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Proceedings Paper

Model-assisted template extraction SRAF application to contact holes patterns in high-end flash memory device fabrication
Author(s): Ahmed Seoud; Juhwan Kim; Yuansheng Ma; Srividya Jayaram; Le Hong; Gyu-Yeol Chae; Jeong-Woo Lee; Dae-Jin Park; Hyoung-Soon Yune; Se-Young Oh; Chan-Ha Park
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Paper Abstract

Sub-resolution assist feature (SRAF) insertion techniques have been effectively used for a long time now to increase process latitude in the lithography patterning process. Rule-based SRAF and model-based SRAF are complementary solutions, and each has its own benefits, depending on the objectives of applications and the criticality of the impact on manufacturing yield, efficiency, and productivity. Rule-based SRAF provides superior geometric output consistency and faster runtime performance, but the associated recipe development time can be of concern. Model-based SRAF provides better coverage for more complicated pattern structures in terms of shapes and sizes, with considerably less time required for recipe development, although consistency and performance may be impacted. In this paper, we introduce a new model-assisted template extraction (MATE) SRAF solution, which employs decision tree learning in a model-based solution to provide the benefits of both rule-based and model-based SRAF insertion approaches. The MATE solution is designed to automate the creation of rules/templates for SRAF insertion, and is based on the SRAF placement predicted by model-based solutions. The MATE SRAF recipe provides optimum lithographic quality in relation to various manufacturing aspects in a very short time, compared to traditional methods of rule optimization. Experiments were done using memory device pattern layouts to compare the MATE solution to existing model-based SRAF and pixelated SRAF approaches, based on lithographic process window quality, runtime performance, and geometric output consistency.

Paper Details

Date Published: 20 March 2018
PDF: 10 pages
Proc. SPIE 10587, Optical Microlithography XXXI, 105870L (20 March 2018); doi: 10.1117/12.2297659
Show Author Affiliations
Ahmed Seoud, Mentor, a Siemens Business (United States)
Juhwan Kim, Mentor, a Siemens Business (United States)
Yuansheng Ma, Mentor, a Siemen's Business (United States)
Srividya Jayaram, Mentor, a Siemens Business (United States)
Le Hong, Mentor, a Siemens Business (United States)
Gyu-Yeol Chae, Mentor Korea (Korea, Republic of)
Jeong-Woo Lee, Mentor Korea (Korea, Republic of)
Dae-Jin Park, SK Hynix, Inc. (Korea, Republic of)
Hyoung-Soon Yune, SK Hynix, Inc. (Korea, Republic of)
Se-Young Oh, SK Hynix, Inc. (Korea, Republic of)
Chan-Ha Park, SK Hynix, Inc. (Korea, Republic of)

Published in SPIE Proceedings Vol. 10587:
Optical Microlithography XXXI
Jongwook Kye, Editor(s)

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