Mask Optimization based on artificial desired pattern

Fei Peng, Chengqun Gui, Yi Song, Yijiang Shen
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Abstract

As one of the most effective methods to compensate image distortion, inverse lithography technology (ILT) has been widely used in the computational lithography. However, the compensation capability of ILT to wafer image is restricted by the effect of low-pass filtering, and difficult to resolve high frequency signals. In this paper, a new optimization algorithm is investigated and applied to ILT. The high frequency points on the target pattern are characterized, and additional low frequency signals are added at these points to form an artificial desired pattern. The artificial desired pattern will replace the target pattern in the optimization, which is proposed to resolve the impact of high frequency signals. Simulation results demonstrate the superiority of the proposed method, which effectively improves the fidelity of the target pattern.
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基于人工期望模式的掩模优化
逆光刻技术作为一种最有效的补偿图像畸变的方法,在计算光刻中得到了广泛的应用。然而,ILT对晶圆图像的补偿能力受到低通滤波的限制,且难以分辨高频信号。本文研究了一种新的优化算法,并将其应用于ILT。对目标图案上的高频点进行表征,并且在这些点处添加额外的低频信号以形成人工所需图案。为了解决高频信号的影响,在优化过程中采用人工期望方向图代替目标方向图。仿真结果证明了该方法的优越性,有效地提高了目标方向图的保真度。
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