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1.
公开(公告)号:US20230267711A1
公开(公告)日:2023-08-24
申请号:US18015313
申请日:2021-07-29
Applicant: ASML NETHERLANDS B.V.
Inventor: Scott Anderson MIDDLEBROOKS , Maxim PISARENCO , Markus Gerardus Martinus Maria VAN KRAAIJ , Coen Adrianus VERSCHUREN
IPC: G06V10/774 , G06N3/0464 , G06V10/50
CPC classification number: G06V10/774 , G06N3/0464 , G06V10/50
Abstract: A method and apparatus for selecting patterns from an image such as a design layout. The method includes obtaining an image (e.g., of a target layout) having a plurality of patterns; determining, based on pixel intensities within the image, a metric (e.g., entropy) indicative of an amount of information contained in one or more portions of the image; and selecting, based on the metric, a sub-set of the plurality of patterns from the one or more portions of the image having values of the metric within a specified range. The sub-set of patterns can be provided as training data for training a model associated with a patterning process.
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2.
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
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.
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公开(公告)号:US20240369944A1
公开(公告)日:2024-11-07
申请号:US18287166
申请日:2022-04-12
Applicant: ASML NETHERLANDS B.V.
Inventor: Chrysostomos BATISTAKIS , Maxim PISARENCO , Markus Gerardus Martinus Maria VAN KRAAIJ , Vito Daniele RUTIGLIANI , Scott Anderson MIDDLEBROOKS , Coen Adrianus VERSCHUREN , Niels GEYPEN
Abstract: A method of determining a stochastic metric, the method including: obtaining a trained model having been trained to correlate training optical metrology data to training stochastic metric data, wherein the training optical metrology data includes a plurality of measurement signals relating to distributions of an intensity related parameter across a zero or higher order of diffraction of radiation scattered from a plurality of training structures, and the training stochastic metric data includes stochastic metric values relating to the plurality of training structures, wherein the plurality of training structures have been formed with a variation in one or more dimensions on which the stochastic metric is dependent; obtaining optical metrology data including a distribution of the intensity related parameter across a zero or higher order of diffraction of radiation scattered from a structure; and using the trained model to infer a value of the stochastic metric from the optical metrology data.
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公开(公告)号:US20240020961A1
公开(公告)日:2024-01-18
申请号:US18039483
申请日:2021-12-08
Applicant: ASML NETHERLANDS B.V.
CPC classification number: G06V10/82 , G06V10/993
Abstract: A method for training a machine learning model includes obtaining a set of unpaired after-development (AD) images and after-etch (AE) images associated with a substrate. Each AD image in the set is obtained at a location on the substrate that is different from the location at which any of the AE images is obtained. The method further includes training the machine learning model to generate a predicted AE image based on the AD images and the AE images, wherein the predicted AE image corresponds to a location from which an input AD image of the AD images is obtained.
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公开(公告)号:US20230036630A1
公开(公告)日:2023-02-02
申请号:US17963063
申请日:2022-10-10
Applicant: ASML Netherlands B.V.
IPC: G06T7/00
Abstract: A method for determining an optimized weighting of an encoder and decoder network; the method comprising: for each of a plurality of test weightings, performing the following steps with the encoder and decoder operating using the test weighting: (a) encoding, using the encoder, a reference image and a distorted image into a latent space to form an encoding; (b) decoding the encoding, using the decoder, to form a distortion map indicative of a difference between the reference image and a distorted image; (c) spatially transforming the distorted image by the distortion map to obtain an aligned image; (d) comparing the aligned image to the reference image to obtain a similarity metric; and (e) determining a loss function which is at least partially defined by the similarity metric; wherein the optimized weighting is determined to be the test weighting which has an optimized loss function.
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公开(公告)号:US20220335290A1
公开(公告)日:2022-10-20
申请号:US17639609
申请日:2020-08-12
Applicant: ASML NETHERLANDS B.V.
Abstract: A method for increasing certainty in parameterized model predictions. The method includes clustering dimensional data in a latent space associated with a parameterized model into clusters. Different clusters correspond to different portions of a given input. The method includes predicting, with the parameterized model, an output based on the dimensional data in the latent space. The method includes transforming, with the parameterized model, the dimensional data in the latent space into a recovered version of the given input that corresponds to one or more of the clusters. In some embodiments, the method includes determining which one or more clusters correspond to predicted outputs with higher variance, and making the parameterized model more descriptive by adding to the dimensionality of the latent space, and/or training the parameterized model with more diverse training data associated with one or more determined clusters or parts thereof associated with predicted outputs with the higher variance.
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公开(公告)号:US20190310554A1
公开(公告)日:2019-10-10
申请号:US16464705
申请日:2017-11-29
Applicant: ASML NETHERLANDS B.V.
Inventor: Scott Anderson MIDDLEBROOKS , Adrianus Cornelis Matheus KOOPMAN , Markus Gerardus Martinus Maria VAN KRAAIJ , Maxim PISARENCO
IPC: G03F7/20
Abstract: A method including: obtaining a logistic mathematical model predicting the formation of a physical structure created using a patterning process; evaluating the logistic mathematical model to predict formation of a part of the physical structure and generate an output; and adapting, based on the output, an aspect of the patterning process.
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公开(公告)号:US20190033725A1
公开(公告)日:2019-01-31
申请号:US16042302
申请日:2018-07-23
Applicant: ASML Netherlands B.V.
Inventor: Nitesh PANDEY , Maxim PISARENCO , Alessandro POLO
IPC: G03F7/20 , G01N21/956 , G01N29/06
Abstract: A method and apparatus to measure overlay from images of metrology targets, images obtained using acoustic waves, for example images obtained using an acoustic microscope. The images of two targets are obtained, one image using acoustic waves and one image using optical waves, the edges of the images are determined and overlay between the two targets is obtained as the difference between the edges of the two images.
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公开(公告)号:US20240062356A1
公开(公告)日:2024-02-22
申请号:US18268924
申请日:2021-12-09
Applicant: ASML Netherlands B.V.
Inventor: Huina XU , Yana MATSUSHITA , Tanbir HASAN , Ren-Jay KOU , Namita Adrianus GOEL , Hongmei LI , Maxim PISARENCO , Marleen KOOIMAN , Chrysostomos BATISTAKIS , Johannes ONVLEE
IPC: G06T7/00
CPC classification number: G06T7/0004 , G06T2207/10061 , G06T2207/20021 , G06T2207/30148 , G06T2207/20081
Abstract: A method and apparatus for analyzing an input electron microscope image of a first area on a first wafer are disclosed. The method comprises obtaining a plurality of mode images from the input electron microscope image corresponding to a plurality of interpretable modes. The method further comprises evaluating the plurality of mode images, and determining, based on evaluation results, contributions from the plurality of interpretable modes to the input electron microscope image. The method also comprises predicting one or more characteristics in the first area on the first wafer based on the determined contributions. In some embodiments, a method and apparatus for performing an automatic root cause analysis based on an input electron microscope image of a wafer are also disclosed.
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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
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.
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