SEM image prediction based on modeling of electron-solid interaction

Toshimasa Kameda; Satoshi Takada; Makoto Suzuki; Toshiyuki Yokosuka; Sergey Borisov; Sergey Babin

doi:10.1117/12.2257661

28 March 2017 SEM image prediction based on modeling of electron-solid interaction

Toshimasa Kameda, Satoshi Takada, Makoto Suzuki, Toshiyuki Yokosuka, Sergey Borisov, Sergey Babin

Proceedings Volume 10145, Metrology, Inspection, and Process Control for Microlithography XXXI; 101451I (2017) https://doi.org/10.1117/12.2257661
Event: SPIE Advanced Lithography, 2017, San Jose, California, United States

Abstract

Monte Carlo-based SEM image simulation can reproduce SEM micrographs by calculating scattering events of primary electrons inside the target materials. By using the simulated SEM images, it is possible to optimize imaging conditions prior to the specimen observation, which could save time for finding suitable observation condition. However, a recent trend of miniaturized and 3-dimentional structures of semiconductor devices, and introduction of various novel materials have created a challenge for such SEM image simulation techniques; that is, more precise and accurate modeling is required. In this paper, we present a quantitatively accurate BSE simulation and a precise parameters setting in voltage contrast simulation, for both to reproduce experimental SEM images accurately. We apply these simulation techniques to optimize the accelerating voltage of SEM for sub-surface imaging, and to analyze a charge distribution on the insulating specimen under the electron irradiation. These applications promise the advancement in developing a new device by preparing inspecting condition in a timely manner.

Conference Presentation

Citation Download Citation

Toshimasa Kameda, Satoshi Takada, Makoto Suzuki, Toshiyuki Yokosuka, Sergey Borisov, and Sergey Babin "SEM image prediction based on modeling of electron-solid interaction", Proc. SPIE 10145, Metrology, Inspection, and Process Control for Microlithography XXXI, 101451I (28 March 2017); https://doi.org/10.1117/12.2257661

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