Machine Learning assistant technology to facilitate Fin and 3D memory measurements on SEM and TEM images

J. Baderot; B. Darbon; N. Clement; M. Bryan; S. Martinez; J. Foucher

doi:10.1117/12.2552033

23 March 2020 Machine Learning assistant technology to facilitate Fin and 3D memory measurements on SEM and TEM images

J. Baderot, B. Darbon, N. Clement, M. Bryan, S. Martinez, J. Foucher

Author Affiliations +

Proceedings Volume 11329, Advanced Etch Technology for Nanopatterning IX; 113290X (2020) https://doi.org/10.1117/12.2552033
Event: SPIE Advanced Lithography, 2020, San Jose, California, United States

Abstract

We present a machine learning-based metrology pipeline for electron microscope imagery in the semiconductor industry. The pipeline is targeted to reduce the time spent by Process Engineers during research and development, by automating measurements of features according to their instructions in the form of a “measurement recipe”. Specifically, we present the principles and functionality of tools to measure Fin and 3D Memory structures based on edge finding algorithms, including through direct modelling of the SEM acquisition process to better capture blurred-appearing features.

Citation Download Citation

J. Baderot, B. Darbon, N. Clement, M. Bryan, S. Martinez, and J. Foucher "Machine Learning assistant technology to facilitate Fin and 3D memory measurements on SEM and TEM images", Proc. SPIE 11329, Advanced Etch Technology for Nanopatterning IX, 113290X (23 March 2020); https://doi.org/10.1117/12.2552033

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