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4 December 2008 An innovative Source-Mask co-Optimization (SMO) method for extending low k1 imaging
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Proceedings Volume 7140, Lithography Asia 2008; 714010 (2008)
Event: SPIE Lithography Asia - Taiwan, 2008, Taipei, Taiwan
The optimization of the source topology and mask design [1,2] is vital to future advanced ArF technology node development. In this study, we report the comparison of an iterative optimization method versus a newly developed simultaneous source-mask optimization approach. In the iterative method, the source is first optimized based on normalized image log slopes (NILS), taking into account the ASML scanner's diffractive optical element (DOE) manufacturability constraints. Assist features (AFs) are placed under the optimized source, and then optical proximity correction (OPC) is performed using the already placed AFs, in the last step the source is re-optimized using the OPC-ed layout with the AFs. The source is then optimized using the layout from the previous stage based on a set of user specified cost function. The new approach first co-optimizes a pixelated freeform source and a continuous transmission gray tone mask based on edge placement error (EPE) based cost function. ASML scanner specific constraints are applied to the optimized source, to match ASML's current and future illuminator capabilities. Next, AF "seeds" are identified from the optimized gray tone mask, which are subsequently co-optimized with the main features to meet the process window and mask error factor requirement. The results show that the new method offers significant process window improvement.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Stephen Hsu, Luoqi Chen, Zhipan Li, Sean Park, Keith Gronlund, Hua-Yu Liu, Neal Callan, Robert Socha, and Steve Hansen "An innovative Source-Mask co-Optimization (SMO) method for extending low k1 imaging", Proc. SPIE 7140, Lithography Asia 2008, 714010 (4 December 2008);


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