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High performance source optimization using a gradient-based method in optical lithography

机译:在光刻中使用基于梯度的方法进行高性能光源优化

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Recently, source and mask optimization (SMO) has been proposed as an effective solution to help extending the life time of conventional 193 nm lithography. However, SMO is very computationally intensive. To mitigate this issue, we propose a highly effective and efficient method for source optimization in this paper. Based on the gray-level pixel based source representation, the gradient of the cost function is calculated to guide optimization to improve the wafer image fidelity and depth of focus (DOF). This method is demonstrated using two mask patterns with critical dimension of 45 nm, including a periodic array of contact holes and an asymmetric mask pattern from an SRAM layout. Comparing with two recently proposed methods, our method can provide greater improvements in image quality and over 10× running speed enhancement. The robustness of our method is verified using several different initial source patterns. Results show that similar final optimized source patterns and image quality have been achieved.
机译:最近,已经提出了源和掩模优化(SMO)作为帮助延长传统193 nm光刻寿命的有效解决方案。但是,SMO的计算量很大。为了减轻这个问题,我们在本文中提出了一种高效且高效的资源优化方法。基于基于灰度像素的源表示,可以计算成本函数的梯度以指导优化,以提高晶圆图像的保真度和景深(DOF)。使用两个临界尺寸为45 nm的掩模图案(包括接触孔的周期性阵列和SRAM布局中的非对称掩模图案)演示了此方法。与两个最近提出的方法相比,我们的方法可以提供更大的图像质量改进和超过10的分辨率-运行速度增强。我们使用几种不同的初始源模式验证了我们方法的鲁棒性。结果表明,已经实现了类似的最终优化光源图案和图像质量。

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