A. A. Kagalwalla, Michale Lam, K. Adam, Puneet Gupta
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EUV-CDA: Pattern shift aware critical density analysis for EUV mask layouts
Despite the use of mask defect avoidance and mitigation techniques, finding a usable defective mask blank remains a challenge for Extreme Ultraviolet Lithography (EUVL) at sub-10nm node due to dense layouts and low CD tolerance. In this work, we propose a pattern shift-aware metric called critical density, which can quickly evaluate the robustness of EUV layouts to mask defects (300-1300x faster than Monte Carlo, with average mask yield root mean square error (RMSE) ranging from 0.08%-6.44%), thereby enabling design-level mask defect mitigation techniques. Our experimental results indicate that reducing layout regularity improves the ability of layouts to tolerate mask defects via pattern shift.