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Influence of the Oxidation Temperature and Atmosphere on the Reliability of Thick Gate Oxides on the 4H-SiC C(000-1) Face

2008· article· en· W2089905261 on OpenAlexaff
Michael Grieb, Dethard Peters, Anton J. Bauer, Peter Friedrichs, H. Ryssel

Bibliographic record

VenueMaterials science forum · 2008
Typearticle
Languageen
FieldEngineering
TopicSilicon Carbide Semiconductor Technologies
Canadian institutionsInfineon Technologies (Canada)
Fundersnot available
KeywordsMaterials scienceOxideThermal oxidationReliability (semiconductor)Analytical Chemistry (journal)WaferCapacitorStress (linguistics)Atmosphere (unit)Gate oxideVoltageOptoelectronicsElectrical engineeringMetallurgyThermodynamicsChemistry

Abstract

fetched live from OpenAlex

The reliability of thermal oxides grown on n-type 4H-SiC C(000-1) face wafer has been investigated. In order to examine the influence of different oxidation atmospheres and temperatures on the reliability, metal-oxide-semiconductor capacitors were manufactured and the different oxides were characterized by C-V measurements and constant-current-stress. The N2O-oxides show the smallest flat band voltage shift compared to the ideal C-V curve and so the lowest number of effective oxide charges. They reveal also the lowest density of interface states in comparison to the other oxides grown on the C(000-1) face, but it is still higher than the best oxides on the Si(000-1) face. Higher oxidation temperatures result in smaller flat band voltage shifts and lower interface state densities. Time to breakdown measurements show that the charge-to-breakdown value of 63% cumulative failure for the N2O-oxide on the C(000-1) face is more than one order of magnitude higher than the highest values measured on the Si(000-1) face. Therefore it can be concluded that a smaller density of interface states results in a higher reliability of the oxide.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.053
Threshold uncertainty score0.574

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.010
GPT teacher head0.203
Teacher spread0.192 · 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

Citations6
Published2008
Admission routes1
Has abstractyes

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