Curvilinear Optical Proximity Correction via Cardinal Spline

Su Zheng, Xiaoxiao Liang, Ziyang Yu, Yuzhe Ma, Bei Yu, Martin Wong

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

Abstract

This paper presents a novel curvilinear optical proximity correction (OPC) framework. The proposed approach involves representing mask patterns with control points, which are interconnected through cardinal splines. Mask optimization is achieved by iteratively adjusting these control points, guided by lithography simulation. To ensure compliance with mask rule checking (MRC) criteria, we develop comprehensive methods for checking width, space, area, and curvature. Additionally, to match the performance of inverse lithography techniques (ILT), we design algorithms to fit ILT results and resolve MRC violations. Extensive experiments demonstrate the effectiveness of our methodology, highlighting its potential as a viable OPC/ILT alternative.

Original languageEnglish
Title of host publication2025 62nd ACM/IEEE Design Automation Conference, DAC 2025
PublisherIEEE
Number of pages7
ISBN (Electronic)9798331503048
ISBN (Print)9798331503055
DOIs
Publication statusPublished - 22 Jun 2025
Event62nd ACM/IEEE Design Automation Conference, DAC 2025 - San Francisco, United States
Duration: 22 Jun 202525 Jun 2025

Publication series

NameProceedings - Design Automation Conference
ISSN (Print)0738-100X

Conference

Conference62nd ACM/IEEE Design Automation Conference, DAC 2025
Country/TerritoryUnited States
CitySan Francisco
Period22/06/2525/06/25

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