公开(公告)号：US20250044710A1

公开(公告)日：2025-02-06

申请号：US18714547

申请日：2022-12-13

Applicant: ASML NETHERLANDS B.V.

Inventor： Jiyou FU ,  Jing SU ,  Chenxi LIN ,  Jiao LIANG ,  Guangqing CHEN ,  Yi ZOU

IPC: G03F7/00 ,  G03F9/00 ,  G06T7/00 ,  G06T7/33 ,  H01L21/66

Abstract: A method of image template matching for multiple process layers of, for example, semiconductor substrate with an adaptive weight map is described. An image template is provided with a weight map, which is adaptively updated based during template matching based on the position of the image template on the image. A method of template matching a grouped pattern or artifacts in a composed template is described, wherein the pattern comprises deemphasized areas weighted less than the image templates. A method of generating an image template based on a synthetic image is described. The synthetic image can be generated based on process and image modeling. A method of selecting a grouped pattern or artifacts and generating a composed template is described. A method of per layer image template matching is described.

公开(公告)号：US20240069450A1

公开(公告)日：2024-02-29

申请号：US18267734

申请日：2021-12-08

Applicant: ASML Netherlands B.V.

Inventor： Nabeel Noor MOIN ,  Chenxi LIN ,  Yi ZOU

IPC: G03F7/00 ,  G06N20/20

CPC classification number: G03F7/7065 ,  G03F7/706841 ,  G06N20/20

Abstract: A method and apparatus for training a defect location prediction model to predict a defect for a substrate location is disclosed. A number of datasets having data regarding process-related parameters for each location on a set of substrates is received. Some of the locations have partial datasets in which data regarding one or more process-related parameters is absent. The datasets are processed to generate multiple parameter groups having data for different sets of process-related parameters. For each parameter group, a sub-model of the defect location prediction model is created based on the corresponding set of process-related parameters and trained using data from the parameter group. A trained sub-model(s) may be selected based on process-related parameters available in a candidate dataset and a defect prediction may be generated for a location associated with the candidate dataset using the selected sub-model.

公开(公告)号：US20230401694A1

公开(公告)日：2023-12-14

申请号：US18033786

申请日：2021-11-02

Applicant: ASML NETHERLANDS B.V.

Inventor： Chenxi LIN ,  Yi ZOU ,  Tanbir HASAN ,  Huina XU ,  Ren-Jay KOU ,  Nabeel Noor MOIN ,  Kourosh NAFISI

IPC: G06T7/00

CPC classification number: G06T7/001 ,  G06T2207/20081 ,  G06T2207/30148

Abstract: A method and apparatus for identifying locations to be inspected on a substrate is disclosed. A defect location prediction model is trained using a training dataset associated with other substrates to generate a prediction of defect or non-defect and a confidence score associated with the prediction for each of the locations based on process-related data associated with the substrates. Those of the locations determined by the defect location prediction model as having confidences scores satisfying a confidence threshold are added to a set of locations to be inspected by an inspection system. After the set of locations are inspected, the inspection results data is obtained, and the defect location prediction model is incrementally trained by using the inspection results data and process-related data for the set of locations as training data.

公开(公告)号：US20220291590A1

公开(公告)日：2022-09-15

申请号：US17634309

申请日：2020-07-09

Applicant: ASML NETHERLANDS B.V.

Inventor： Jing SU ,  Yana CHENG ,  Zchenxi LIN ,  Yi ZOU ,  Ddavit HARUTYUNYAN ,  Emil Peter SCHMITT-WEAVER ,  Kaustuve BHATTACHARYYA ,  Cornelis Johannes Henricus LAMBREGTS ,  Hadi YAGUBIZADE

IPC: G03F7/20

Abstract: A method for determining a model to predict overlay data associated with a current substrate being patterned. The method involves obtaining (i) a first data set associated with one or more prior layers and/or current layer of the current substrate, (ii) a second data set including overlay metrology data associated with one or more prior substrates, and (iii) de-corrected measured overlay data associated with the current layer of the current substrate; and determining, based on (i) the first data set, (ii) the second data set, and (iii) the de-corrected measured overlay data, values of a set of model parameters associated with the model such that the model predicts overlay data for the current substrate, wherein the values are determined such that a cost function is minimized, the cost function comprising a difference between the predicted data and the de-corrected measured overlay data.

公开(公告)号：US20230273529A1

公开(公告)日：2023-08-31

申请号：US18012222

申请日：2021-06-14

Applicant: ASML NETHERLANDS B.V.

Inventor： Satej Subhash KHEDEKAR ,  Henricus Jozef CASTELIJNS ,  Anjan Prasad GANTAPARA ,  Stephen Henry BOND ,  Seyed Iman MOSSAVAT ,  Alexander YPMA ,  Gerald DICKER ,  Ewout Klaas STEINMEIER ,  Chaoqun GUO ,  Chenxi LIN ,  Hongwei CHEN ,  Zhaoze LI ,  Youping ZHANG ,  Yi ZOU ,  Koos VAN BERKEL ,  Joost Johan BOLDER ,  Arnaud HUBAUX ,  Andriy Vasyliovich HLOD ,  Juan Manuel GONZALEZ HUESCA ,  Frans Bernard AARDEN

IPC: G03F7/20

CPC classification number: G03F7/70525 ,  G03F7/70633 ,  G03F7/7065

Abstract: Generating a control output for a patterning process is described. A control input is received. The control input is for controlling the patterning process. The control input includes one or more parameters used in the patterning process. The control output is generated with a trained machine learning mod& based on the control input, The machine learning model is trained with training data generated from simulation of the patterning process and/or actual process data, The training data includes 1) a plurality of training control inputs corresponding to a plurality of operational conditions of the patterning process, where the plurality of operational conditions of the patterning process are associated with operational condition specific behavior of the patterning process over time, and 2) training control outputs generated using a physical model based on the training control inputs.

公开(公告)号：US20200380362A1

公开(公告)日：2020-12-03

申请号：US16970648

申请日：2019-02-20

Applicant: ASML NETHERLANDS B.V.

Inventor： Yu CAO ,  Ya LUO ,  Yen-Wen LU ,  Been-Der CHEN ,  Rafael C. HOWELL ,  Yi ZOU ,  Jing SU ,  Dezheng SUN

IPC: G06N3/08 ,  G06N3/04

Abstract: Methods of training machine learning models related to a patterning process, including a method for training a machine learning model configured to predict a mask pattern. The method including obtaining (i) a process model of a patterning process configured to predict a pattern on a substrate, wherein the process model comprises one or more trained machine learning models, and (ii) a target pattern, and training the machine learning model configured to predict a mask pattern based on the process model and a cost function that determines a difference between the predicted pattern and the target pattern.

公开(公告)号：US20220026810A1

公开(公告)日：2022-01-27

申请号：US17297171

申请日：2019-11-14

Applicant: ASML NETHERLANDS B.V.

Inventor： Nicolaas Petrus Marcus BRANTJES ,  Matthijs COX ,  Boris MENCHTCHIKOV ,  Cyrus Emil TABERY ,  Youping ZHANG ,  Yi ZOU ,  Chenxi LIN ,  Yana CHENG ,  Simon Philip Spencer HASTINGS ,  Maxim Philippe Frederic GENIN

IPC: G03F7/20 ,  G03F9/00 ,  G05B13/02

Abstract: A method for determining a correction relating to a performance metric of a semiconductor manufacturing process, the method including: obtaining a set of pre-process metrology data; processing the set of pre-process metrology data by decomposing the pre-process metrology data into one or more components which: a) correlate to the performance metric; or b) are at least partially correctable by a control process which is part of the semiconductor manufacturing process; and applying a trained model to the processed set of pre-process metrology data to determine the correction for the semiconductor manufacturing process.

公开(公告)号：US20210389677A1

公开(公告)日：2021-12-16

申请号：US17295193

申请日：2019-11-04

Applicant: ASML NETHERLANDS B.V.

Inventor： Chenxi LIN ,  Cyrus Emil TABERY ,  Hakki Ergün CEKLI ,  Simon Philip Spencer HASTINGS ,  Boris MENCHTCHIKOV ,  Yi ZOU ,  Yana CHENG ,  Maxime Philippe Frederic GENIN ,  Tzu-Chao CHEN ,  Davit HARUTYUNYAN ,  Youping ZHANG

IPC: G03F7/20 ,  G05B13/02 ,  G05B19/418 ,  H01L21/66

Abstract: A method for determining a root cause affecting yield in a process for manufacturing devices on a substrate, the method including: obtaining yield distribution data including a distribution of a yield parameter across the substrate or part thereof; obtaining sets of metrology data, each set including a spatial variation of a process parameter over the substrate or part thereof corresponding to a different layer of the substrate; comparing the yield distribution data and metrology data based on a similarity metric describing a spatial similarity between the yield distribution data and an individual set out of the sets of the metrology data; and determining a first similar set of metrology data out of the sets of metrology data, being the first set of metrology data in terms of processing order for the corresponding layers, which is determined to be similar to the yield distribution data.

公开(公告)号：US20210216697A1

公开(公告)日：2021-07-15

申请号：US15734141

申请日：2019-05-23

Applicant: ASML NETHERLANDS B.V.

Inventor： Marinus Aart VAN DEN BRINK ,  Yu CAO ,  Yi ZOU

IPC: G06F30/398 ,  G06F30/392

Abstract: A method for calibrating a process model and training an inverse process model of a patterning process. The training method includes obtaining a first patterning device pattern from simulation of an inverse lithographic process that predicts a patterning device pattern based on a wafer target layout, receiving wafer data corresponding to a wafer exposed using the first patterning device pattern, and training an inverse process model configured to predict a second patterning device pattern using the wafer data related to the exposed wafer and the first patterning device pattern.

公开(公告)号：US20210397172A1

公开(公告)日：2021-12-23

申请号：US17296316

申请日：2019-10-30

Applicant: ASML NETHERLANDS B.V.

Inventor： Abraham SLACHTER ,  Wim Tjibbo TEL ,  Daan Maurits SLOTBOOM ,  Vadim Yourievich TIMOSHKOV ,  Koen Wilhelmus Cornelis Adrianus VAN DER STRATEN ,  Boris MENCHTCHIKOV ,  Simon Philip Spencer HASTINGS ,  Cyrus Emil TABERY ,  Maxime Philippe Frederic GENIN ,  Youping ZHANG ,  Yi ZOU ,  Chenxi LIN ,  Yana CHENG

IPC: G05B19/418

Abstract: A method for analyzing a process, the method including obtaining a multi-dimensional probability density function representing an expected distribution of values for a plurality of process parameters; obtaining a performance function relating values of the process parameters to a performance metric of the process; and using the performance function to map the probability density function to a performance probability function having the process parameters as arguments.