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Proceedings Paper

EUV computational lithography using accelerated topographic mask simulation
Author(s): Vitaly Domnenko; Bernd Küchler; Wolfgang Hoppe; Jürgen Preuninger; Ulrich Klostermann; Wolfgang Demmerle; Martin Bohn; Dietmar Krüger; Ryoung Ryoung Han Kim; Ling Ee Tan
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Paper Abstract

As EUV lithography is getting ready for deployment in high volume manufacturing, lithography engineering focus moves to efficient computational lithography tools (mask correction, verification, source-, mask- and processoptimization) providing optimal RET solutions for EUV early design exploration. Key to computational lithography success is the prediction ability of the underlying lithography process simulation model. Topographic mask effects prediction is one of the major challenges with significant impact on both simulation quality of results and turn around time. In this paper, we apply a fast modeling approach to EUV light diffraction on topographic masks, which is based on fully rigorous topographic mask simulations. It is demonstrating performance benefits of several orders of magnitude while maintaining the accuracy requirements for productive cases. We explore its applicability to medium sized computational lithography tasks. The accurate mask solver results will be complemented with imaging and 3D resist simulations using the rigorous lithography simulator S-Litho by Synopsys.

Paper Details

Date Published: 4 April 2019
PDF: 8 pages
Proc. SPIE 10962, Design-Process-Technology Co-optimization for Manufacturability XIII, 109620O (4 April 2019); doi: 10.1117/12.2515668
Show Author Affiliations
Vitaly Domnenko, Synopsys SPb, LLC (Russian Federation)
Bernd Küchler, Synopsys GmbH (Germany)
Wolfgang Hoppe, Synopsys GmbH (Germany)
Jürgen Preuninger, Synopsys GmbH (Germany)
Ulrich Klostermann, Synopsys GmbH (Germany)
Wolfgang Demmerle, Synopsys GmbH (Germany)
Martin Bohn, Synopsys GmbH (Germany)
Dietmar Krüger, Synopsys GmbH (Germany)
Ryoung Ryoung Han Kim, IMEC (Belgium)
Ling Ee Tan, IMEC (Belgium)

Published in SPIE Proceedings Vol. 10962:
Design-Process-Technology Co-optimization for Manufacturability XIII
Jason P. Cain, Editor(s)

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