SEE rate estimation based on diffusion approximation of charge collection

Sogoyan, A. V.; Chumakov, A. I.; Smolin, Anatoly A.

doi:10.1016/j.nimb.2018.01.001

Cited by 2 publications

(3 citation statements)

References 12 publications

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“…The parameters in such a model are the RPP size and the critical charge. The basic assumption of this model, that the chargecollection mechanism after ionization in the device may be represented by a single volume which has a uniform chargecollection efficiency, is unphysical as has been pointed out by Wrobel et al [50], Warren et al [51], and Sogoyan et al [52]. In reality, the charge-collection efficiency of a transistor is not constant throughout a fixed volume, since multiple processes contribute to the charge-collection mechanism.…”

Section: B Model Geometrymentioning

confidence: 99%

“…In this region, there are no strong fields present and the charge has to diffuse to a transistor p-n junction where it is collected efficiently. Different approaches have been taken to address these shortcomings of the RPP model, for example, by modeling the time structure of charge diffusion and collection [54], [55], by modeling the total amount of charge collected through diffusion [50]- [52], or by introducing a nested RPP model that allows for variations in the charge-collection efficiency [51]. More realistic models such as these also allow for charge sharing between adjacent transistors and memory cells, an effect not included in the standard RPP model.…”

Section: B Model Geometrymentioning

confidence: 99%

“…The model presented in this article has been developed to address some of the issues with the RPP model and treats charge diffusion in a way similar to what has been proposed in [50] and [52]. It can be seen as an extension of the traditional RPP model, modeling both charge drift and diffusion.…”

Section: B Model Geometrymentioning

confidence: 99%

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Proton- and Neutron-Induced Single-Event Upsets in FPGAs for the PANDA Experiment

Preston

Calén

Johansson

et al. 2020

IEEE Trans. Nucl. Sci.

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Single-event upsets (SEUs) affecting the configuration memory of a 28-nm field-programmable gate array (FPGA) have been studied through experiments and Monte Carlo modeling. This FPGA will be used in the front-end electronics of the electromagnetic calorimeter in PANDA (Antiproton Annihilation at Darmstadt), an upcoming hadron-physics experiment. Results from proton and neutron irradiations of the FPGA are presented and shown to be in agreement with previous experimental results. To estimate the mean time between SEUs during operation of PANDA, a Geant4-based Monte Carlo model of the phenomenon has been used. This model describes the energy deposition by particles in a silicon volume, the subsequent drift and diffusion of charges in the FPGA memory cell, and the eventual collection of charges in the sensitive regions of the cell. The values of the two free parameters of the model, the sensitive volume side d = 87 nm and the critical charge Q crit = 0.23 fC, were determined by fitting the model to the experimental data. The results of the model agree well with both the proton and neutron data and are also shown to correctly predict the cross sections for upsets induced by other particles. The modelpredicted energy dependence of the cross section for neutroninduced upsets has been used to estimate the rate of SEUs during initial operation of PANDA. At a luminosity of 1 • 10 31 cm −2 s −1 , the predicted mean time between upsets (MTBU) is between 120 and 170 h per FPGA, depending on the beam momentum.

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Section: B Model Geometrymentioning

confidence: 99%