Curvilinear Optical Proximity Correction via Cardinal Spline

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.

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Publication Details

Published
2025-06-22
DOI
https://doi.org/10.1109/dac63849.2025.11133367
Citations
2
Primary Topic
Advanced Numerical Analysis Techniques
Type
article
Field-Weighted Citation Impact
2.67
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article

Curvilinear Optical Proximity Correction via Cardinal Spline

Bei Yu, Martin D. F. Wong, Xiaoxiao Liang, Ziyang Yu et al.
2 citations
Advanced Numerical Analysis Techniques
2.67
article

Curvilinear Optical Proximity Correction via Cardinal Spline

Bei Yu, Martin D. F. Wong, Xiaoxiao Liang, Ziyang Yu, Yuzhe Ma, Su Zheng
article en
2 citations

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.

Hong Kong Baptist University (HK), Chinese University of Hong Kong (HK)
Openalex Percentile: Top 10%
Advanced Numerical Analysis Techniques
2.67
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