Scatterometry has been presented as a solution for next generation Critical Dimension (CD) metrology for advanced
lithography scanners [3,9-16]. Scatterometry used in Integrated Metrology (IM) is an entirely different technique for
measuring CD data than the previous CD SEM (Scanning Electron Microscope) method and has benefits beyond those
of the CD SEM including: 1) faster process time, 2) direct integration with the lithography track/scanner link, and 3)
additional data collection such as line profile and stack data to detect non-litho excursions. This paper will describe
technical issues and implemented solutions that allows scatterometry to seamlessly replace the CD
This paper focuses on the following IM spectrometry implementation aspects:
Scatterometry model creation/optimization to control multiple pitch layers and unique structures using standard
scatterometry features and stack properties change control.
Sample plan optimization methodology for extended scanner and track characterization, and excursion prevention
(EP), from additional real-time feedback capabilities, such as: 1) within-field variation, 2) within-wafer and wafer-to-
wafer variation data, 3) scan direction delta, 4) scan uniformity, 5) resist thickness uniformity, and 6) track
Automation system optimization for scatterometry IM extended data and new capabilities as EP and Advanced
Process Control (APC).
Scatterometry vision for Litho Process Control optimization by combining scatterometry overlay and critical
dimension measurement capabilities in one integrated metrology solution for the Litho track/scanner link.
For the newer, faster and more expensive 193nm (and beyond) Litho links, integrated metrology is the way to ensure the
link is producing quality material with high utilization. Scanner/track performance is monitored continuously and
includes previously unavailable field/wafer/track module data. Automatic Process Control is improved due to fast and
extended feedback, and excursions are detected immediately. Scatterometry as a methodology enables new
opportunities for further process improvement when overlay and critical dimension measurement capabilities are
combined in the same tool, integrated with the Litho link.
The quality of an Automated Process Control (APC) depends highly on the amount of relevant measurement data points. The quality of APC for low volume products is lower than high volume products, since there is not enough data to respond to tool parameters drift or incoming variations. In order to improve low volume runners control it is proposed to use high volume runners data to generate feedback for low volume runners. Product to product differences can be minimized by applying bias. This bias does not remain stable due to tool parameters drift or incoming variations. The current paper addresses these issues and reviews different methods for bias control/change if needed. Intel Litho APC is using EWMA time based weighting for parameters like Overlay parameters, Focus and Dose control. The data for each set of feedback list is segmented by several partition variables (tool, operation, etc.) within a defined expiration period. For low volume runners it is possible to widen the partition by adding main runners data with applied bias. Historical data shows possible bias variability following process or tool drifts over time. Different cases of partition biases are reviewed based on Litho parameters examples. Various algorithms for bias control and bias calculation are reviewed. Simulation studies are performed to predict the impact of deploying this strategy in production.