Poster + Paper
27 April 2023 Scatterometry and machine learning for in-die overlay solution
Author Affiliations +
Conference Poster
Abstract
Advanced technology nodes require tighter lithography overlay specifications with higher throughput and lower cost of ownership. Today, with the accelerating complexity of nanoelectronics for memory applications, an increased emphasis is placed on controlling the on-product overlay (OPO) budget. Consequently, accurate in-die overlay measurements play a critical role after the etching process (ACI) for which it can better reflect the actual product overlay. Here we propose a solution with the combined spectroscopic full Mueller matrix, measured with the KLA next-generation SpectraShape™ dimensional metrology system and a physics-based machine learning algorithm. Both real spectra collected by the SpectraShape and theoretical spectra generated from the scatterometry model are trained against their corresponding ground truth reference and synthetic reference data respectively to predict overlay. Theoretical and experimental results show that the Mueller elements are sensitive to very small changes in the overlay parameters which can enable inline, high-throughput overlay metrology. Accuracy, robustness, and precision on massive datasets using design of experiments (DOE) wafers are presented and discussed. Moreover, the measurement reliability is assessed with a key performance indicator (KPI), designed to flag a process excursion in a high-volume manufacturing (HVM) environment. Good agreement is observed between the KPI and the actual model accuracy.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
June Yeh and Houssam Chouaib "Scatterometry and machine learning for in-die overlay solution", Proc. SPIE 12496, Metrology, Inspection, and Process Control XXXVII, 124962R (27 April 2023); https://doi.org/10.1117/12.2657946
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KEYWORDS
Overlay metrology

Education and training

Machine learning

Semiconducting wafers

Metrology

Scatterometry

High volume manufacturing

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