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Record W4281643807 · doi:10.3390/electronics11111757

Comparison of Total Ionizing Dose Effects in 22-nm and 28-nm FD SOI Technologies

2022· article· en· W4281643807 on OpenAlexaff
Zongru Li, Christopher Elash, Chen Jin, Li Chen, Jiesi Xing, Zhiwu Yang, Shuting Shi

Bibliographic record

VenueElectronics · 2022
Typearticle
Languageen
FieldEngineering
TopicRadiation Effects in Electronics
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsSilicon on insulatorAbsorbed doseStatic random-access memoryIrradiationDegradation (telecommunications)Materials scienceOptoelectronicsIonizing radiationNode (physics)Electrical engineeringSiliconPhysicsEngineeringNuclear physics

Abstract

fetched live from OpenAlex

Total ionizing dose (TID) effects from Co-60 gamma ray and heavy ion irradiation were studied at the 22-nm FD SOI technology node and compared with the testing results from the 28-nm FD SOI technology. Ring oscillators (RO) designed with inverters, NAND2, and NOR2 gates were used to observe the output frequency drift and current draw. Experimental results show a noticeable increased device current draw and decreases in RO frequencies where NOR2 ROs have the most degradation. As well, the functionality of a 256 kb SRAM block and shift-register chains were evaluated during C0-60 irradiation. SRAM functionality deteriorated at 325 krad(Si) of the total dosage, while the FF chains remained functional up to 1 Mrad(Si). Overall, the 22-nm FD SOI results show better resilience to TID effects compared to the 28-nm FD SOI technology node.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.005
GPT teacher head0.237
Teacher spread0.231 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations11
Published2022
Admission routes1
Has abstractyes

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