Calibration of Physical Resist Models:Methods, Usability, and Predictive Power

摘要

We discuss the methodology of resist model calibration under various aspects and assess the resulting predictiveaccuracy. The study is performed on an extensive OPC data set which includes several thousands of CD values obtainedwith immersion lithography for the 45 nm technology node. We address practical aspects such as speed of calibration vs.size of calibration data set and the role of pattern selection for calibration. In particular, we show that a small subset ofthe data set is sufficient to provide accurate calibration results. However, the overall predictive power can strongly beenhanced if a few critical patterns are additionally included into the calibration data set. Besides, we demonstrate asignificant impact of the illumination source shape (measured vs. nominal top hat) on the resulting model quality. Mostimportantly, it will be shown that calibrated resist models based on a 3D (topographic) mask description perform betterthan resist models based on a 2D (Kirchhoff) mask approximation. Also, we show that a resist model calibrated withone-dimensional (lines & spaces) structures only can successfully predict the printing behavior of two-dimensionalpatterns (end-of-line structures).