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Proceedings Paper

Smart data filtering for enhancement of model accuracy
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Paper Abstract

As integrated circuit technology advances and features shrink, the scale of critical dimension (CD) variations induced by lithography effects become comparable with the critical dimension of the design itself. At the same time, each technology node requires tighter margins for errors introduced in the lithography process. Optical and process models -- the black boxes that simulate the pattern transfer onto silicon -- are becoming more and more concerned with those different process errors. As a consequence, an optical proximity correction (OPC) model consists mainly of two parts; a physical part dealing with the physics of light and its behavior through the lithographical patterning process, and an empirical part to account for any process errors that might be introduced between writing the mask and sampling measurements of patterns on wafer. Understanding how such errors can affect a model's stability and predictability, and taking such errors into consideration while building a model, could actually help convergence, stability, and predictability of the model when it comes to design patterns other than those used during model calibration and verification. This paper explores one method to quickly enhance model accuracy and stability.

Paper Details

Date Published: 16 March 2009
PDF: 6 pages
Proc. SPIE 7274, Optical Microlithography XXII, 727423 (16 March 2009); doi: 10.1117/12.814153
Show Author Affiliations
Shady Abdelwahed, Mentor Graphics Corp. (Egypt)
Jae Hyun Kang, Dongbu HiTek Co., Ltd. (Korea, Republic of)
Jaeyoung Choi, Dongbu HiTek Co., Ltd. (Korea, Republic of)
Jong Doo Kim, Dongbu HiTek Co., Ltd. (Korea, Republic of)
Hyesung Lee, Dongbu HiTek Co., Ltd. (Korea, Republic of)
Sungho Jun, Dongbu HiTek Co., Ltd. (Korea, Republic of)
Youngmi Kim, Dongbu HiTek Co., Ltd. (Korea, Republic of)

Published in SPIE Proceedings Vol. 7274:
Optical Microlithography XXII
Harry J. Levinson; Mircea V. Dusa, Editor(s)

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