公开(公告)号：US20240370621A1

公开(公告)日：2024-11-07

申请号：US18686994

申请日：2022-08-22

Applicant: ASML NETHERLANDS B.V.

Inventor： Meng LIU ,  Been-Der CHEN ,  Debao SHAO ,  Jen-Yi WUU ,  Hao CHEN ,  Ayman HAMOUDA ,  Jianhua CHENG

IPC: G06F30/392 ,  G06F111/20

Abstract: Selecting an optimized, geometrically diverse subset of clips for a design layout for a semiconductor wafer is described. A complete representation of the design layout is received. A set of representative clips of the design layout is determined such that individual representative clips comprise different combinations of one or more unique patterns of the design layout. A subset of the representative clips is selected based on the one or more unique patterns. The subset of the representative clips is configured to include: (1) each geometrically unique pattern in a minimum number of representative clips; or (2) as many geometrically unique patterns of the design layout as possible in a maximum number of representative clips. The subset of representative clips is provided as training data for training an optical proximity correction or source mask optimization semiconductor process machine learning model, for example.

公开(公告)号：US20240345487A1

公开(公告)日：2024-10-17

申请号：US18681613

申请日：2022-08-02

Applicant: ASML NETHERLANDS B.V.

Inventor： Rencheng SUN ,  Feng YANG ,  Meng LIU ,  Fei YAN

IPC: G03F7/00

CPC classification number: G03F7/705 ,  G03F7/70441

Abstract: Systems and methods for evaluating selected set of patterns of a design layout. A method herein includes obtaining (i) a first pattern set resulting from a pattern selection process, (ii) first pattern data associated with the first pattern set, (iii) characteristic data associated with the first pattern data, and (iv) second pattern data associated with a second pattern set. A machine learning model is trained based on the characteristic data, where the machine learning model being configured to predict pattern data for an input pattern. The second pattern set is input to the trained machine learning model to predict second pattern data of the second pattern set. The first pattern set is evaluated by comparing the second pattern data and the predicted second pattern data. If the evaluation indicates insufficient pattern coverage, additional patterns can be included to improve the pattern coverage.

公开(公告)号：US20230273528A1

公开(公告)日：2023-08-31

申请号：US18018034

申请日：2021-07-29

Applicant: ASML NETHERLANDS B.V.

Inventor： Rencheng SUN ,  Qi JIA ,  Meng LIU ,  Weixuan HU ,  Jen-Yi WUU ,  Hao CHEN

IPC: G03F7/20 ,  G03F7/00 ,  G06N20/00 ,  G05B19/4099

CPC classification number: G03F7/705 ,  G03F7/70441 ,  G03F7/706841 ,  G06N20/00 ,  G05B19/4099 ,  G05B2219/45031

Abstract: A method for selecting patterns for training a model to predict patterns to be printed on a substrate. The method includes (a) obtaining images of multiple patterns, wherein the multiple patterns correspond to target patterns to be printed on a substrate; (b) grouping the images into a group of special patterns and multiple groups of main patterns; and (c) outputting a set of patterns based on the images as training data for training the model, wherein the set of patterns includes the group of special patterns and a representative main pattern from each group of main patterns.

公开(公告)号：US20240037897A1

公开(公告)日：2024-02-01

申请号：US18265431

申请日：2021-11-24

Applicant: ASML NETHERLANDS B.V.

Inventor： Danying LI ,  Meng LIU ,  Jen-Yi WUU ,  Rencheng SUN ,  Cong WU ,  Dean XU

IPC: G06V10/44 ,  G06T7/11 ,  G06V10/764

CPC classification number: G06V10/44 ,  G06T7/11 ,  G06V10/764

Abstract: An apparatus and method of feature extraction for identifying a pattern. An improved method includes obtaining data representative of a pattern instance, dividing the pattern instance into a plurality of zones, determining a representative characteristic of a zone of the plurality of zones, generating a representation of the pattern instance using a feature vector, wherein the feature vector includes an element corresponding to the representative characteristic, wherein the representative characteristic is indicative of a spatial distribution of one or more features of the zone. The method may also include classifying and/or selecting pattern instances based on the feature vector.