Patent · US Active

Large scale computational lithography using machine learning models

US12249115B2 · kind B2 · utility

0Cited by

0References

20Claims

0Family size

Assignee

SYNOPSYS, INC. · US

Inventors

Dereje Shewaseged Woldeamanual · Munich, DE
Thomas Mulders · Erding, DE
Jiuzhou Tang · Munich, DE
Rainer Zimmermann · Paderborn, DE
Robert M. Lugg · Portland, US
Hans-Jürgen Stock · Dachau, DE
Georg Albert Viehöver · Höhenkirchen-Siegertsbrunn, DE

Key dates

Filing date	May 23, 2022
Grant date	Mar 11, 2025
Priority date	—
Expiry date	Apr 22, 2043

Classification

Technology area (CPC G)Physics
CPC primaryG06V20/69
WIPO fieldComputer technology
WIPO sectorElectrical engineering

Abstract

A computational lithography process uses machine learning models. An aerial image produced by a lithographic mask is first calculated using a two-dimensional model of the lithographic mask. This first aerial image is applied to a first machine learning model, which infers a second aerial image. The first machine learning model was trained using a training set that includes aerial images calculated using a more accurate three-dimensional model of lithographic masks. The two-dimensional model is faster to compute than the three-dimensional model but it is less accurate. The first machine learning model mitigates this inaccuracy.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.