公开(公告)号：EP4060408A1

公开(公告)日：2022-09-21

申请号：EP21162785.6

申请日：2021-03-16

Applicant: ASML Netherlands B.V.

Inventor： HELFENSTEIN, Patrick, Philipp ,  MIDDLEBROOKS, Scott, Anderson ,  PISARENCO, Maxim ,  VAN KRAAIJ, Markus, Gerardus, Martinus, Maria ,  KONIJNENBERG, Alexander, Prasetya

IPC: G03F7/20 ,  G06N3/02

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.

公开(公告)号：EP3918420A1

公开(公告)日：2021-12-08

申请号：EP20700456.5

申请日：2020-01-09

Applicant: ASML Netherlands B.V.

Inventor： HUBAUX, Arnaud ,  BECKERS, Johan, Franciscus, Maria ,  DAVIES, Dylan John David ,  KUNNEN, Johan, Gertrudis, Cornelis ,  PONGERS, Willem, Richard ,  DAWARE, Ajinkya, Ravindra ,  LI, Chung-Hsun ,  TSIROGIANNIS, Georgios ,  BORGER, Hendrik, Cornelis, Anton ,  DE JONG, Frederik Eduard ,  GONZALEZ HUESCA, Juan Manuel ,  HLOD, Andriy, Vasyliovich ,  PISARENCO, Maxim

IPC: G03F7/20 ,  G05B23/02 ,  G05B19/418

公开(公告)号：EP3893057A1

公开(公告)日：2021-10-13

申请号：EP20169199.5

申请日：2020-04-10

Applicant: ASML Netherlands B.V.

Inventor： VERSCHUREN, Coen, Adrianus ,  MIDDLEBROOKS, Scott, Anderson ,  PISARENCO, Maxim

IPC: G03F7/20 ,  G01N21/956 ,  G06K9/62 ,  G06N3/02

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.

公开(公告)号：EP3789923A1

公开(公告)日：2021-03-10

申请号：EP19195954.3

申请日：2019-09-06

Applicant: ASML Netherlands B.V.

Inventor： PISARENCO, Maxim ,  MIDDLEBROOKS, Scott Anderson ,  VERSCHUREN, Coen Adrianus

IPC: G06N3/04 ,  G06N3/08 ,  G06N7/00

Abstract: A method for increasing certainty in parameterized model predictions is described. The method comprises 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 comprises predicting, with the parameterized model, an output based on the dimensional data in the latent space. The method comprises 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 comprises determining which 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 of the determined clusters or parts of clusters associated with the higher variance.

公开(公告)号：EP3594750A1

公开(公告)日：2020-01-15

申请号：EP18182602.5

申请日：2018-07-10

Applicant: ASML Netherlands B.V.

Inventor： PISARENCO, Maxim ,  MIDDLEBROOKS, Scott Anderson ,  VAN KRAAIJ, Markus Gerardus Martinus Maria ,  KOOPMAN, Adrianus Cornelis Matheus

IPC: G03F7/20 ,  G03F1/84 ,  G03F1/86 ,  G06T7/00 ,  G01N21/956

Abstract: A method for determining the existence of a defect in a printed pattern includes 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 also includes generating a combined image as a weighted combination of portions of the captured image and the simulated image. Also, the method includes determining whether a defect exists in the printed pattern based on the combined image.

公开(公告)号：EP3523698A1

公开(公告)日：2019-08-14

申请号：EP18727761.1

申请日：2018-05-23

Applicant: ASML Netherlands B.V.

Inventor： HARUTYUNYAN, Davit ,  JIA, Fei ,  STAALS, Frank ,  WANG, Fuming ,  LOOIJESTIJN, Hugo, Thomas ,  RIJNIERSE, Cornelis, Johannes ,  PISARENCO, Maxim ,  WERKMAN, Roy ,  THEEUWES, Thomas ,  VAN HEMERT, Tom ,  BASTANI, Vahid ,  WILDENBERG, Jochem, Sebastiaan ,  MOS, Everhardus, Cornelis ,  WALLERBOS, Erik, Johannes, Maria

IPC: G03F7/20 ,  G05B13/04 ,  G05B19/418 ,  H01L21/66

公开(公告)号：EP4502926A1

公开(公告)日：2025-02-05

申请号：EP23188908.0

申请日：2023-08-01

Applicant: ASML Netherlands B.V.

Inventor： BOTARI, Tiago ,  ONOSE, Alexandru ,  TRAJANOSKA, Marija ,  PISARENCO, Maxim ,  KIEHN, Moritz, Simon, Maria ,  KUIPER, Vincent, Sylvester

IPC: G06T7/00 ,  G06T7/194 ,  G01N23/2251 ,  G03F7/00 ,  G06V20/69 ,  H01L21/66

Abstract: A data processing method for image data obtained by scanning a charged particle beam across a sample; the method comprising:
classifying pixels of the image data into foreground pixels and background pixels to generate a foreground pixel map; and
encoding the foreground pixel map as encoded data using a sparse matrix encoding technique.

公开(公告)号：EP4123583A1

公开(公告)日：2023-01-25

申请号：EP21186830.2

申请日：2021-07-21

Applicant: ASML Netherlands B.V.

Inventor： PISARENCO, Maxim ,  MIDDLEBROOKS, Scott, Anderson ,  VAN KRAAIJ, Markus, Gerardus, Martinus, Maria ,  VERSCHUREN, Coen, Adrianus

IPC: G06T11/00 ,  G06T5/00

Abstract: Disclosed herein is a non-transitory computer readable medium that has stored therein a computer program, wherein the computer program comprises code that, when executed by a computer system, instructs the computer system to perform a method for generating synthetic distorted images, the method comprising: obtaining an input set that comprises a plurality of distorted images; determining, using a model, distortion modes of the distorted images in the input set; generating a plurality of different combinations of the distortion modes; generating, for each one of the plurality of combinations of the distortion modes, a synthetic distorted image in dependence on the combination; and including each of the synthetic distorted images in an output set.

公开(公告)号：EP4086703A1

公开(公告)日：2022-11-09

申请号：EP21172589.0

申请日：2021-05-06

Applicant: ASML Netherlands B.V.

Inventor： BATISTAKIS, Chrysostomos ,  PISARENCO, Maxim ,  VAN KRAAIJ, Markus Gerardus Martinus Maria ,  RUTIGLIANI, Vito Daniele ,  MIDDLEBROOKS, Scott Anderson

IPC: G03F7/20

Abstract: Disclosed is a method of determining at least one stochastic metric relating to a lithographic process and associated optical metrology device. The method comprises obtaining a trained machine learning model, the machine learning model having been trained to infer one or more stochastic metric values for said stochastic metric from optical metrology data. Optical metrology data comprising at least one measurement signal relating to a structure having been exposed in a lithographic process is obtained and the trained machine learning model used to infer a value for said stochastic metric from said optical metrology data.

公开(公告)号：EP3828632A1

公开(公告)日：2021-06-02

申请号：EP19212419.6

申请日：2019-11-29

Applicant: ASML Netherlands B.V.

Inventor： MIDDLEBROOKS, Scott, Anderson ,  PISARENCO, Maxim ,  VAN KRAAIJ, Markus, Gerardus, Martinus, Maria ,  KONIJNENBERG, Alexander, Prasetya ,  HELFENSTEIN, Patrick, Philipp

IPC: G03F7/20 ,  G06K9/36 ,  G06N3/02 ,  G06N3/04 ,  G06N20/00 ,  G06T7/00

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.