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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

    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.

    METHODS OF METROLOGY
    6.
    发明申请
    METHODS OF METROLOGY 有权

    公开(公告)号：US20250147436A1

    公开(公告)日：2025-05-08

    申请号：US18832408

    申请日：2023-01-23

    Applicant: ASML NETHERLANDS B.V.

    Inventor： Chrysostomos BATISTAKIS ,  Huaichen ZHANG ,  Maxim PISARENCO ,  Vahid BASTANI ,  Konstantin Sergeevich NECHAEV ,  Roy ANUNCIADO ,  Stefan Cornelis Theodorus VAN DER SANDEN

    IPC: G03F7/00

    Abstract: A method for determining a parameter of interest relating to at least one structure formed on a substrate in a manufacturing process. The method includes: obtaining layout data relating to a layout of a pattern to be applied to the at least one structure, the pattern including the at least one structure; and obtaining a trained model, having been trained on metrology data and the layout data to infer a value and/or probability metric relating to a parameter of interest from at least the layout data, the metrology data relating to a plurality of measurements of the parameter of interest at a respective plurality of measurement locations on the substrate. A value and/or probability metric is determined relating to the parameter of interest at one or more locations on the substrate different from the measurement locations from at least layout data using the trained model.

    TRAINING A MODEL TO GENERATE PREDICTIVE DATA
    7.
    发明申请
    TRAINING A MODEL TO GENERATE PREDICTIVE DATA 有权

    公开(公告)号：US20250103964A1

    公开(公告)日：2025-03-27

    申请号：US18971818

    申请日：2024-12-06

    Applicant: ASML Netherlands B.V.

    Inventor： Maxim PISARENCO ,  Chrysostomos BATISTAKIS

    IPC: G06N20/00

    Abstract: A method of training a generator model comprising: using the generator model to generate the predictive data based on the first measured data, wherein the first measured data and the predictive data can be used to form images of the sample; pairing subsets of the first measured data with subsets of the predictive data, the subsets corresponding to locations within the images of the sample that can be formed from the first measured data and the predictive data; using a discriminator to evaluate a likelihood that the predictive data comes from a same data distribution as second measured data measured from a sample after an etching process; and training the generator model based on: correlation for the pairs corresponding to a same location relative to correlation for pairs corresponding to different locations, the correlation being the correlation between the paired subsets of data, and the likelihood evaluated by the discriminator.

    METHOD FOR PREDICTING STOCHASTIC CONTRIBUTORS
    10.
    发明申请
    METHOD FOR PREDICTING STOCHASTIC CONTRIBUTORS 有权

    公开(公告)号：US20230081821A1

    公开(公告)日：2023-03-16

    申请号：US17986829

    申请日：2022-11-14

    Applicant: ASML Netherlands B.V.

    Inventor： Chrysostomos BATISTAKIS ,  Maxim PISARENCO ,  Bernardo Andres OYARZUN RIVERA ,  Abraham SLACHTER

    IPC: G06T7/73 ,  G06V10/46 ,  G06T7/00 ,  H01L21/66

    Abstract: Described herein is a method for training a machine learning model to determine a source of error contribution to multiple features of a pattern printed on a substrate. The method includes obtaining training data having multiple datasets, wherein each dataset has error contribution values representative of an error contribution from one of multiple sources to the features, and wherein each dataset is associated with an actual classification that identifies a source of the error contribution of the corresponding dataset; and training, based on the training data, a machine learning model to predict a classification of a reference dataset of the datasets such that a cost function that determines a difference between the predicted classification and the actual classification of the reference dataset is reduced.

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