Multigon-based curvilinear mask rule checks for advanced mask data preparation applications

Amogh Raj; Rachit Sharma; Ranganadh Peesapati; Sayalee Gharat; Stephen Kim; Ingo Bork

doi:10.1117/12.3034684

12 November 2024 Multigon-based curvilinear mask rule checks for advanced mask data preparation applications

Amogh Raj, Rachit Sharma, Ranganadh Peesapati, Sayalee Gharat, Stephen Kim, Ingo Bork

Author Affiliations +

Proceedings Volume 13216, Photomask Technology 2024; 132161O (2024) https://doi.org/10.1117/12.3034684
Event: SPIE Photomask Technology + EUV Lithography, 2024, Monterey, California, United States

Abstract

The growing adaptation of complex curvilinear masks (CL masks) and Inverse Lithography Technology (ILT) designs for advanced nodes, enabled by Multi-Beam Mask Writer’s ability to effectively write these intricate patterns, has driven the industry to explore Multigons for efficient curvilinear data representation and processing. To enable the industry to evaluate the feasibility of Multigon-based flows, the curvilinear Multigon representation was developed and integrated as an extension to the SEMI P39 OASIS format by the SEMI task force working group. Previous studies have underscored the importance of developing native Multigon processing algorithms to enhance the accuracy and efficiency of curvilinear post-tape-out applications such as Optical Proximity Correction (OPC), Mask Process Correction (MPC), Mask Data Preparation (MDP). Mask Rule Checks (MRCs) serve as a critical verification step to ensure design integrity and manufacturability of curvilinear masks. However, curvilinear masks can be more challenging to verify as they often involve freeform shapes, higher data complexity and large file sizes. In this paper, we will introduce native Multigon-based curvilinear mask rule checks and present a comprehensive study assessing the effectiveness of these checks in scenarios involving Multigon to Multigon and Multigon to Piecewise-Linear (PWL) checks. Furthermore, we will study the runtime of Multigon-based CLMRC and compare the performance to equivalent PWL based checks.

Conference Presentation

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Amogh Raj, Rachit Sharma, Ranganadh Peesapati, Sayalee Gharat, Stephen Kim, and Ingo Bork "Multigon-based curvilinear mask rule checks for advanced mask data preparation applications", Proc. SPIE 13216, Photomask Technology 2024, 132161O (12 November 2024); https://doi.org/10.1117/12.3034684

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