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    METHOD FOR DETERMINING CURVILINEAR PATTERNS FOR PATTERNING DEVICE
    11.
    发明申请
    METHOD FOR DETERMINING CURVILINEAR PATTERNS FOR PATTERNING DEVICE 有权

    公开(公告)号：US20210048753A1

    公开(公告)日：2021-02-18

    申请号：US16976492

    申请日：2019-02-28

    Applicant: ASML NETHERLANDS B.V.

    Inventor： Quan ZHANG ,  Been-Der CHENG ,  Rafael C. HOWELL ,  Jing SU ,  Yi ZOU ,  Yen-Wen LU

    IPC: G03F7/20 ,  G03F1/36 ,  G03F1/70

    Abstract: A method to determine a curvilinear pattern of a patterning device that includes obtaining (i) an initial image of the patterning device corresponding to a target pattern to be printed on a substrate subjected to a patterning process, and (ii) a process model configured to predict a pattern on the substrate from the initial image, generating, by a hardware computer system, an enhanced image from the initial image, generating, by the hardware computer system, a level set image using the enhanced image, and iteratively determining, by the hardware computer system, a curvilinear pattern for the patterning device based on the level set image, the process model, and a cost function, where the cost function (e.g., EPE) determines a difference between a predicted pattern and the target pattern, where the difference is iteratively reduced.

    IDENTIFICATION OF HOT SPOTS OR DEFECTS BY MACHINE LEARNING
    13.
    发明申请
    IDENTIFICATION OF HOT SPOTS OR DEFECTS BY MACHINE LEARNING 审中-公开

    公开(公告)号：US20190147127A1

    公开(公告)日：2019-05-16

    申请号：US16300380

    申请日：2017-04-20

    Applicant: ASML NETHERLANDS B.V.

    Inventor： Jing SU ,  Yi ZOU ,  Chenxi LIN ,  Stefan HUNSCHE ,  Marinus JOCHEMSEN ,  Yen-Wen LU ,  Lin Lee CHEONG

    IPC: G06F17/50 ,  G03F7/20 ,  G06N20/00 ,  G06T7/00

    Abstract: Methods of identifying a hot spot from a design layout or of predicting whether a pattern in a design layout is defective, using a machine learning model. An example method disclosed herein includes obtaining sets of one or more characteristics of performance of hot spots, respectively, under a plurality of process conditions, respectively, in a device manufacturing process; determining, for each of the process conditions, for each of the hot spots, based on the one or more characteristics under that process condition, whether that hot spot is defective; obtaining a characteristic of each of the process conditions; obtaining a characteristic of each of the hot spots; and training a machine learning model using a training set including the characteristic of one of the process conditions, the characteristic of one of the hot spots, and whether that hot spot is defective under that process condition.

    SYSTEMS AND METHODS FOR OPTIMIZING LITHOGRAPHIC DESIGN VARIABLES USING IMAGE-BASED FAILURE RATE MODEL
    14.
    发明申请
    SYSTEMS AND METHODS FOR OPTIMIZING LITHOGRAPHIC DESIGN VARIABLES USING IMAGE-BASED FAILURE RATE MODEL 有权

    公开(公告)号：US20250028255A1

    公开(公告)日：2025-01-23

    申请号：US18714728

    申请日：2022-11-23

    Applicant: ASML NETHERLANDS B.V.

    Inventor： Chenxi LIN ,  Steven George HANSEN ,  Xin LEI ,  Yi ZOU

    IPC: G03F7/00

    Abstract: A method for determining values of design variables of a lithographic process based on a predicted failure rate for printing a target pattern on a substrate using a lithographic apparatus. The method includes obtaining an image corresponding to a target pattern to be printed on a substrate using a lithographic apparatus, wherein the image is generated based on a set of values of design variables of the lithographic apparatus or a lithographic process; determining image properties, the image properties representative of a pattern printed on the substrate, the pattern corresponding to the target pattern; predicting a failure rate in printing the pattern on the substrate based on the image properties; and determining a specified value of a specified design variable based on the failure rate, the specified value to be used in the lithographic process to print the target pattern on the substrate.

    METHODS FOR GENERATING CHARACTERISTIC PATTERN AND TRAINING MACHINE LEARNING MODEL
    16.
    发明申请
    METHODS FOR GENERATING CHARACTERISTIC PATTERN AND TRAINING MACHINE LEARNING MODEL 有权

    公开(公告)号：US20220335333A1

    公开(公告)日：2022-10-20

    申请号：US17641159

    申请日：2020-08-21

    Applicant: ASML NETHERLANDS B.V.

    Inventor： Yu CAO ,  Greggory SCRANTON ,  Jing SU ,  Yi ZOU

    IPC: G06N20/00 ,  G03F1/36 ,  G03F7/20 ,  G06N3/04

    Abstract: Methods of generating a characteristic pattern for a patterning process and training a machine learning model. A method of training a machine learning model configured to generate a characteristic pattern for a mask pattern includes obtaining (i) a reference characteristic pattern that meets a satisfactory threshold related to manufacturing of the mask pattern, and (ii) a continuous transmission mask (CTM) for use in generating the mask pattern; and training, based on the reference characteristic pattern and the CTM, the machine learning model such that a first metric between the characteristic pattern and the CTM, and a second metric between the characteristic pattern and the reference characteristic pattern is reduced.

    COLORING AWARE OPTIMIZATION
    18.
    发明申请
    COLORING AWARE OPTIMIZATION 审中-公开

    公开(公告)号：US20180259857A1

    公开(公告)日：2018-09-13

    申请号：US15573832

    申请日：2016-04-29

    Applicant: ASML Netherlands B.V.

    Inventor： Yi ZOU

    IPC: G03F7/20 ,  G06T7/90 ,  G06T11/00

    Abstract: A method includes obtaining a sub-layout having an area that is a performance limiting spot, adjusting colors of patterns in the area, and determining whether the area is still a performance limiting spot. Another method includes decomposing patterns in a design layout into multiple sub-layouts; determining for at least one area in one of the sub-layouts, the likelihood of that a figure of merit is beyond its allowed range; and if the likelihood is above a threshold, that one sub-layout has a performance limiting spot. Another method includes: obtaining a design layout having a first group of patterns and a second group of patterns, wherein colors of the first group of patterns are not allowed to change and colors of the second group of patterns are allowed to change; and co-optimizing at least the first group of patterns, the second group of patterns and an illumination of a lithographic apparatus.

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