Stochastic simulation of resist linewidth roughness and critical dimension uniformity for optical lithography

Stewart A. Robertson; John J. Biafore; Mark D. Smith; Michael Reilly; Jerome Wandell

doi:10.1117/1.3517090

1 October 2010 Stochastic simulation of resist linewidth roughness and critical dimension uniformity for optical lithography

Stewart A. Robertson, John J. Biafore, Mark D. Smith, Michael Reilly, Jerome Wandell

Author Affiliations +

Journal of Micro/Nanolithography, MEMS, and MOEMS, Vol. 9, Issue 4, 041212 (October 2010). https://doi.org/10.1117/1.3517090

Abstract

The physical processes that underpin a recently developed commercial stochastic resist model are introduced and the model details discussed. The model is calibrated to experimental data for a commercially available immersion chemically amplified photoresist using basic physical information about the resist and an iterative fitting procedure. This data comprises CD (critical dimension) and LWR (linewidth roughness) measurements through focus and exposure for three separate line-type features on varying pitches: dense, semidense, and isolated. A root mean square error (RMSE) of 2.0 nm is observed between the calibrated model and the experimental CD data. The ability of the calibrated model to predict experimentally observed CD uniformity distributions is tested for a variety of 1-D and 2-D patterns under fixed focus and exposure conditions. The subnanometer RMSE obtained between experiment and simulation suggests that the calibrated stochastic model has excellent predictive power for a variety of applications.

©(2010) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

Stewart A. Robertson, John J. Biafore, Mark D. Smith, Michael Reilly, and Jerome Wandell "Stochastic simulation of resist linewidth roughness and critical dimension uniformity for optical lithography," Journal of Micro/Nanolithography, MEMS, and MOEMS 9(4), 041212 (1 October 2010). https://doi.org/10.1117/1.3517090

Published: 1 October 2010

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