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12 November 2015 Optimizing hybrid metrology: rigorous implementation of Bayesian and combined regression
Mark-Alexander Henn, Richard M. Silver, John S. Villarrubia, Nien Fan Zhang, Hui Zhou, Bryan M. Barnes, Bin Ming, András E. Vladár
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Journal of Micro/Nanolithography, MEMS, and MOEMS, Vol. 14, Issue 4, 044001 (November 2015). https://doi.org/10.1117/1.JMM.14.4.044001
Abstract
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 three-dimensional (3-D) structures but also a more realistic estimation of the corresponding uncertainties. Recent developments at the National Institute of Standards and Technology feature the combination of optical critical dimension measurements and scanning electron microscope results. The hybrid methodology offers the potential to make measurements of essential 3-D attributes that may not be feasible otherwise. 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.
CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
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Mark-Alexander Henn, Richard M. Silver, John S. Villarrubia, Nien Fan Zhang, Hui Zhou, Bryan M. Barnes, Bin Ming, and András E. Vladár "Optimizing hybrid metrology: rigorous implementation of Bayesian and combined regression," Journal of Micro/Nanolithography, MEMS, and MOEMS 14(4), 044001 (12 November 2015). https://doi.org/10.1117/1.JMM.14.4.044001
Published: 12 November 2015
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Cited by 12 scholarly publications and 5 patents.
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KEYWORDS
Scanning electron microscopy
Metrology
Error analysis
Data modeling
Standards development
3D metrology
Indium arsenide
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