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Record W4407097988 · doi:10.1109/tns.2025.3537609

Analysis of Guard Gates on FF SEU Rates at a 12-nm FinFET Node

2025· article· pt· W4407097988 on OpenAlex
Christopher Elash, Jiesi Xing, Peiman Pour Momen, Devin P. Ramaswami, Hangjun Lu, Zongru Li, Shi-Jie Wen, Rita Fung, Li Chen

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Transactions on Nuclear Science · 2025
Typearticle
Languagept
FieldEngineering
TopicIntegrated Circuits and Semiconductor Failure Analysis
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of CanadaCMC MicrosystemsCisco Systems
KeywordsNode (physics)Logic gateGuard (computer science)Electrical engineeringOptoelectronicsPhysicsRandom access memoryMaterials scienceElectronic engineeringComputer scienceEngineeringComputer hardwareQuantum mechanics

Abstract

fetched live from OpenAlex

This article studies the soft error rates (SERs) of latches by using different delay lengths in guard gate (GG)-based flip-flop (FF) designs at a 12-nm FinFET technology node. Three FFs are designed by using the guard-gate structure with varying delay elements (two, four, and six inverter delays), along with a standard reference FF. The FFs were connected in chains and fabricated on a test chip, which was tested with alpha particles, heavy ions, and protons. Results indicate that single-event upset (SEU) rates can be reduced with the guard-gate structure during alpha particle irradiation. However, the guard-gate designs only show slight SER improvement over the reference design for moderate and high linear energy transfer (LET) ranges. Through technology computer aided design (TCAD) simulations, it is shown that the single-event transient (SET) pulse widths for moderate- to high-LET particles can be significantly longer than the delay-element propagation times. Also, guard-gate designs experience a strong dependence on data input patterns regarding SERs, which is due to uneven charge collection in pMOS and nMOS devices at this 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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.008
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.013
GPT teacher head0.249
Teacher spread0.236 · 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