Contour-based variability decomposition for stochastic band metrology

Thomas I. Wallow; Jiyou Fu; Jiao Liang; Jen-Shiang Wang; Jimmy Fan; Maxence Delorme; ChangAn Wang; Fahong Li; Vivek Jain; Rui Yuan

doi:10.1117/12.2601587

28 September 2021 Contour-based variability decomposition for stochastic band metrology

Thomas I. Wallow, Jiyou Fu, Jiao Liang, Jen-Shiang Wang, Jimmy Fan, Maxence Delorme, ChangAn Wang, Fahong Li, Vivek Jain, Rui Yuan

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Proceedings Volume 11854, International Conference on Extreme Ultraviolet Lithography 2021; 118540E (2021) https://doi.org/10.1117/12.2601587
Event: SPIE Photomask Technology + EUV Lithography, 2021, Online Only

Abstract

Driving down imaging-induced edge placement error (EPE) is a key enabler of semiconductor technology node scaling1-3. From the 5 nm node forward, stochastic edge placement error (SEPE) is predicted to become the biggest contributor to total edge placement error. Many previous studies have established that LER, LCDU, and similar variability measurements require corrections for metrology artifacts and noise as well as mask variability transfer to more accurately represent wafer-level stochastic variability. In this presentation, we will discuss SEPE band behavior based on a methodology that allows local extraction of SEPE from total measured local variability (LEPU) in a generalized way along 2D contours.

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Thomas I. Wallow, Jiyou Fu, Jiao Liang, Jen-Shiang Wang, Jimmy Fan, Maxence Delorme, ChangAn Wang, Fahong Li, Vivek Jain, and Rui Yuan "Contour-based variability decomposition for stochastic band metrology", Proc. SPIE 11854, International Conference on Extreme Ultraviolet Lithography 2021, 118540E (28 September 2021); https://doi.org/10.1117/12.2601587

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KEYWORDS

Metrology

Stochastic processes

Photomasks

Model-based design

Scanning electron microscopy

Line edge roughness

Optical lithography

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