Demonstrating the benefits of source-mask optimization and enabling technologies through experiment and simulations

Computational lithography: Exhausting the resolution limits of 193-nm projection lithography systems

“…125 When the problem formulation takes into account the socalled "lithographic paradigm," in which the quality of a lithographic solution is considered to be no better than that of the first circuit element whose printing fails (so that the solution quality is gated by the feature having the smallest process window in the face of control fluctuations), one generally finds that the optimization objective and active constraints are governed at the solution by only a small set of image features and associated mask variables (as well as by the source variables, which are few in number). 136,141 Although the critical clips that do bind the solution cannot be rigorously identified in advance, this opens up a strategy in which a judiciously chosen set of mask samples (very small in area compared to the full layout) are used to design the source, with the remainder of the mask layout then being designed by relatively fast fixedsource methods.…”

“…121,131,134,136,[141][142][143][144] Experimental efforts have also shown that these enablers have allowed resolution enhancement technique (RET) solutions to keep pushing the limits of the 193i system. Here the computational results focus around SMO solutions that have been developed for a number of critical layers at 22 nm and beyond.…”

“…To achieve this, based on the performance limitations of intensive Fig. 136,141 This is done because running a full chip optimization in SMO is still computationally or time bound (a point covered in Sec. Approaches in the industry do vary, but typically take on something similar to this flow.…”

“…7 shows a typical flow that is used to build a technology solution based on SMO. 141 This includes all the aspects reviewed in Sec. 136,151,152 The input design first goes through processing to find a limited range of clips that are important to the optimization.…”

Total source mask optimization: high-capacity, resist modeling, and production-ready mask solution

“…As described in recent publications [2][3][4], SMO provides intensively optimized wave distributions that illuminate both the mask and the wafer, exploring all possible benefits from the available degrees of freedom in the band-limited exposure process. Conventional SMO algorithms rely mainly on joint optimizations to be the main block for providing non-intuitive source profiles and mask solutions, which leads to improved lithographic performance.…”