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

机译:通过高通量电子束计量学评估变异性和缺陷性,以预测构图缺陷概率

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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HMI高通量电子束工具进行的超过1.12亿个SEM测量的大型数据集,对图案可变性和缺陷性进行了实验研究。测试用例是通过采用DUV浸入式LELE工艺进行图案化的阵列的10nm节点SRAM,在该阵列中,我们看到了不同唯一通孔图案之间平均尺寸和光刻灵敏度的变化,从而导致缺陷率看似定性的差异。庞大的可用数据量使您能够进行进一步分析,以可靠地区分全局和本地CDU的变化,包括对本地系统和随机数据的细分。仔细观察分布的尾端并估计缺陷概率,可以得出结论,尽管观察到了特定图案特征的差异,但存在共同的缺陷机制​​和缺陷阈值。我们希望该分析方法可以在将来用于缺陷概率建模以及一般过程认证。

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