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公开(公告)号：US20230004096A1
公开(公告)日：2023-01-05
申请号：US17780960
申请日：2020-09-28
Applicant: ASML Netherlands B.V.
Inventor： Scott Anderson MIDDLEBROOKS , Patrick WARNAAR , Patrick Philipp HELFENSTEIN , Alexander Prasetya KONIJNENBERG , Maxim PISARENCO , Markus Gerardus Martinus Maria VAN KRAAIJ
Abstract: A method and system for predicting complex electric field images with a parameterized model are described. A latent space representation of a complex electric field image is determined based on dimensional data in a latent space of the parameterized model for a given input to the parameterized model. The given input may be a measured amplitude (e.g., intensity) associated with the complex electric field image. The complex electric field image is predicted based on the latent space representation of the complex electric field image. The predicted complex electric field image includes an amplitude and a phase. The parameterized model comprises encoder-decoder architecture. In some embodiments, determining the latent space representation of the electric field image comprises minimizing a function constrained by a set of electric field images that could be predicted by the parameterized model based on the dimensional data in the latent space and the given input.
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公开(公告)号：US20220342316A1
公开(公告)日：2022-10-27
申请号：US17640792
申请日：2020-09-03
Applicant: ASML Netherlands B.V.
Inventor： Marleen KOOIMAN , Maxim PISARENCO , Abraham SLACHTER , Mark John MASLOW , Bernardo Andres OYARZUN RIVERA , Wim Tjibbo TEL , Ruben Cornelis MAAS
Abstract: 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.
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13.发明申请公开(公告)号：US20210174491A1
公开(公告)日：2021-06-10
申请号：US17145033
申请日：2021-01-08
Applicant: ASML Netherlands B.V.
Inventor： Maxim PISARENCO , Scott Anderson MIDDLEBROOKS , Markus Gerardus Martinus Maria VAN KRAAIJ , Adrianus Cornelis Matheus KOOPMAN
Abstract: A method for determining the existence of a defect in a printed pattern may include obtaining a) a captured image of a printed pattern from an image capture device, and b) a simulated image of the printed pattern generated by a process model. The method may include generating a combined image as a weighted combination of portions of the captured image and the simulated image. The method may include determining whether a defect exists in the printed pattern based on the combined image.
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14.发明申请公开(公告)号：US20190025714A1
公开(公告)日：2019-01-24
申请号：US16035961
申请日：2018-07-16
Applicant: ASML NETHERLANDS B.V.
Abstract: Methods and apparatuses for estimation of at least one parameter of interest of a feature fabricated on a substrate, the feature having a plurality of structure parameters, the structure parameters including the at least one parameter of interest and one or more nuisance parameters. A receiver receives radiation scattered from one or more measured features on the substrate. A pupil generator generates an unprocessed pupil representation of the received radiation. A matrix multiplier multiplies a transformation matrix with intensities of each of a plurality of pixels of the unprocessed pupil representation to determine a post-processed pupil representation in which effects of the one or more nuisance parameters are mitigated or removed. A parameter estimator estimates the at least one parameter of interest based on the post-processed pupil representation.
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公开(公告)号：US20170102623A1
公开(公告)日：2017-04-13
申请号：US15285051
申请日：2016-10-04
Applicant: ASML Netherlands B.V.
IPC: G03F7/20 , G01B15/00 , G01N23/201
CPC classification number: G03F7/70625 , G01B15/00 , G01N23/201 , G01N2223/501 , G03F7/705
Abstract: A structure of interest is irradiated with radiation for example in the x-ray or EUV waveband, and scattered radiation is detected by a detector (306). A processor (308) calculates a property such as linewidth (CD) by simulating interaction of radiation with a structure and comparing the simulated interaction with the detected radiation. A layered structure model (600, 610) is used to represent the structure in a numerical method. The structure model defines for each layer of the structure a homogeneous background permittivity and for at least one layer a non-homogeneous contrast permittivity. The method uses Maxwell's equation in Born approximation, whereby a product of the contrast permittivity and the total field is approximated by a product of the contrast permittivity and the background field. A computation complexity is reduced by several orders of magnitude compared with known methods.
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Patent Agency Ranking
公开(公告)号：US20250003899A1
公开(公告)日：2025-01-02
申请号：US18708929
申请日：2022-10-14
Applicant: ASML Netherlands B.V.
Inventor： Tim HOUBEN , Maxim PISARENCO , Thomas Jarik HUISMAN , Lingling PU , Jian ZHOU , Liangjiang YU , Yi-Hsin CHANG , Yun-Ling YEH
IPC: G01N23/2251 , G06T7/00
Abstract: Systems and methods for image analysis include obtaining a plurality of simulation images and a plurality of non-simulation images both associated with a sample under inspection, at least one of the plurality of simulation images being a simulation image of a location on the sample not imaged by any of the plurality of non-simulation images; and training an unsupervised domain adaptation technique using the plurality of simulation images and the plurality of non-simulation images as inputs to reduce a difference between first intensity gradients of the plurality of simulation images and second intensity gradients of the plurality of non-simulation images.
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公开(公告)号：US20240320528A1
公开(公告)日：2024-09-26
申请号：US18579560
申请日：2022-08-17
Applicant: ASML NETHERLANDS B.V.
Inventor： Patrick Philipp HELFENSTEIN , Scott Anderson MIDDLEBROOKS , Markus Gerardus Martinus Maria VAN KRAAIJ , Maxim PISARENCO
IPC: G06N7/01
CPC classification number: G06N7/01
Abstract: A method of designing a target includes obtaining a model of an initial dataset, performing a Bayesian optimization using the model which provides an improved model, and performing an optimization of the target design using the improved model.
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公开(公告)号：US20240152060A1
公开(公告)日：2024-05-09
申请号：US18282305
申请日：2022-02-17
Applicant: ASML Netherlands B.V.
Inventor： Patrick Philipp HELFENSTEIN , Scott Anderson MIDDLEBROOKS , Maxim PISARENCO , Markus Gerardus Martinus Maria VAN KRAAIJ , Alexander Prasetya KONIJNENBERG
IPC: G03F7/00
CPC classification number: G03F7/705 , G03F7/70575 , G03F7/70675
Abstract: A method and system for predicting process information (e.g., phase data) using a given input (e.g., intensity) to a parameterized model are described. A latent space of a given input is determined based on dimensional data in a latent space of the parameterized model for a given input to the parameterized model. Further, an optimum latent space is determined by constraining the latent space with prior information (e.g., wavelength) that enables converging to a solution that causes more accurate predictions of the process information. The optimum latent space is used to predict the process information. The given input may be a measured amplitude (e.g., intensity) associated with the complex electric field image. The predicted process information can be complex electric field image having amplitude data and phase data. The parameterized model comprises variational encoder-decoder architecture.
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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
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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公开(公告)号：US20220082949A1
公开(公告)日：2022-03-17
申请号：US17423325
申请日：2020-01-09
Applicant: ASML NETHERLANDS B.V.
Inventor： Arnaud HUBAUX , Johan Franciscus Maria BECKERS , Dylan John David DAVIES , Johan Gertrudis Cornelis KUNNEN , Willem Richard PONGERS , Ajinkya Ravindra DAWARE , Chung-Hsun LI , Georgios TSIROGIANNIS , Hendrik Cornelis Anton BORGER , Frederik Eduard DEJONG , Juan Manuel GONZALEZ HUESCA , Andriy HLOD , Maxim PISARENCO
IPC: G03F7/20 , G03F1/70 , G06F30/392
Abstract: A method for categorizing a substrate subject to a semiconductor manufacturing process including multiple operations, the method including: obtaining values of functional indicators derived from data generated during one or more of the multiple operations on the substrate, the functional indicators characterizing at least one operation; applying a decision model including one or more threshold values to the values of the functional indicators to obtain one or more categorical indicators; and assigning a category to the substrate based on the one or more categorical indicators.
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