Wafer exposure process simulation and optical photomask feature metrology both rely on optical image modeling for accurate results. The best way to gauge the accuracy of an imaging model is to compare the model results with an actual image. Modeling results, however, depend on several input parameters describing the object and imaging system, such as wavelength, illumination and objective NA's, magnification, focus, etc. for the optical system, and topography, complex index of refraction n and k , etc. for the object. Errors in these parameter values can lead to significant differences between the actual image and the modeled image. Because of these parametric uncertainties, one would hope and expect the models to be far more accurate than such a comparison might indicate. An alternative used here is to compare different imaging models with each other. While the parameter nominal values should be chosen to represent real objects and instruments, they will be identical for both models and contribute no uncertainty to the conclusions. Admittedly not a complete or satisfactory answer to the question of image modeling accuracy, such a differential comparison at least places a meaningful number on modeling differences and sets a limit on modeling accuracy.
Proceedings Title: Proceedings of SPIE
Conference Dates: February 26, 2007
Conference Location: San Jose, CA
Conference Title: Metrology, Inspection, and Process Control Conference for Microlithography XXI
Pub Type: Conferences
feature size., measurement uncertainty, Optical image modeling, photomask