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Source Optimization under Thick Mask Model

机译:厚面模型下的源优化

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Source optimization(SO) is a key method of resolution enhancement technology. However, as the technique node enters 45 nm and below, the influence of thick mask effect has become apparent. The result of source optimization considering the mask as a thin film is inaccurate. In this paper, we propose a source optimization model considering thick mask structure. We establish the theoretical model of source optimization with gradient method and compressive sensing(CS) method. The typical masks of 45nm, 28nm and 22nm were selected for simulation. The optimized source provides better imaging performance, while the simulation speed has been improved by using CS method.
机译:源优化(SO)是分辨率增强技术的关键方法。然而,随着技术节点进入45nm和以下,厚掩模效应的影响变得明显。考虑掩模作为薄膜的源优化结果是不准确的。在本文中,我们提出了考虑厚掩模结构的源优化模型。用梯度法建立源极优化的理论模型及压缩检测(CS)方法。选择45nm,28nm和22nm的典型面部用于模拟。优化的源提供更好的成像性能,而通过使用CS方法已经提高了仿真速度。

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