公开(公告)号：US11126092B2

公开(公告)日：2021-09-21

申请号：US15774583

申请日：2016-10-07

Applicant: ASML NETHERLANDS B.V.

Inventor： Lin Lee Cheong ,  Wenjin Huang ,  Bruno La Fontaine

IPC: G03F7/20 ,  G05B19/4097

Abstract: A method including: determining a value of a characteristic of a patterning process or a product thereof, at a current value of a processing parameter; determining whether a termination criterion is met by the value of the characteristic; if the termination criterion is not met, determining a new value of the processing parameter from the current value of the processing parameter and a prior value of the processing parameter, and setting the current value to the new value and repeating the determining steps; and if the termination criterion is met, providing the current value of the processing parameter as an approximation of a value of the processing parameter at which the characteristic has a target value.

公开(公告)号：US11443083B2

公开(公告)日：2022-09-13

申请号：US16300380

申请日：2017-04-20

Applicant: ASML NETHERLANDS B.V.

Inventor： Jing Su ,  Yi Zou ,  Chenxi Lin ,  Stefan Hunsche ,  Marinus Jochemsen ,  Yen-Wen Lu ,  Lin Lee Cheong

IPC: G06T7/00 ,  G06F30/20 ,  G03F7/20 ,  G06K9/62 ,  G06F30/398 ,  G06N20/00

Abstract: Methods of identifying a hot spot from a design layout or of predicting whether a pattern in a design layout is defective, using a machine learning model. An example method disclosed herein includes obtaining sets of one or more characteristics of performance of hot spots, respectively, under a plurality of process conditions, respectively, in a device manufacturing process; determining, for each of the process conditions, for each of the hot spots, based on the one or more characteristics under that process condition, whether that hot spot is defective; obtaining a characteristic of each of the process conditions; obtaining a characteristic of each of the hot spots; and training a machine learning model using a training set including the characteristic of one of the process conditions, the characteristic of one of the hot spots, and whether that hot spot is defective under that process condition.

公开(公告)号：US20220277116A1

公开(公告)日：2022-09-01

申请号：US17744091

申请日：2022-05-13

Applicant: ASML NETHERLANDS B.V.

Inventor： Jing SU ,  Yi Zou ,  Chenxi Lin ,  Stefan Hunsche ,  Marinus Jochemsen ,  Yen-Wen Lu ,  Lin Lee Cheong

IPC: G06F30/20 ,  G03F7/20 ,  G06T7/00 ,  G06K9/62 ,  G06F30/398 ,  G06N20/00

Abstract: Methods of identifying a hot spot from a design layout or of predicting whether a pattern in a design layout is defective, using a machine learning model. An example method disclosed herein includes obtaining sets of one or more characteristics of performance of hot spots, respectively, under a plurality of process conditions, respectively, in a device manufacturing process; determining, for each of the process conditions, for each of the hot spots, based on the one or more characteristics under that process condition, whether that hot spot is defective; obtaining a characteristic of each of the process conditions; obtaining a characteristic of each of the hot spots; and training a machine learning model using a training set including the characteristic of one of the process conditions, the characteristic of one of the hot spots, and whether that hot spot is defective under that process condition.