Presentation + Paper
12 October 2021 Using curvature-based pre-bias to reduce number of iterations in curvilinear mask process correction
Author Affiliations +
Abstract
In this work, we present using curvature-based pre-bias to reduce the number of iterations required to reach convergence in curvilinear mask correction. The pre-bias is generated with a simple curvature, which extracts the input contour curvature. Although the curvature-aware model is simple, the created pre-bias is close to the converged MPC correction output. Therefore, fewer iterations with the full model are needed to reach convergence. In the meantime, since the curvature model is simple and does not require high compute resources, the total runtime of curvilinear MPC can be reduced.
Conference Presentation
© (2021) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Zhiheng (Mary) Zuo, Malavika Sharma, Ingo Bork, Bhardwaj Durvasula, and Peter Buck "Using curvature-based pre-bias to reduce number of iterations in curvilinear mask process correction", Proc. SPIE 11855, Photomask Technology 2021, 118550Q (12 October 2021); https://doi.org/10.1117/12.2600959
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KEYWORDS
Photomasks

Optical proximity correction

Manufacturing

Model-based design

Process modeling

Computational lithography

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