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Proceedings Paper

Advanced module-based approach to effective CD prediction of sub-100nm patterns
Author(s): Jangho Shin; Insung Kim; Chan Hwang; Dong-Woon Park; Sang-Gyun Woo; Han-Ku Cho; Woo-Sung Han; Joo-Tae Moon
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Paper Abstract

In this article, an advanced module-based approach is introduced to simulate sub-100 nm patterns. Topography (TOPO), an in-house lithography simulator, consists of four basic modules: i) illumination, ii) mask, iii) imaging, and iv) resist. Since TOPO is module-based, it is convenient for user specific applications. The input parameter of illumination module is pupil intensity profile, which is measured using the transmission image sensor of ASML. In the mask kernel, mask corner rounding effect is considered while imaging module takes care of lens aberration and flare problems. Finally, the resist module uses Gaussian convolution model with the trade-off in mind between accuracy of full resist model and speed of Gaussian convolution model. As an application example, an iso-dense bias (ID bias) fitting is implemented for an ArF resist to image sub-100 nm patterns. Simulation results show that the fitting error meets the prediction accuracy target of International Technology Roadmap for Semiconductors 2002. The advanced module-based model using aerial image with measured pupil intensity profile and Gaussian convolution seems to be an effective way for the CD prediction of sub-100 nm patterns.

Paper Details

Date Published: 29 April 2004
PDF: 9 pages
Proc. SPIE 5378, Data Analysis and Modeling for Process Control, (29 April 2004); doi: 10.1117/12.536345
Show Author Affiliations
Jangho Shin, Samsung Electronics Co., Ltd. (South Korea)
Insung Kim, Samsung Electronics Co., Ltd. (South Korea)
Chan Hwang, Samsung Electronics Co., Ltd. (South Korea)
Dong-Woon Park, Samsung Electronics Co., Ltd. (South Korea)
Sang-Gyun Woo, Samsung Electronics Co., Ltd. (South Korea)
Han-Ku Cho, Samsung Electronics Co., Ltd. (South Korea)
Woo-Sung Han, Samsung Electronics Co., Ltd. (South Korea)
Joo-Tae Moon, Samsung Electronics Co., Ltd. (South Korea)


Published in SPIE Proceedings Vol. 5378:
Data Analysis and Modeling for Process Control
Kenneth W. Tobin, Editor(s)

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