To achieve the ultimate resolution and process control from an optical (193i 1.35NA) scanner system, it is desirable to be able to exploit both source and mask degrees of freedom to create the imaging conditions for any given set of patterns that comprise a photomask. For the source it has been possible to create an illumination system that allows for almost no restrictions in the location and intensity of source points in the illumination plane . For the mask, it has been harder to approach the ideal continuous phase and transmission mask that theoretically would have the best imaging performance. Mask blanks and processing requirements have limited us to binary (1 and 0 amplitude, or 1 and -0.25 amplitude (6% attenuated PSM)) or Alternating PSM (1, 0 and -1 amplitude) solutions. Furthermore, mask writing (and OPC algorithms) have limited us to Manhattan layouts for full chip logic solutions. Recent developments in the areas of mask design and newly developed Multi-Beam Mask Writers (MBMW) have removed the mask limitation to Manhattan geometries . In this paper we consider some of the manufacturing challenges for these curvilinear masks.
At the 20nm technology node, it is challenging for simple resolution enhancements techniques (RET) to achieve sufficient process margin due to significant coupling effects for dense features. Advanced computational lithography techniques including Source Mask Optimization (SMO), thick mask modeling (M3D), Model Based Sub Resolution Assist Features (MB-SRAF) and Process Window Solver (PW Solver) methods are now required in the mask correction processes to achieve optimal lithographic goals. An OPC solution must not only converge to a nominal condition with high fidelity, but also provide this fidelity over an acceptable process window condition. The solution must also be sufficiently robust to account for potential scanner or OPC model tuning. In many cases, it is observed that with even a small change in OPC parameters, the mask correction could have a big change, therefore making OPC optimization quite challenging. On top of this, different patterns may have significantly different optimum source maps and different optimum OPC solution paths. Consequently, the need for finding a globally optimal OPC solution becomes important. In this work, we introduce a holistic solution including source and mask optimization (SMO), MB-SRAF, conventional OPC and Co-Optimization OPC, in which each technique plays a unique role in process window enhancement: SMO optimizes the source to find the best source solution for all critical patterns; Co-Optimization provides the optimized location and size of scattering bars and guides the optimized OPC solution; MB-SRAF and MB-OPC then utilizes all information from advanced solvers and performs a globally optimized production solution.