Model-based insertion and optimization of assist features with application to contact layers

摘要

To shorten the turn around time and reduce the amount of effort for SRAF insertion and optimization on any arbitrary layout, a new model-based SRAF insertion and optimization flow is developed. It is based on the pixel-based mask optimization technique to find the optimal mask shapes that result in the best image contrast. The contrast-optimized mask is decomposed into main features and assist features. The decomposed assist features are then run through a simplification process for shot count reduction to improve mask writing throughput. Model-based Optical Proximity Correction (OPC) is applied finally to achieve required pattern fidelity for the current technology. In this flow, main features and assist features are allowed to be optimized simultaneously such that the effect of SRAF optimization and Optical Proximity Correction (OPC) are achieved. Since the objective of the mask optimization is the image fidelity, and there is no light coming through assist features (in dark field case), the assist features were ensured not to print even with high dose. The results on 65nm/contact layer showed this approach greatly reduced the total time and effort required for SRAF placement optimization compared to rule-based method, with better lithographic performance for various layout types when compared to rule-based approach.