Process variability band analysis for quantitative optimization of exposure conditions

John L. Sturtevant; Srividya Jayaram; Le Hong

doi:10.1117/12.816501

12 March 2009 Process variability band analysis for quantitative optimization of exposure conditions

John L. Sturtevant, Srividya Jayaram, Le Hong

Author Affiliations +

Proceedings Volume 7275, Design for Manufacturability through Design-Process Integration III; 72751Q (2009) https://doi.org/10.1117/12.816501
Event: SPIE Advanced Lithography, 2009, San Jose, California, United States

Abstract

One of the critical challenges facing lithographers is how to optimize the numerical aperture (NA) and illumination source intensity and polarization distribution to deliver the maximum process window for a given design in manufacturing. While the maximum NA has topped out at 1.35, the available illuminator options continue to increase, including the eventual possibility of dynamically programmable pixelized illumination to deliver nearly any imaginable source shape profile. New approaches to leverage this capability and simultaneously optimize the source and mask shapes (SMO) on a per-design basis are actively being developed. Even with the available "standard" illumination source primitive shapes, however, there exist a huge range of possible choices available to the lithographer. In addition, there are multiple conceivable cost functions which could be considered when determining which illumination to utilize for a specified technology and mask layer. These are related to the primary lithographic variables of exposure dose, focus, and mask size, and include depth of focus (DOF), exposure latitude (EL), normalized image log slope (NILS), image contrast, and mask error enhancement factor (MEEF). The net result can be a very large quantity of simulation data which can prove difficult to assess, and often manifest different extrema, depending upon which cost function is emphasized. We report here on the use of several analysis methods, including process variability bands, as convenient metrics to optimize full-chip post-OPC CD control in conjunction with illumination optimization tooling. The result is a more thorough and versatile statistical analysis capability than what has traditionally been possible with a CD cutline approach. The method is analogous to conventional process window CD plots used in lithography for many years.

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John L. Sturtevant, Srividya Jayaram, and Le Hong "Process variability band analysis for quantitative optimization of exposure conditions", Proc. SPIE 7275, Design for Manufacturability through Design-Process Integration III, 72751Q (12 March 2009); https://doi.org/10.1117/12.816501

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