MétaCan
Menu
Back to cohort
Record W1519445922 · doi:10.1063/1.2898502

Ultrashallow defect states at SiO2∕4H–SiC interfaces

2008· article· en· W1519445922 on OpenAlexaff
Sarit Dhar, X. D. Chen, P. M. Mooney, John R. Williams, L. C. Feldman

Bibliographic record

VenueApplied Physics Letters · 2008
Typearticle
Languageen
FieldEngineering
TopicSilicon Carbide Semiconductor Technologies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsConduction bandMaterials scienceEnhanced Data Rates for GSM EvolutionWide-bandgap semiconductorCapacitanceAnalytical Chemistry (journal)OptoelectronicsCondensed matter physicsAtomic physicsChemistryPhysicsElectrodePhysical chemistry

Abstract

fetched live from OpenAlex

Interface state density (Dit) at SiO2∕4H–SiC interfaces are reported for states lying energetically within ∼0.05–0.2eV of the conduction band edge (EC) of 4H–SiC using capacitance-voltage characterization as a function of temperature. Comparison of as-grown dry oxidized and nitrided interfaces confirms the significant reduction of Dit associated with nitridation. In the as-oxidized case (no nitridation), the Dit in the energy range ∼0.05–0.2eV below EC is found to consist of a broad Dit peak at about ∼0.1eV below EC with an energy width of about ∼0.2eV and a peak magnitude of ∼2×1013cm−2eV−1 superimposed on an exponentially decaying background distribution. Interfacial nitridation completely eliminates the broad peak but does not strongly affect the background.

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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.014
GPT teacher head0.192
Teacher spread0.178 · 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

Citations50
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueApplied Physics LettersSame topicSilicon Carbide Semiconductor TechnologiesFrench-language works237,207