Will Darwin's law help us to improve our resist models?

Calibration of resist model parameters becomes more and more important in lithography simulation. The general goal of such a calibration procedure is to find parameters and model options which minimize the difference between experimentally measured and simulated data. In this paper a multidimensional downhill simplex method and a genetic algorithm are introduced. We investigate the performance of different modeling options such as the diffusivity of the photogenerated acid and of the quencher base, and different development models. Furthermore, new objective functions are proposed and evaluated: The overlap of process windows between simulated and experimental data and the comparison of linearity curves. The calibration procedures are performed for a 248nm and for a 193nm chemically amplified resist, respectively.