Fast Lithographic Mask Optimization Considering Process Variation

摘要

As nanometer technology advances, conventional optical proximity correction (OPC) that minimizes the edge placement error (EPE) at the nominal process condition alone often leads to poor process windows. To improve the mask printability across various process corners, process-window OPC optimizes EPE for multiple process corners, but often suffers long runtime, due to repeated lithographic simulations. This paper presents an efficient process variation (PV)-aware mask optimization framework, namely PVOPC, to simultaneously minimize EPE and PV band with fast convergence. The PVOPC framework includes EPE-sensitivity-driven dynamic fragmentation, PV-aware EPE modeling, and correction with three new EPE-converging techniques and a systematic subresolution-assisted feature insertion algorithm. Experimental results show that our approach efficiently achieves high-quality EPE and PV band results.