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Publication Citation: Optimizing Hybrid Metrology through a Consistent Multi-Tool Parameter Set and Uncertainty Model

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Author(s): Richard M. Silver; Bryan M. Barnes; Nien F. Zhang; Hui H. Zhou; Andras Vladar; John S. Villarrubia; Regis J. Kline; Daniel F. Sunday; Alok Vaid;
Title: Optimizing Hybrid Metrology through a Consistent Multi-Tool Parameter Set and Uncertainty Model
Published: April 14, 2014
Abstract: There has been significant interest in hybrid metrology as a novel method for reducing overall measurement uncertainty and optimizing measurement throughput (speed) through rigorous combinations of two or more different measurement techniques into a single result. This approach is essential for advanced 3-D metrology when performing model-based critical dimension measurements. However, a number of fundamental challenges present themselves with regard to consistent noise and measurement uncertainty models across hardware platforms, and the need for a standardized set of model parameters. This is of paramount concern when the various techniques have substantially different models and underlying physics. In this presentation we will work through realistic examples using SEM, CDAFM and Optical CD methods applied to sub-20 nm dense feature sets. We will show reduced measurement uncertainties using hybrid metrology on 15 nm CD features and evaluate approaches to adapt quantitative hybrid metrology into a high volume manufacturing environment.
Conference: Metrology, Inspection, and Process Control for Microlithography
Proceedings: Proceedings of the SPIE
Volume: 9050
Pages: 8 pp.
Location: San Jose, CA
Dates: February 23-27, 2014
Keywords: optical metrology; electromagnetic simulation; evaluate sensitivities and uncertainties; phase sensitive measurements; through-focus three-dimensional field
Research Areas: Dimensional Metrology, Statistics, Critical Dimension and Overlay Metrology, Characterization, Nanometrology, and Nanoscale Measurements
DOI: http://dx.doi.org/10.1117/12.2048225  (Note: May link to a non-U.S. Government webpage)
PDF version: PDF Document Click here to retrieve PDF version of paper (889KB)