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Optimizing Hybrid Metrology: Rigorous Implementation of Bayesian and Combined Regression.
Journal of Micro/Nanopatterning, Materials, and Metrology ( IF 1.5 ) Pub Date : 2015-12-19 , DOI: 10.1117/1.jmm.14.4.044001
Mark-Alexander Henn 1 , Richard M Silver 1 , John S Villarrubia 1 , Nien Fan Zhang 2 , Hui Zhou 1 , Bryan M Barnes 1 , Bin Ming 1 , András E Vladár 1
Affiliation  

Hybrid metrology, e.g., the combination of several measurement techniques to determine critical dimensions, is an increasingly important approach to meet the needs of the semiconductor industry. A proper use of hybrid metrology may yield not only more reliable estimates for the quantitative characterization of 3-D structures but also a more realistic estimation of the corresponding uncertainties. Recent developments at the National Institute of Standards and Technology (NIST) feature the combination of optical critical dimension (OCD) measurements and scanning electron microscope (SEM) results. The hybrid methodology offers the potential to make measurements of essential 3-D attributes that may not be otherwise feasible. However, combining techniques gives rise to essential challenges in error analysis and comparing results from different instrument models, especially the effect of systematic and highly correlated errors in the measurement on the χ2 function that is minimized. Both hypothetical examples and measurement data are used to illustrate solutions to these challenges.

中文翻译:

优化混合计量:贝叶斯和组合回归的严格实现。

混合计量学(例如,几种测量技术的组合来确定关键尺寸)是满足半导体行业需求的一种越来越重要的方法。正确使用混合计量不仅可以得出用于3D结构定量表征的更可靠的估计,而且可以得出相应不确定性的更现实的估计。美国国家标准技术研究院(NIST)的最新发展是光学临界尺寸(OCD)测量和扫描电子显微镜(SEM)结果的结合。混合方法提供了测量基本3-D属性的潜力,而这在其他情况下是不可行的。然而,组合技术给误差分析和比较来自不同仪器模型的结果带来了重大挑战,尤其是在最小化的χ2函数上,系统性和高度相关的误差在测量中的影响。假设的示例和测量数据均用于说明这些挑战的解决方案。
更新日期:2019-11-01
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