A Methodology to Estimate Single-Event Effects Induced by Low-Energy Protons

This work explains that the Coulomb elastic process on the nucleus is a major source of single-event effects (SEE) for protons within the energy range of 1–10 MeV. The infinite range of Coulomb interactions implies an exceptionally high recoil probability. This research seeks to extend the investiga...

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Bibliographic Details
Published in:Eng (Basel, Switzerland) Switzerland), 2024-03, Vol.5 (1), p.319-332
Main Authors: Marques, Cleiton, Wrobel, Frédéric, Aguiar, Ygor, Michez, Alain, Boch, Jérôme, Saigné, Frédéric, García Alía, Rubén
Format: Article
Language:English
Subjects:
Atoms & subatomic particles
Charged particles
Coulomb interaction
cross-section
Cross-sections
elastic process
Electronics
Energy
Engineering Sciences
Mathematical analysis
Methodology
Neutrons
Probability
proton
Protons
Radiation
SEU
Silicon
Single Event Effects
Single event upsets
Citations: Items that this one cites
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Summary:This work explains that the Coulomb elastic process on the nucleus is a major source of single-event effects (SEE) for protons within the energy range of 1–10 MeV. The infinite range of Coulomb interactions implies an exceptionally high recoil probability. This research seeks to extend the investigations under which the elastic process becomes significant in the energy deposition process by providing a simplified methodology to evaluate the elastic contribution impact on the reliability of electronics. The goal is to derive a method to provide a simple way to calculate and predict the SEE cross-section. At very low energy, we observe a significant increase in the proton differential cross-section. The use of a direct Monte Carlo approach would mainly trigger low energy recoiling ions, and a very long calculation time would be necessary to observe the tail of the spectrum. In this sense, this work provides a simple methodology to calculate the SEE cross-section. The single-event upset (SEU) cross-section results demonstrate a good agreement with the experimental data in terms of shape and order of magnitude for different technological nodes.
ISSN:2673-4117
2673-4117
DOI:10.3390/eng5010017