公开(公告)号：WO2021104718A1

公开(公告)日：2021-06-03

申请号：PCT/EP2020/077115

申请日：2020-09-28

Applicant: ASML NETHERLANDS B.V.

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

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.

公开(公告)号：WO2023021097A1

公开(公告)日：2023-02-23

申请号：PCT/EP2022/072980

申请日：2022-08-17

Applicant: ASML NETHERLANDS B.V.

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

IPC: G03F7/20 ,  G06N7/00

Abstract: A method of designing a target comprising providing an initial dataset, obtaining a model of the initial dataset, performing a Bayesian optimization using the model which provides an improved model, performing an optimization of the target design using the improved model.

公开(公告)号：WO2022253526A1

公开(公告)日：2022-12-08

申请号：PCT/EP2022/062486

申请日：2022-05-09

Applicant: ASML NETHERLANDS B.V.

Inventor： NIENHUYS, Han-Kwang ,  HELFENSTEIN, Patrick, Philipp ,  ROOBOL, Sander, Bas ,  VAN RIJSWIJK, Loes, Frederique ,  SCHOLZ, Sandy, Claudia

IPC: G03F7/20

Abstract: Disclosed is a method of measuring a target on a substrate using a metrology tool comprising an illumination source operable to emit an illumination beam for illuminating the target and a metrology sensor for collecting the scattered radiation having been scattered by the target. The method comprises calculating a target angle based on cell dimensions of a unit cell of said target in a first direction and a second direction orthogonal to said first direction; and order numbers of a selected pair of complementary diffraction orders in said first direction and second direction. At least one pair of measurement acquisitions is performed at a first target orientation and a second target orientation with respect to the illumination beam, wherein said target angle for at least one of said at least one pair of measurement acquisitions is an oblique angle.

公开(公告)号：WO2022194483A1

公开(公告)日：2022-09-22

申请号：PCT/EP2022/053969

申请日：2022-02-17

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.