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    DETERMINING A MARK LAYOUT ACROSS A PATTERNING DEVICE OR SUBSTRATE
    2.
    发明申请
    DETERMINING A MARK LAYOUT ACROSS A PATTERNING DEVICE OR SUBSTRATE 审中-公开

    公开(公告)号：WO2020108861A1

    公开(公告)日：2020-06-04

    申请号：PCT/EP2019/078529

    申请日：2019-10-21

    Applicant: ASML NETHERLANDS B.V.

    Inventor： SMAL, Pavel ,  SOCHAL, Inez, Marlena ,  SARMA, Gautam

    IPC: G03F7/20 ,  G03F9/00

    Abstract: A method for determining a layout of mark positions across a patterning device or substrate, the method comprising: a) obtaining (502) a model configured to model data associated with measurements performed on the patterning device or substrate at one or more mark positions; b) obtaining (504) an initial mark layout (506) comprising initial mark positions; c) reducing (508) the initial mark layout by removal of one or more mark positions to obtain a plurality of reduced mark layouts (510), each reduced mark layout obtained by removal of a different mark position from the initial mark layout; d) determining (512) a model uncertainty metric associated with usage of the model for each reduced mark layout out of said plurality of reduced mark layouts; and e) selecting (514) one or more reduced mark layouts (516) based on its associated model uncertainty metric.

    METHOD FOR DETERMINING A SAMPLING SCHEME, A SEMICONDUCTOR SUBSTRATE MEASUREMENT APPARATUS, A LITHOGRAPHIC APPARATUS
    5.
    发明公开
    METHOD FOR DETERMINING A SAMPLING SCHEME, A SEMICONDUCTOR SUBSTRATE MEASUREMENT APPARATUS, A LITHOGRAPHIC APPARATUS 审中-公开

    公开(公告)号：EP4235306A2

    公开(公告)日：2023-08-30

    申请号：EP23173939.2

    申请日：2020-05-11

    Applicant: ASML Netherlands B.V.

    Inventor： SMORENBERG, Pieter, Gerardus, Jacobus ,  SAPUTRA, Putra ,  ELBATTAY, Khalid ,  DERWIN, Paul ,  WERKMAN, Roy ,  JENSEN, Erik ,  YU, Hyun-Woo ,  SARMA, Gautam

    IPC: G03F7/20

    Abstract: The invention provides a method of obtaining a fingerprint model for modelling a spatial distribution of a performance parameter over a portion of a substrate, the method comprising: defining an initial fingerprint model related to the spatial distribution of the performance parameter over the portion as a parameterized combination of basis functions; determining parameter values for the parameterized combination of basis functions based on pre-knowledge, and determining the fingerprint model for modelling the spatial distribution of the performance parameter over the portion of the substrate, based on a measurement set representing the performance parameter over the portion of a set of one or more semiconductor substrates and the initial fingerprint model, whereby a ratio of at least two parameter values of the basis functions as determined in the initial fingerprint model is kept constant or at least part of the shape of the initial fingerprint model is maintained in the fingerprint model.

    DETERMINING A MARK LAYOUT ACROSS A PATTERNING DEVICE OR SUBSTRATE
    6.
    发明公开
    DETERMINING A MARK LAYOUT ACROSS A PATTERNING DEVICE OR SUBSTRATE 审中-公开

    公开(公告)号：EP3734363A1

    公开(公告)日：2020-11-04

    申请号：EP19171485.6

    申请日：2019-04-29

    Applicant: ASML Netherlands B.V.

    Inventor： SMAL, Pavel ,  SOCHAL, Inez Marlena ,  SARMA, Gautam

    IPC: G03F7/20 ,  G03F9/00

    Abstract: A method for determining a layout of mark positions across a patterning device or substrate, the method comprising: a) obtaining 502 a model configured to model data associated with measurements performed on the patterning device or substrate at one or more mark positions; b) obtaining 504 an initial mark layout 506 comprising initial mark positions; c) reducing 508 the initial mark layout by removal of one or more mark positions to obtain a plurality of reduced mark layouts 510, each reduced mark layout obtained by removal of a different mark position from the initial mark layout; d) determining 512 a model uncertainty metric associated with usage of the model for each reduced mark layout out of said plurality of reduced mark layouts; and e) selecting 514 one or more reduced mark layouts 516 based on its associated model uncertainty metric.

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