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dc.contributor.authorCecchetto, Matteo
dc.contributor.authorAlia, Ruben Garcia
dc.contributor.authorWrobel, Frederic
dc.contributor.authorCoronetti, Andrea
dc.contributor.authorBilko, Kacper
dc.contributor.authorLucsanyi, David
dc.contributor.authorFiore, Salvatore
dc.contributor.authorBazzano, Giulia
dc.contributor.authorPirovano, Elisa
dc.contributor.authorNolte, Ralf
dc.date.accessioned2021-03-11T10:04:33Z
dc.date.available2021-03-11T10:04:33Z
dc.date.issued2021
dc.identifier.citationCecchetto, M., Alia, R. G., Wrobel, F., Coronetti, A., Bilko, K., Lucsanyi, D., Fiore, S., Bazzano, G., Pirovano, E., & Nolte, R. (2021). 0.1-10 MeV Neutron Soft Error Rate in Accelerator and Atmospheric Environments. <i>IEEE Transactions on Nuclear Science</i>, <i>68</i>(5), 873-883. <a href="https://doi.org/10.1109/TNS.2021.3064666" target="_blank">https://doi.org/10.1109/TNS.2021.3064666</a>
dc.identifier.otherCONVID_51870677
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/74591
dc.description.abstractNeutrons with energies between 0.1-10 MeV can significantly impact the Soft Error Rate (SER) in SRAMs manufactured in scaled technologies, with respect to high-energy neutrons. Their contribution is evaluated in accelerator, ground level and avionic (12 km of altitude) environments. Experimental cross sections were measured with monoenergetic neutrons from 144 keV to 17 MeV, and results benchmarked with Monte Carlo simulations. It was found that even 144 keV neutrons can induce upsets due to elastic scattering. Moreover, neutrons in the 0.1-10 MeV energy range can induce more than 60% of the overall upset rate in accelerator applications, while their contribution can exceed 18% in avionics. The SER due to neutrons below 3 MeV, whose contribution has always been considered negligible, is found to be up to 44% of the total upsets in accelerator environments. These results have strong Radiation Hardness Assurance (RHA) implications for those environments with high fluxes of neutrons in the 0.1-10 MeV energy range.en
dc.format.mimetypeapplication/pdf
dc.languageeng
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.ispartofseriesIEEE Transactions on Nuclear Science
dc.rightsCC BY 4.0
dc.subject.otherneutrons
dc.subject.otherprotons
dc.subject.otherparticle beams
dc.subject.othermesons
dc.subject.otherlife estimation
dc.subject.othersensitivity
dc.subject.otheraerospace electronics
dc.title0.1-10 MeV Neutron Soft Error Rate in Accelerator and Atmospheric Environments
dc.typearticle
dc.identifier.urnURN:NBN:fi:jyu-202103111939
dc.contributor.laitosFysiikan laitosfi
dc.contributor.laitosDepartment of Physicsen
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.type.coarhttp://purl.org/coar/resource_type/c_2df8fbb1
dc.description.reviewstatuspeerReviewed
dc.format.pagerange873-883
dc.relation.issn0018-9499
dc.relation.numberinseries5
dc.relation.volume68
dc.type.versionpublishedVersion
dc.rights.copyright© Authors, 2021
dc.rights.accesslevelopenAccessfi
dc.relation.grantnumber721624
dc.relation.grantnumber721624
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/H2020/721624/EU//RADSAGA
dc.subject.ysoprotonit
dc.subject.ysoneutronit
dc.subject.ysokäyttömuistit
dc.subject.ysoavaruustekniikka
dc.subject.ysosäteilyfysiikka
dc.subject.ysoMonte Carlo -menetelmät
dc.subject.ysoelektroniikkakomponentit
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p12428
jyx.subject.urihttp://www.yso.fi/onto/yso/p15394
jyx.subject.urihttp://www.yso.fi/onto/yso/p15250
jyx.subject.urihttp://www.yso.fi/onto/yso/p17376
jyx.subject.urihttp://www.yso.fi/onto/yso/p11069
jyx.subject.urihttp://www.yso.fi/onto/yso/p6361
jyx.subject.urihttp://www.yso.fi/onto/yso/p9652
dc.rights.urlhttps://creativecommons.org/licenses/by/4.0/
dc.relation.doi10.1109/TNS.2021.3064666
dc.relation.funderEuropean Commissionen
dc.relation.funderEuroopan komissiofi
jyx.fundingprogramMSCA Innovative Training Networks (ITN)en
jyx.fundingprogramMSCA Innovative Training Networks (ITN)fi
jyx.fundinginformationThe KVI test campaign has received funding from the European Union’s Horizon 2020 research and innovation programme under the MSC agreement no. 721624.
dc.type.okmA1


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