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Modeling of MOSFETs Altered by Ionizing Radiation Using Artificial Neural Networks

  • General and Applied Physics
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Abstract

The ionizing radiation absorbed by semiconductor devices can change their properties by modifying their electrical parameters and, in the case of memories, it can modify the information contained in these components. Thus, the ability to predict how ionizing radiation affects electronic circuits becomes especially important in environments where there is the possibility of prolonged exposure to intense radiation, such as satellites, nuclear reactors, particle accelerators, and medical equipment, among others. In this sense, this paper proposes a methodology to reproduce the behavior of TID (total ionizing dose) damaged MOSFET transistors using the fully connected artificial neural networks, taking advantage of its universal estimator characteristics to oversample the dataset’s pattern and give it a better resolution. The dataset complexity requires a specific architecture choice, being necessary the use of two neural network models to separately reproduce the MOSFET electric current magnitude order and its curve shape. Results show a very good capability to reproduce and interpolate the MOSFET behavior, which makes the proposed method a promising way to simulate circuits based on MOSFETs that are exposed to ionizing radiation.

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Data Availability

Dataset is available on the Mendeley Data platform [19].

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Acknowledgements

This work dataset was obtained the Laboratory of Ionizing Radiation Effects (LERI) of FEI University Center.

Funding

The authors received financial support from the Brazilian funding agencies FAPESP (Project No. 2022/02331-3), CNPq and PIBIFSP Guarulhos.

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Authors and Affiliations

  1. Federal Institute of Education, Science and Technology of São Paulo - Campus Guarulhos, 3501 Salgado Filho ave, Guarulhos, 07115-000, São Paulo, Brazil

    Lucas S. A. dos Santos & Dennis L. Toufen

  2. Institute of Physics, University of São Paulo, 1371 Matão st, São Paulo, 05508-090, São Paulo, Brazil

    Paula R. P. Allegro

  3. Federal University of São Carlos, Rod Washington Luís km 235, São Carlos, 13565-905, São Paulo, Brazil

    Paula R. P. Allegro

  4. FEI University Center, 3972-B Humberto de Alencar Castelo Branco ave, São Bernardo do Campo, 09850-901, São Paulo, Brazil

    Marcilei A. Guazzelli, Ana L. Guidi, Paulo R. G. Junior & Alexis C. Vilas Bôas

  5. Federal Institute of Education, Science and Technology of São Paulo - Campus São Paulo, 625 Pedro Vicente st, São Paulo, 01109-010, São Paulo, Brazil

    Valdison S. A. Junior

Authors
  1. Lucas S. A. dos Santos
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  2. Paula R. P. Allegro
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  3. Marcilei A. Guazzelli
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  4. Ana L. Guidi
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  5. Paulo R. G. Junior
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  6. Valdison S. A. Junior
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  7. Dennis L. Toufen
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  8. Alexis C. Vilas Bôas
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Contributions

Lucas S. A. dos Santos: conceptualization, methodology, software, writing original draft. Paula R.P. Allegro: conceptualization, methodology, writing review. Marcilei A. Guazzelli: experimental dataset measurements, writing review. Ana L. Guidi: experimental dataset measurements, writing review. Paulo R. G. Junior: experimental dataset measurements, writing review. Valdison S. A. Junior: methodology, writing review. Dennis L. Toufen: conceptualization, methodology, software, writing original draft. Alexis C. Vilas Bôas: experimental dataset measurements, writing review.

Corresponding author

Correspondence to Dennis L. Toufen.

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dos Santos, L.S.A., Allegro, P.R.P., Guazzelli, M.A. et al. Modeling of MOSFETs Altered by Ionizing Radiation Using Artificial Neural Networks. Braz J Phys 53, 101 (2023). https://doi.org/10.1007/s13538-023-01307-8

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