.
    发明申请
    SYSTEM AND METHOD FOR GENERATING PREDICTIVE IMAGES FOR WAFER INSPECTION USING MACHINE LEARNING 有权

    公开(公告)号：US20220375063A1

    公开(公告)日：2022-11-24

    申请号：US17761578

    申请日：2020-09-14

    Applicant: ASML Netherlands B.V.

    Inventor： Maxim PISARENCO ,  Scott Anderson MIDDLEBROOKS ,  Mark John MASLOW ,  Marie-Claire VAN LARE ,  Chrysostomos BATISTAKIS

    IPC: G06T7/00 ,  G06V10/77 ,  G06V10/82 ,  G03F7/20

    Abstract: A system and method for generating predictive images for wafer inspection using machine learning are provided. Some embodiments of the system and method include acquiring the wafer after a photoresist applied to the wafer has been developed; imaging a portion of a segment of the developed wafer; acquiring the wafer after the wafer has been etched; imaging the segment of the etched wafer; training a machine learning model using the imaged portion of the developed wafer and the imaged segment of the etched wafer; and applying the trained machine learning model using the imaged segment of the etched wafer to generate predictive images of a developed wafer. Some embodiments include imaging a segment of the developed wafer; imaging a portion of the segment of the etched wafer; training a machine learning model; and applying the trained machine learning model to generate predictive after-etch images of the developed wafer.

    METHOD OF MEASURING VARIATION, INSPECTION SYSTEM, COMPUTER PROGRAM, AND COMPUTER SYSTEM
    4.
    发明申请
    METHOD OF MEASURING VARIATION, INSPECTION SYSTEM, COMPUTER PROGRAM, AND COMPUTER SYSTEM 审中-公开

    公开(公告)号：US20190391500A1

    公开(公告)日：2019-12-26

    申请号：US16486169

    申请日：2018-02-07

    Applicant: ASML NETHERLANDS B.V.

    Inventor： Antoine Gaston Marie KIERS ,  Scott Anderson MIDDLEBROOKS ,  Jan-Willem GEMMINK

    IPC: G03F7/20 ,  G01N21/956 ,  G01N21/95 ,  G03F7/00

    Abstract: Methods of measuring variation across multiple instances of a pattern on a substrate or substrates after a step in a device manufacturing process are disclosed. In one arrangement, data representing a set of images is received. Each image represents a different instance of the pattern, wherein the pattern includes a plurality of pattern elements. The set of images are registered relative to each other to superimpose the instances of the pattern. The registration includes applying different weightings to two or more of the plurality of pattern elements, wherein the weightings control the extent to which each pattern element contributes to the registration of the set of images and each weighting is based on an expected variation of the pattern element to which the weighting is applied. Variation in the pattern is measured using the registered set of images.

    METHOD AND APPARATUS FOR IMAGE ANALYSIS
    5.
    发明申请
    METHOD AND APPARATUS FOR IMAGE ANALYSIS 审中-公开

    公开(公告)号：US20190391498A1

    公开(公告)日：2019-12-26

    申请号：US16561096

    申请日：2019-09-05

    Applicant: ASML Netherlands B.V.

    Inventor： Scott Anderson MIDDLEBROOKS ,  Markus Gerardus Martinus Maria VAN KRAAIJ ,  Adrianus Cornelis Matheus KOOPMAN ,  Stefan HUNSCHE ,  Willem Marie Julia Marcel COENE

    IPC: G03F7/20 ,  G06T7/60 ,  G06T7/12

    Abstract: A method and apparatus of detection, registration and quantification of an image. The method may include obtaining an image of a lithographically created structure, and applying a level set method to an object, representing the structure, of the image to create a mathematical representation of the structure. The method may include obtaining a first dataset representative of a reference image object of a structure at a nominal condition of a parameter, and obtaining second dataset representative of a template image object of the structure at a non-nominal condition of the parameter. The method may further include obtaining a deformation field representative of changes between the first dataset and the second dataset. The deformation field may be generated by transforming the second dataset to project the template image object onto the reference image object. A dependence relationship between the deformation field and change in the parameter may be obtained.

    Inspection Method and Apparatus, and Corresponding Lithographic Apparatus
    6.
    发明申请
    Inspection Method and Apparatus, and Corresponding Lithographic Apparatus 审中-公开
    检验方法和装置，以及相应的平版印刷设备

    公开(公告)号：US20130135600A1

    公开(公告)日：2013-05-30

    申请号：US13667174

    申请日：2012-11-02

    Applicant: ASML Netherlands B.V.

    Inventor： Scott Anderson MIDDLEBROOKS ,  Rene Andreas Maria Pluijms ,  Martyn John Coogans ,  Marc Johannes Noot

    IPC: G03B27/54

    CPC classification number: G03F7/70625 ,  G03F7/70525 ,  G03F7/70641

    Abstract: An inspection method, and corresponding apparatus, enables classification of pupil images according to a process variable. The method comprises acquiring diffraction pupil images of a plurality of structures formed on a substrate during a lithographic process. A process variable of the lithographic process varies between formation of the structures, the variation of the process variable resulting in a variation in the diffraction pupil images. The method further comprises determining at least one discriminant function for the diffraction pupil images, the discriminant function being able to classify the pupil images in terms of the process variable.

    Abstract translation: 检查方法和相应的装置能够根据过程变量分类瞳孔图像。 该方法包括在光刻工艺期间获取在基板上形成的多个结构的衍射光瞳图像。 光刻过程的过程变量在结构的形成之间变化，过程变量的变化导致衍射光瞳图像的变化。 该方法还包括确定用于衍射光瞳图像的至少一个判别函数，判别函数能够根据过程变量对瞳孔图像进行分类。

    REMOVING AN ARTIFACT FROM AN IMAGE
    7.
    发明申请
    REMOVING AN ARTIFACT FROM AN IMAGE 有权

    公开(公告)号：US20230021320A1

    公开(公告)日：2023-01-26

    申请号：US17957997

    申请日：2022-09-30

    Applicant: ASML Netherlands B.V.

    Inventor： Maxim PISARENCO ,  Scott Anderson MIDDLEBROOKS ,  Thomas Jarik HUISMAN

    IPC: G06T5/50 ,  G03F7/20 ,  G06T5/00 ,  G06T7/00 ,  H01J37/22

    Abstract: An inspection tool comprises an imaging system configured to image a portion of a semiconductor substrate. The inspection tool may further comprise an image analysis system configured to obtain an image of a structure on the semiconductor substrate from the imaging system, encode the image of the structure into a latent space thereby forming a first encoding. the image analysis system may subtract an artifact vector, representative of an artifact in the image, from the encoding thereby forming a second encoding; and decode the second encoding to obtain a decoded image.

    DEEP LEARNING FOR SEMANTIC SEGMENTATION OF PATTERN
    9.
    发明申请
    DEEP LEARNING FOR SEMANTIC SEGMENTATION OF PATTERN 有权

    公开(公告)号：US20210374936A1

    公开(公告)日：2021-12-02

    申请号：US16968966

    申请日：2019-02-15

    Applicant: ASML NETHERLANDS B.V.

    Inventor： Adrianus Cornelis Matheus KOOPMAN ,  Scott Anderson MIDDLEBROOKS ,  Antoine Gaston Marie KIERS ,  Mark John MASLOW

    IPC: G06T7/00 ,  G06K9/62 ,  G06T7/11 ,  G03F7/20 ,  G06N3/08

    Abstract: A method for training a deep learning model of a patterning process. The method includes obtaining (i) training data including an input image of at least a part of a substrate having a plurality of features and including a truth image, (ii) a set of classes, each class corresponding to a feature of the plurality of features of the substrate within the input image, and (iii) a deep learning model configured to receive the training data and the set of classes, generating a predicted image, by modeling and/or simulation with the deep learning model using the input image, assigning a class of the set of classes to a feature within the predicted image based on matching of the feature with a corresponding feature within the truth image, and generating, by modeling and/or simulation, a trained deep learning model by iteratively assigning weights using a loss function.

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