Probabilistic process window: a new approach to focus-exposure analysis

Chris A. Mack; Jonathan Yannuzzi; Gian Lorusso; Mohamed Zidan; Danilo De Simone; Ataklti Weldeslassie; Nadia Vandenbroeck; Philippe Foubert; Christophe Beral; Anne-Laure Charley

doi:10.1117/12.2614445

26 May 2022 Probabilistic process window: a new approach to focus-exposure analysis

Chris A. Mack, Jonathan Yannuzzi, Gian Lorusso, Mohamed Zidan, Danilo De Simone, Ataklti Weldeslassie, Nadia Vandenbroeck, Philippe Foubert, Christophe Beral, Anne-Laure Charley

Author Affiliations +

Proceedings Volume 12053, Metrology, Inspection, and Process Control XXXVI; 1205307 (2022) https://doi.org/10.1117/12.2614445
Event: SPIE Advanced Lithography + Patterning, 2022, San Jose, California, United States

Abstract

Background: Focus-exposure process window measurement and analysis is an essential function in lithography, but the current geometric approach suffers from several significant deficiencies. Aim: By clearly identifying the problems with the Geometric Process Window approach, a new process window measurement and analysis method will be proposed to address these problems. Approach: The Probabilistic Process Window proposed here takes metrology uncertainty into account and rigorously calculates the expected fraction of in-spec features based on settings for best dose/focus and presumed random errors in dose and focus. Using the fraction of in-spec features thus calculated, a much more rigorous determination of the trade-off between exposure latitude and depth of focus can be performed. Results: The Probabilistic Process Window approach is demonstrated on focus-exposure data generated from a standard extreme ultraviolet lithography process at three different pitches, showing the value of this method. Conclusions: The new Probabilistic Process Window approach offers clear advantages in accuracy for both depth of focus determination and best dose/focus determination. Consequently, its use is preferred both for process development applications and high-volume manufacturing.

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Citation Download Citation

Chris A. Mack, Jonathan Yannuzzi, Gian Lorusso, Mohamed Zidan, Danilo De Simone, Ataklti Weldeslassie, Nadia Vandenbroeck, Philippe Foubert, Christophe Beral, and Anne-Laure Charley "Probabilistic process window: a new approach to focus-exposure analysis", Proc. SPIE 12053, Metrology, Inspection, and Process Control XXXVI, 1205307 (26 May 2022); https://doi.org/10.1117/12.2614445

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