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Record W2054903919 · doi:10.1109/iedm.2008.4796687

Session 14: Characterization, reliability, and yield - ESD/memory reliability

2008· article· en· W2054903919 on OpenAlexaff
Harald Goßner, A. Paccagnella

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicIntegrated Circuits and Semiconductor Failure Analysis
Canadian institutionsInfineon Technologies (Canada)
Fundersnot available
KeywordsReliability (semiconductor)Electrostatic dischargeReliability engineeringNon-volatile memorySession (web analytics)Flash memoryComputer scienceLeakage (economics)CMOSElectrical engineeringVoltageEngineeringEmbedded systemPhysics

Abstract

fetched live from OpenAlex

The ESD and non-volatile memory reliability session focuses on recent developments in ESD and Latchup protection methodology and reliability challenges for NVMs. The invited talk on the ESD qualification for 45 nm and beyond provides first hand information about the vivid discussion on ESD target levels started in the electronics industry. For 22 nm and beyond FINFET technology might become an option which requires an appropriate ESD protection as discussed by the second paper. The growing awareness of a latchup optimized design is addressed by the study of guard ring interactions and their effect on CMOS Latchup resilience. In the second part of the session, Non-Volatile Memory reliability aspects will be presented, starting with a new method to evaluate the trapped charge distributions in SONOS-type devices. Retention implications will be discussed in this presentation, as well as in the following one, focused on the statistical investigation of leakage current in floating gate cells with a high-k interpoly dielectric. In the last paper of this session, evidence will be provided for bit flips produced in Flash memories by the atmospheric neutrons deriving as ground level byproducts of cosmic ions.

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 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 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 score0.423
Threshold uncertainty score0.866

Codex and Gemma teacher scores by category

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)0.0010.000

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 head0.197
Teacher spread0.185 · 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 teacher head, 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

Citations0
Published2008
Admission routes1
Has abstractyes

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