公开(公告)号：US20220137503A1

公开(公告)日：2022-05-05

申请号：US17429770

申请日：2020-01-24

Applicant: ASML NETHERLANDS B.V.

Inventor： Jun TAO ,  Stanislas Hugo Louis BARON ,  Jing SU ,  Ya LUO ,  Yu CAO

IPC: G03F1/36 ,  G06T7/00 ,  G06T7/60

Abstract: Training methods and a mask correction method. One of the methods is for training a machine learning model configured to predict a post optical proximity correction (OPC) image for a mask. The method involves obtaining (i) a pre-OPC image associated with a design layout to be printed on a substrate, (ii) an image of one or more assist features for the mask associated with the design layout, and (iii) a reference post-OPC image of the design layout; and training the machine learning model using the pre-OPC image and the image of the one or more assist features as input such that a difference between the reference image and a predicted post-OPC image of the machine learning model is reduced.

公开(公告)号：US20200050099A1

公开(公告)日：2020-02-13

申请号：US16606791

申请日：2018-05-04

Applicant: ASML NETHERLANDS B.V.

Inventor： Jing SU ,  Yi ZOU ,  Chenxi LIN ,  Yu CAO ,  Yen-Wen LU ,  Been-Der CHEN ,  Quan ZHANG ,  Stanislas Hugo Louis BARON ,  Ya LUO

IPC: G03F1/36 ,  G06F17/50 ,  G06N20/10 ,  G05B19/4097 ,  G06K9/46 ,  G06T7/60 ,  G06T7/00

Abstract: A method including: obtaining a portion of a design layout; determining characteristics of assist features based on the portion or characteristics of the portion; and training a machine learning model using training data including a sample whose feature vector includes the characteristics of the portion and whose label includes the characteristics of the assist features. The machine learning model may be used to determine characteristics of assist features of any portion of a design layout, even if that portion is not part of the training data.