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Assessment of variability and defectivity by high-throughput e-beam metrology for prediction of patterning defect probabilities

机译:高通量电子束计量对图案化缺陷概率预测的高吞吐量电子束计量评估

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We present an experimental study of pattern variability and defectivity, based on a large data set with more than 112 million SEM measurements from an HMI high-throughput e-beam tool. The test case is a 10nm node SRAM via array patterned with a DUV immersion LELE process, where we see a variation in mean size and litho sensitivities between different unique via patterns that leads to a seemingly qualitative differences in defectivity. The large available data volume enables further analysis to reliably distinguish global and local CDU variations, including a breakdown into local systematics and stochastics. A closer inspection of the tail end of the distributions and estimation of defect probabilities concludes that there is a common defect mechanism and defect threshold despite the observed differences of specific pattern characteristics. We expect that the analysis methodology can be applied for defect probability modeling as well as general process qualification in the future.
机译:我们基于来自HMI高吞吐量电子束工具的大于11200万次SEM测量的大数据集,展示了模式变异性和缺陷的实验研究。测试用例是通过DUV浸没式LELE工艺图案化的10nm节点SRAM,其中我们看到了在不同独特的通过图案之间的平均尺寸和立力敏感性的变化,这导致了缺陷看似的差异差异。大型可用数据量使得进一步分析可靠地区分全局和本地CDU变化,包括置于本地系统性和随机的崩溃。仔细检查分布的尾端和缺陷概率的估计的结论是,尽管观察到特定模式特征的差异,存在常见的缺陷机制​​和缺陷阈值。我们预计分析方法可以应用于未来的缺陷概率建模以及一般过程资格。

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