TY - GEN
T1 - Curvilinear Optical Proximity Correction via Cardinal Spline
AU - Zheng, Su
AU - Liang, Xiaoxiao
AU - Yu, Ziyang
AU - Ma, Yuzhe
AU - Yu, Bei
AU - Wong, Martin
N1 - The project is supported in part by Research Grants Council of Hong Kong SAR (No. RFS2425-4S02, No. CUHK14211824 and No. CUHK14210723), and the MIND project (MINDXZ202404).
Publisher Copyright:
© 2025 IEEE.
PY - 2025/6/22
Y1 - 2025/6/22
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=105017585564&partnerID=8YFLogxK
U2 - 10.1109/DAC63849.2025.11133367
DO - 10.1109/DAC63849.2025.11133367
M3 - Conference proceeding
AN - SCOPUS:105017585564
SN - 9798331503055
T3 - Proceedings - Design Automation Conference
BT - 2025 62nd ACM/IEEE Design Automation Conference, DAC 2025
PB - IEEE
T2 - 62nd ACM/IEEE Design Automation Conference, DAC 2025
Y2 - 22 June 2025 through 25 June 2025
ER -