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10 April 2024 Process incoming control for advanced EUV overlay strategy enabling mass production of GAA nanosheet
SungWoon Uh, Dong-Min Kim, Dooho Park, Jae Hyoung Kim, Sangil Son, Insung kim
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Proceedings Volume PC12953, Optical and EUV Nanolithography XXXVII; PC129530N (2024) https://doi.org/10.1117/12.3010035
Event: SPIE Advanced Lithography + Patterning, 2024, San Jose, California, United States
Abstract
To ensure successful mass production for GAA MBCFET structures and beyond, EUV overlay technology has advanced to withstand extreme process conditions. Commonly used method for its effectiveness was using overlay feedforward strategy to compensate upcoming critical layers such as ‘N+1’, or ‘N+2’ layer with current layer ‘N’ assuming the applied layers have kindred stack properties with identical overlay targets. Overlay feedforward strategy has been developed internally in great sophistication to significantly enhance on product overlay(OPO) proven also in mass production phase. However, it has been recognized that using aforementioned strategy to specific products rooting from GAA MBCFET structure may not be as beneficial as anticipated. In this paper, we would like to present the source of this strange phenomenon largely due to wafer warpage, in which we provide comprehensive solutions to measure, contain and permanently eradicate the originating in-coming process. After implementation of the authors' solution, overlay feedforward strategy demonstrated to be efficacious even for highly biased process excursions.
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(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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SungWoon Uh, Dong-Min Kim, Dooho Park, Jae Hyoung Kim, Sangil Son, and Insung kim "Process incoming control for advanced EUV overlay strategy enabling mass production of GAA nanosheet", Proc. SPIE PC12953, Optical and EUV Nanolithography XXXVII, PC129530N (10 April 2024); https://doi.org/10.1117/12.3010035
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KEYWORDS
Extreme ultraviolet
Semiconducting wafers
Logic
Optical alignment
Overlay metrology
Mathematical optimization
Modeling
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