A commercial 65nm CMOS technology for space applications: Heavy ion, proton and gamma test results and modeling

Gasiot,; Uznanski,; Daveau,; Torras-Flaquer,; Clerc,; Harboe-Sorensen,

doi:10.1109/radecs.2009.5994696

Cited by 11 publications

(3 citation statements)

References 18 publications

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“…where σ(LET) is the saturation flipping cross-section, i.e., the value in the Weibull curve where the flipping cross-section no longer increases with LET, LET th is the LET threshold, and a and b are shape fitting parameters. The saturation cross-section values calculated in this paper are roughly on the order of 10 −10 to 10 −8 cm 2 , which is consistent with the research results from the relevant literature [23]. This, to some extent, confirms the accuracy of the method proposed in this paper.…”

Section: Automated Prediction Process For Radiation-induced Vulnerabi...supporting

confidence: 91%

A Method for Automatically Predicting the Radiation-Induced Vulnerability of Unit Integrated Circuits

Dong,

Lu,

Yang

et al. 2024

Micromachines

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With the rapid development of semiconductor technology, the reduction in device operating voltage and threshold voltage has made integrated circuits more susceptible to the effects of particle radiation. Moreover, as process sizes decrease, the impact of charge sharing effects becomes increasingly severe, with soft errors caused by single event effects becoming one of the main causes of circuit failures. Therefore, the study of sensitivity evaluation methods for integrated circuits is of great significance for promoting the optimization of integrated circuit design, improving single event effect experimental methods, and enhancing the irradiation reliability of integrated circuits. In this paper, we first established a device model for the charge sharing effect and simulated it under reasonable conditions. Based on the simulation results, we then built a neural network model to predict the charge amounts in primary and secondary devices. We also propose a comprehensive automated method for calculating soft errors in unit circuits and validated it through TCAD simulations, achieving an error margin of 2.8–4.3%. This demonstrated the accuracy and effectiveness of the method we propose.

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Section: Automated Prediction Process For Radiation-induced Vulnerabi...supporting

confidence: 91%

A Method for Automatically Predicting the Radiation-Induced Vulnerability of Unit Integrated Circuits

Dong,

Lu,

Yang

et al. 2024

Micromachines

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“…In fact, the digital blocks of the RD53A chip were implemented on the DNW layer in order to shield the sensitive analog design from the digital noise. The DNW layer could potentially decrease the SEU tolerance [4]. Irradiation tests were carried out at CERN.…”

Section: Introductionmentioning

confidence: 99%

A study of SEU-tolerant latches for the RD53A chip

Fougeron¹

2018

Proceedings of Topical Workshop on Electronics for Particle Physics — PoS(TWEPP-17)

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“…These systems suffer from neutron [10,11], gamma [12], alpha [13], proton [14], Heavy ions [15] and elementary particle failure [16], due to the generation of single event effects [18,19] and due to a single bit or multi-bit failure [20,21]. This can be generated directly by primary radiation or indirectly by secondary radiation [22].…”

Section: Introductionmentioning

confidence: 99%

GEANT4 simulations in terms of radiation hardness of commercially available SRAM

Moujbani

Weide‐Zaage

Romer³

et al. 2015

2015 16th International Conference on Thermal, Mechanical and Multi-Physics Simulation and Experiments in Microelectronics and

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Commercial of the shelf (COTS) SRAMS were investigated by measurements and simulation in terms of radiation hardness. For the simulations the GEANT4 tool was used. With GEANT4 it is possible to determine the different particles generated by the applied energy as well as the radiation source. It was found that the single event upsets (SEU) is related to the radiation energy, technology node and react differently for the investigated SRAM. Furthermore a possible correlation between the generated particles and the SEU was found.

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A commercial 65nm CMOS technology for space applications: Heavy ion, proton and gamma test results and modeling

Cited by 11 publications

References 18 publications

A Method for Automatically Predicting the Radiation-Induced Vulnerability of Unit Integrated Circuits

A Method for Automatically Predicting the Radiation-Induced Vulnerability of Unit Integrated Circuits

A study of SEU-tolerant latches for the RD53A chip

GEANT4 simulations in terms of radiation hardness of commercially available SRAM

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