Addressing optical proximity correction challenges from highly nonlinear models

Stephen Jang; Yunqiang Zhang; Tom Cecil; Howard Cai; Amyn Poonawala; Matt St. John

doi:10.1117/12.2258088

24 March 2017 Addressing optical proximity correction challenges from highly nonlinear models

Stephen Jang, Yunqiang Zhang, Tom Cecil, Howard Cai, Amyn Poonawala, Matt St. John

Proceedings Volume 10147, Optical Microlithography XXX; 101471S (2017) https://doi.org/10.1117/12.2258088
Event: SPIE Advanced Lithography, 2017, San Jose, California, United States

Abstract

Model-based optical proximity correction (MB-OPC) has been widely applied in advanced lithography processes today. As k1 factor decreases and circuit design complexity increases, various advanced OPC modeling techniques have been employed to better simulate the lithography processes, such as mask3D (M3D), negative tone development (NTD) modeling techniques, etc. These advanced OPC modeling techniques introduce increasingly nonlinear behaviors in MB-OPC and bring many challenges in controlling edge placement error (EPE) and critical dimension (CD) while maintaining non-aggressive mask correction where possible for mask-rule check (MRC) compliance and better yield. In this paper, we review the MB-OPC challenges, and show our integration of Proteus inverse lithography technology (ILT) with MB-OPC as the solution to these challenges.

Citation Download Citation

Stephen Jang, Yunqiang Zhang, Tom Cecil, Howard Cai, Amyn Poonawala, and Matt St. John "Addressing optical proximity correction challenges from highly nonlinear models", Proc. SPIE 10147, Optical Microlithography XXX, 101471S (24 March 2017); https://doi.org/10.1117/12.2258088

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