Bright field imaging based metrology performance enhancement is essential in the quest to meet lithography process control requirements below 65 nm half pitch. Recent work has shown that, in parallel to the lithographic processes themselves, the metrology tools are able to continue to perform despite the fact that the size of the features under test are often below the classical Rayleigh resolution limit of the optical system. Full electromagnetic simulation is a mandatory tool in the investigation and optimization of advanced metrology tool and metrology target architectures. In this paper we report on imaging simulations of overlay marks. We benchmark different simulation platforms and methods, focusing in particular on the challenges associated with bright-field imaging overlay metrology of marks with feature sizes below the resolution limit. In particular, we study the dependence of overlay mark contrast and information content on overlay mark pitch and feature size.
In this publication, the contributors to in-field overlay metrology uncertainty have been parsed and quantified on a back
end process and compared with results from a previous front end study<sup>1</sup>. Particular focus is placed on the unmodeled
systematics, i.e. the components which contribute to residuals in a linear model after removal of random errors. These
are the contributors which are often the most challenging to quantify and are suspected to be significant in the model
residuals. The results show that in both back and front end processes, the unmodeled systematics are the dominant
residual contributor, accounting for 60 to 70% of the variance, even when subsequent exposures are on the same
scanner. A higher order overlay model analysis demonstrates that this element of the residuals can be further dissected
into correctible and non-correctible high order systematics. A preliminary sampling analysis demonstrates a major
opportunity to improve the accuracy of lot dispositioning parameters by transitioning to denser sample plans compared
with standard practices. Field stability is defined as a metric to quantify the field to field variability of the intrafield
In this publication, the contributors to in-field overlay metrology uncertainty have been parsed and quantified in a specific case study. Particular focus is placed on the unmodeled systematics, i.e. the components which contribute to residuals in a linear model after removal of random errors. These are the contributors which are often the most challenging to quantify and are suspected to be significant in the model residuals. The results show that even in a relatively "clean" front end process, the unmodeled systematics are the dominant residual contributor, accounting for 60 to 70% of the variance. Given the above results, new sampling and modeling methods are proposed which have the potential to improve the accuracy of modeled correctibles and lot dispositioning parameters.
The overlay budgets in leading-edge processes are expected to shrink below 20nm within the next 12-24 months. The demand for ever higher accuracies of overlay metrology for the 65nm node and below drive the development and design of new optical metrology solutions. In this work, we present new results as a continuation of the work we have previously reported on an overlay metrology simulation platform, capable of simulating the entire overlay measurement process. The simulation platform is used for modeling both the optical effects of the overlay metrology tool and the target process and design related effects on the overlay metrology performance. Using this simulation platform we have modeled target proximity effects limiting target size reduction, and process variation effects on overlay performance.