Paper
28 May 2004 Two-dimensional image-based model calibration for OPC applications
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Abstract
The existing approaches to lithography model generation rely heavily on one-dimensional (1D) Scanning Electron Microscope (SEM) measurements to characterize a two-dimensional (2D) process. Traditional 1-D techniques require measuring an exhaustive test cell matrix containing hundreds of features representing different sizes, shapes, and pitches. Despite the large amount of data collected, there can still be a significant amount of model error present, particularly in 2D structures such as line ends and corners, which do not lend themselves to a well defined CD measurement. This is due to the inadequacy of using a 1D measurement for characterizing 2D features. A new approach to lithography simulation confirms the axiom "a SEM image is worth a thousand CD measurements". Using a set of six or fewer SEM images and fitting a contour-based 2-D simulation to the image during the model derivation, achieves a good 2D predictive capability without sacrificing through pitch predictability. This paper will show the results of using SEM images to tune lithography models on clear and dark field layers and illustrate the accuracy of the models using contour based simulations overlaid with SEM images. This approach to OPC modeling greatly reduces the number of CD measurements required to generate a model and lessens the susceptibility of the model to SEM CD metrology errors, while achieving a very well tuned model. This method works best when the 2-D simulation and calibration are coupled to the algorithms that perform the correction.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kunal N. Taravade, Ebo H. Croffie, and Andrew Jost "Two-dimensional image-based model calibration for OPC applications", Proc. SPIE 5377, Optical Microlithography XVII, (28 May 2004); https://doi.org/10.1117/12.538244
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Cited by 7 scholarly publications.
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KEYWORDS
Optical proximity correction

Scanning electron microscopy

Calibration

Process modeling

Lithography

Critical dimension metrology

Data modeling

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