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用于光学光刻工艺稳健性的像素化源掩模优化

Pixelated source mask optimization for process robustness in optical lithography.

作者信息

Jia Ningning, Lam Edmund Y

机构信息

Imaging Systems Laboratory, Department of Electrical and Electronic Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong.

出版信息

Opt Express. 2011 Sep 26;19(20):19384-98. doi: 10.1364/OE.19.019384.

Abstract

Optical lithography has enabled the printing of progressively smaller circuit patterns over the years. However, as the feature size shrinks, the lithographic process variation becomes more pronounced. Source-mask optimization (SMO) is a current technology allowing a co-design of the source and the mask for higher resolution imaging. In this paper, we develop a pixelated SMO using inverse imaging, and incorporate the statistical variations explicitly in an optimization framework. Simulation results demonstrate its efficacy in process robustness enhancement.

摘要

多年来,光学光刻技术已能够打印出越来越小的电路图案。然而,随着特征尺寸的缩小,光刻工艺变化变得更加明显。源掩模优化(SMO)是一种当前技术,它允许对源和掩模进行协同设计以实现更高分辨率的成像。在本文中,我们使用逆成像开发了一种像素化的源掩模优化方法,并在优化框架中明确纳入统计变化。仿真结果证明了其在增强工艺稳健性方面的有效性。

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