Prediction of EUV stochastic microbridge probabilities by lithography simulations

Abstract

Stochastic defects are a concern in the lithographic processes used for semiconductor manufacturing, particularly for advanced node extreme ultraviolet lithographic processes. Experimentally determining the defect probability for a lithographic process is extremely time-consuming, requiring expensive metrology equipment and generally limited to simple patterns. Defect probability simulations can be beneficial from time and cost perspective and furthermore should be extensible to more complex patterns. As such, being able to accurately predict the defect probability using lithography simulations would be a valuable complementary option. We show the results of a fast simulation-based methodology for predicting defect probabilities based on a continuum lithographic model calibrated to experimental data. The simulation based-results are compared to experimental microbridge defect probability data where we show a good correlation between the two.