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Record W2487433548 · doi:10.1063/1.4958852

Effects of antimony (Sb) on electron trapping near SiO2/4H-SiC interfaces

2016· article· en· W2487433548 on OpenAlexafffund
P. M. Mooney, Zenan Jiang, A. F. Basile, Yongju Zheng, Sarit Dhar

Bibliographic record

VenueJournal of Applied Physics · 2016
Typearticle
Languageen
FieldEngineering
TopicSilicon Carbide Semiconductor Technologies
Canadian institutionsSimon Fraser University
FundersArmy Research LaboratoryNatural Sciences and Engineering Research Council of CanadaAuburn UniversitySimon Fraser UniversityNational Science Foundation
KeywordsMaterials scienceTrappingDeep-level transient spectroscopyPassivationCapacitorMOSFETAntimonySilicon carbideCapacitanceAnalytical Chemistry (journal)SiliconElectronDopingOptoelectronicsChemistryElectrodeLayer (electronics)NanotechnologyElectrical engineeringComposite materialMetallurgyTransistor

Abstract

fetched live from OpenAlex

To investigate the mechanism by which Sb at the SiO2/SiC interface improves the channel mobility of 4H-SiC MOSFETs, 1 MHz capacitance measurements and constant capacitance deep level transient spectroscopy (CCDLTS) measurements were performed on Sb-implanted 4H-SiC MOS capacitors. The measurements reveal a significant concentration of Sb donors near the SiO2/SiC interface. Two Sb donor related CCDLTS peaks corresponding to shallow energy levels in SiC were observed close to the SiO2/SiC interface. Furthermore, CCDLTS measurements show that the same type of near-interface traps found in conventional dry oxide or NO-annealed capacitors are present in the Sb implanted samples. These are O1 traps, suggested to be carbon dimers substituted for O dimers in SiO2, and O2 traps, suggested to be interstitial Si in SiO2. However, electron trapping is reduced by a factor of ∼2 in Sb-implanted samples compared with samples with no Sb, primarily at energy levels within 0.2 eV of the SiC conduction band edge. This trap passivation effect is relatively small compared with the Sb-induced counter-doping effect on the MOSFET channel surface, which results in improved channel transport.

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 score0.022
Threshold uncertainty score0.520

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)0.0000.000

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 head0.206
Teacher spread0.199 · 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

Citations5
Published2016
Admission routes2
Has abstractyes

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