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Design systematic weak point discovery optimization

机译:设计系统的弱点发现优化

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Design systematics have posed significant problems for the development of the latest technology nodes, specifically for logic with design rules of 28nm and below. The faster design systematics are identified, the faster the technology can mature into high volume manufacturing. For advanced design rules, the cost of these systematics increases exponentially with time and thus early detection yields high return on investment. In this paper, we report on a 2× increase in killer defect capture rate for PWQ (Process Window Qualification) inspections by revising the inspection layer. In addition, we found that we can also improve the signal-to-noise ratio (SNR) for single line opens (SLOs) for the actual inline process monitor at post-CMP. This experimentally measured SNR for SLOs was compared to a new computational tool to simulate the expected SNR of DOIs (defects of interest) from broadband plasma (BBP) inspection systems. The reported simulation tool was found to match experimental SNR as a function of the input physical defect model. As the physical defect model more closely matched the actual wafer, the closer the prediction was to the measured SNR. This new tool can aid in finding the best optical state for a given DOI and thus enable detection of the smallest design systematic faster than current methods.
机译:设计系统对于最新技术节点的开发提出了重大问题,特别是对于具有28nm及以下设计规则的逻辑。确定的设计系统越快,技术就可以更快地成熟到大批量生产。对于高级设计规则,这些系统的成本会随着时间呈指数增长,因此早期检测会产生高投资回报率。在本文中,我们通过修改检查层报告了PWQ(过程窗口鉴定)检查的致命缺陷捕获率提高了2倍。此外,我们发现,对于CMP后的实际在线过程监控器,我们还可以提高单线开路(SLO)的信噪比(SNR)。将该实验测量的SLO信噪比与新的计算工具进行比较,以模拟宽带等离子体(BBP)检查系统的DOI期望信噪比(感兴趣的缺陷)。发现所报告的仿真工具可以根据输入的物理缺陷模型将实验SNR与之匹配。由于物理缺陷模型与实际晶圆的匹配程度更高,因此预测越接近测量的SNR。这种新工具可以帮助找到给定DOI的最佳光学状态,从而比目前的方法能够更快地系统检测最小的设计。

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