Improving model prediction accuracy for ILT with aggressive SRAFs

For semiconductor IC manufacturing at sub-30nm and beyond, aggressive SRAFs are necessary to ensure sufficient process window and yield. Models used for full chip Inverse Lithography Technology (ILT) or OPC with aggressive SRAFs must predict both CDs and sidelobes accurately. Empirical models are traditionally designed to fit SEMmeasured CDs, but may not extrapolate accurately enough for patterns not included in their calibration. This is particularly important when using aggressive SRAFs, because adjusting an empirical parameter to improve fit to CDSEM measurements of calibration patterns may worsen the model's ability to predict sidelobes reliably. Proper choice of the physical phenomena to include in the model can improve its ability to predict sidelobes as well as CDs of critical patterns on real design layouts. In the work presented here, we examine the effects of modeling certain chemical processes in resist. We compare how a model used for ILT fits SEM CD measurements and predicts sidelobes for patterns with aggressive SRAFs, with and without these physically-based modeling features. In addition to statistics from fits to the calibration data, the comparison includes hot-spot checks performed with independent OPC verification software, and SEM measurements of on-chip CD variation using masks created with ILT.