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    SYSTEM AND METHOD FOR GENERATING PREDICTIVE IMAGES FOR WAFER INSPECTION USING MACHINE LEARNING
    1.
    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

    申请人： ASML Netherlands B.V.

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

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

    摘要： 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.

    PROCESS WINDOW TRACKER
    4.
    发明申请
    PROCESS WINDOW TRACKER 审中-公开

    公开(公告)号：US20180224752A1

    公开(公告)日：2018-08-09

    申请号：US15579938

    申请日：2016-05-27

    申请人： ASML NETHERLANDS B.V.

    发明人： Wim Tjibbo TEL ,  Frank STAALS ,  Mark John MASLOW

    IPC分类号： G03F7/20

    CPC分类号： G03F7/70533 ,  G03F7/70525 ,  G03F7/70891 ,  H01L21/0274

    摘要： A method for adjusting a lithography process, wherein processing parameters of the lithography process include a first group of processing parameters and a second group of processing parameters, the method including: obtaining a change of the second group of processing parameters; determining a change of a sub- process window (sub-PW) as a result of the change of the second group of processing parameters, wherein the sub-PW is spanned by only the first group of processing parameters; and adjusting the first group of processing parameters based on the change of the sub-PW.

    METHOD FOR DETERMINING DEFECTIVENESS OF PATTERN BASED ON AFTER DEVELOPMENT IMAGE
    7.
    发明申请
    METHOD FOR DETERMINING DEFECTIVENESS OF PATTERN BASED ON AFTER DEVELOPMENT IMAGE 有权

    公开(公告)号：US20220342316A1

    公开(公告)日：2022-10-27

    申请号：US17640792

    申请日：2020-09-03

    申请人： ASML Netherlands B.V.

    发明人： Marleen KOOIMAN ,  Maxim PISARENCO ,  Abraham SLACHTER ,  Mark John MASLOW ,  Bernardo Andres OYARZUN RIVERA ,  Wim Tjibbo TEL ,  Ruben Cornelis MAAS

    IPC分类号： G03F7/20 ,  G06T7/00 ,  G06T7/33

    摘要： Described herein is a method of training a model configured to predict whether a feature associated with an imaged substrate will be defective after etching of the imaged substrate and determining etch conditions based on the trained model. The method includes obtaining, via a metrology tool, (i) an after development image of the imaged substrate at a given location, the after development image including a plurality of features, and (ii) an after etch image of the imaged substrate at the given location; and training, using the after development image and the after etch image, the model configured to determine defectiveness of a given feature of the plurality of features in the after development image. In an embodiment, the determining of defectiveness is based on comparing the given feature in the after development image with a corresponding etch feature in the after etch image.

    DEEP LEARNING FOR SEMANTIC SEGMENTATION OF PATTERN
    8.
    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

    申请人： ASML NETHERLANDS B.V.

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

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

    摘要： 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.