Scanner-specific separable models for computational lithography

Stefan Hunsche; Xu Xie; Qian Zhao; Hua-Yu Liu; Peter Nikolsky; Anthony Ngai

doi:10.1117/12.801706

17 October 2008 Scanner-specific separable models for computational lithography

Stefan Hunsche, Xu Xie, Qian Zhao, Hua-Yu Liu, Peter Nikolsky, Anthony Ngai

Proceedings Volume 7122, Photomask Technology 2008; 71221V (2008) https://doi.org/10.1117/12.801706
Event: SPIE Photomask Technology, 2008, Monterey, California, United States

Abstract

The usage of conventional OPC models traditionally was confined to the specific process conditions at which the models were. Separable models for computational lithography (CL), including OPC and post-OPC layout verification, allow extrapolation of the calibrated model and accurate prediction at process conditions different from the exact settings used for model calibration. This capability enables significantly reduced turnaround time in early process development, and it opens the way for new applications such as model based process optimization. It relies on sufficiently accurate modeling of litho process components as separate subsystems, in particular mask, scanner optics, and resist process. Inclusion of actual machine parameters of the exposure tool in the optical model can improve model accuracy and predictability, while 'actual machine parameters' may represent either a specific scanner type or an individual exposure tool. We study the impact of machine parameters that can be incorporated in a modern computational litho model, by analyzing their relative effect on predicted CD measurements and extract a ranking in terms of their expected benefit for model separability. An experimental study demonstrates improved model accuracy and separability by inclusion of either scanner-type specific model data or individual machine-specific metrology data in the CL model building process.

Citation Download Citation

Stefan Hunsche, Xu Xie, Qian Zhao, Hua-Yu Liu, Peter Nikolsky, and Anthony Ngai "Scanner-specific separable models for computational lithography", Proc. SPIE 7122, Photomask Technology 2008, 71221V (17 October 2008); https://doi.org/10.1117/12.801706

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