Effective multicutline QUASAR illumination optimization for SRAM and logic

Abstract

Lithographers face many hurdles to achieve the ever-shrinking process design rules (PDRs). Proximity effects are becoming more and more an issue requiring model-based Optical Proximity Correction (OPC), sub-resolution assist features, and properly tuned illumination settings in order to minimize these effects while providing enough contrast to maintain a viable process window. For any type of OPC application to be successful, a fundamental illumination optimization must first be completed. Unfortunately, the once trivial illumination optimization has evolved into a major task for ASIC houses that require a manufacturable process window for isolated logic structures as well as dense SRAM features. Since these features commonly appear on the same reticle, today’s illumination optimization must look at “common” process windows for multiple cutlines that include a variety of different feature types and pitches. This is a daunting task for the current single feature simulators and requires a considerable amount of simulation time, engineering time, and fab confirmation data in order to come up with an optimum illumination setting for such a wide variety of features. An internal Illumination Optimization (ILO) application has greatly simplified this process by allowing the user to optimize an illumination setting by simultaneously maximizing the “combined” DOF (depth of focus) over multiple cutlines (simulation sites). Cutlines can be placed on a variety of structures in an actual design as well as several key pitches. Any number of the cutlines can be constrained to the gds drawn CD (critical dimension) while others can be allowed to “float” with pseudo OPC allowing the co-optimization of the illumination setting for any OPC that may be applied in the final design. The automated illumination optimization is then run using a tuned model. Output data is a suggested illumination setting with supporting data used to formulate the recommendation. This paper will present the multi-cutline ILO process and compare it with the work involved to do the same optimization using a single feature simulator. Examples will be shown where multi-cutline ILO was able to resolve hard annular aberrations while maintaining the DOF.