Fast generation of SEM images including charging effect by neural network

H. Du; T. Yokosuka; Y. Iwabuchi; M. Suzuki; Y. Aoki

doi:10.1117/12.2613955

26 May 2022 Fast generation of SEM images including charging effect by neural network

H. Du, T. Yokosuka, Y. Iwabuchi, M. Suzuki, Y. Aoki

Proceedings Volume 12053, Metrology, Inspection, and Process Control XXXVI; 120531Y (2022) https://doi.org/10.1117/12.2613955
Event: SPIE Advanced Lithography + Patterning, 2022, San Jose, California, United States

Conference Poster

Abstract

In scanning electron microscope (SEM) image simulation, it is necessary to consider the charging of electron beam irradiation, which can be computationally intensive. Therefore, we have developed a neural network-based algorithm to generate SEM images by inputting the shape and material properties of semiconductor devices, after which various preprocesses are applied to the physical parameters to improve the accuracy. The contrast and visibility of the generated images are then compared with simulation results that are not included in the training dataset. As a preliminary result, we found that the physical parameters that affect charging, such as the relative permittivity and electron mobility of the material, can be predicted. The effect of acceptance is also considered in the training process to reproduce the changes in image quality depending on the type and arrangement of detectors.

Citation Download Citation

H. Du, T. Yokosuka, Y. Iwabuchi, M. Suzuki, and Y. Aoki "Fast generation of SEM images including charging effect by neural network", Proc. SPIE 12053, Metrology, Inspection, and Process Control XXXVI, 120531Y (26 May 2022); https://doi.org/10.1117/12.2613955

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