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Record W3160365192 · doi:10.1109/led.2021.3079244

Trap Recovery by in-Situ Annealing in Fully-Depleted MOSFET With Active Silicide Resistor

2021· article· en· W3160365192 on OpenAlex

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.

Bibliographic record

VenueIEEE Electron Device Letters · 2021
Typearticle
Languageen
FieldEngineering
TopicSemiconductor materials and devices
Canadian institutionsInstitut interdisciplinaire d'innovation technologiqueUniversité de Sherbrooke
Fundersnot available
KeywordsMaterials scienceAnnealing (glass)MOSFETTransconductanceOptoelectronicsSilicideTransistorCMOSResistorSilicon on insulatorElectrical engineeringElectronic engineeringSiliconEngineeringMetallurgyVoltage

Abstract

fetched live from OpenAlex

This work reports first original results on the impact of active in-situ electro-thermal recovery, on the electrical and low-frequency noise characteristics of N-type MOS transistor with thick high-k metal gate oxide, from 28 nm Fully Depleted Silicon-On-Insulator (FDSOI) process. In order to recover “typical” device characteristics, four cycles of local thermal annealing up to 590K are applied for 14 ms each, using an active silicide source. Experimental results reveal an important improvement of the “corner” transistor’s I-V behavior allowing the recovery of “typical” device characteristics. An increase of the maximum transconductance by 43% is obtained. In the same time, a typical device stays unaffected by this local annealing. Low-frequency noisemeasurements showa clear reduction of the 1/f noise and Random Telegraph Noise by almost one decade, after the electro-thermal recovery. This can explain the improvement of the electrical characteristics by annealing of defects.

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)
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 score0.004
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.007
GPT teacher head0.202
Teacher spread0.195 · 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