Stochastic defect criticality prediction enabled by physical stochastic modeling and massive metrology

ChangAn Wang; Peigen Cao; Maxence Delorme; Jen-Yi Wuu; Jiyou Fu; Fuming Wang; Bob Lin; Yiqiong Zhao; Yi-Hsing Peng; Yongfa Fan; Mu Feng; Bin Cheng; Jen-Shiang Wang; Mark Simmoms; Stefan Hunsche; Oliver Patterson; Kuo-Feng Pao; Abdalmohsen Elmalk; Kevin Gao; Ruochong Fei; Xuefeng Zeng; Xiaolong Zhang

doi:10.1117/12.2584767

22 February 2021 Stochastic defect criticality prediction enabled by physical stochastic modeling and massive metrology

ChangAn Wang, Peigen Cao, Maxence Delorme, Jen-Yi Wuu, Jiyou Fu, Fuming Wang, Bob Lin, Yiqiong Zhao, Yi-Hsing Peng, Yongfa Fan, Mu Feng, Bin Cheng, Jen-Shiang Wang, Mark Simmoms, Stefan Hunsche, Oliver Patterson, Kuo-Feng Pao, Abdalmohsen Elmalk, Kevin Gao, Ruochong Fei, Xuefeng Zeng, Xiaolong Zhang

Author Affiliations +

Proceedings Volume 11609, Extreme Ultraviolet (EUV) Lithography XII; 1160916 (2021) https://doi.org/10.1117/12.2584767
Event: SPIE Advanced Lithography, 2021, Online Only

Abstract

With the adoption of extreme ultraviolet (EUV) lithography for high volume production in the advanced wafer manufacturing fab, defects resulting from stochastic effects could be one of major yield killers and draw increasing interest from the industry. In this paper, we will present a flow, including stochastic edge placement error (SEPE) model calibration, pattern recognition and hot spot ranking from defect probability, to detect potential hot spot in the chip design. The prediction result shows a good match with the wafer inspection. HMI eP5 massive metrology and contour analysis were used to extract wafer statistical edge placement distribution data.

Conference Presentation

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ChangAn Wang, Peigen Cao, Maxence Delorme, Jen-Yi Wuu, Jiyou Fu, Fuming Wang, Bob Lin, Yiqiong Zhao, Yi-Hsing Peng, Yongfa Fan, Mu Feng, Bin Cheng, Jen-Shiang Wang, Mark Simmoms, Stefan Hunsche, Oliver Patterson, Kuo-Feng Pao, Abdalmohsen Elmalk, Kevin Gao, Ruochong Fei, Xuefeng Zeng, and Xiaolong Zhang "Stochastic defect criticality prediction enabled by physical stochastic modeling and massive metrology", Proc. SPIE 11609, Extreme Ultraviolet (EUV) Lithography XII, 1160916 (22 February 2021); https://doi.org/10.1117/12.2584767

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