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Deep Levels in As-Grown 4H-SiC Epitaxial Layers and their Correlation with CVD Parameters

2003· article· en· W2001273725 on OpenAlexaff
Ioana Pintilie, L. Pintilie, K. Irmscher, Bernd Thomas

Bibliographic record

VenueMaterials science forum · 2003
Typearticle
Languageen
FieldEngineering
TopicSilicon Carbide Semiconductor Technologies
Canadian institutionsInfineon Technologies (Canada)
FundersBundesministerium für Bildung und Forschung
KeywordsMaterials scienceEpitaxyOptoelectronicsEngineering physicsComposite materialLayer (electronics)

Abstract

fetched live from OpenAlex

Abstract. Nitrogen doped 4H-SiC epitaxial layers grown by hot-wall chemical vapor deposition were investigated by deep level transient spectroscopy in the as-grown state. Besides the Z1,2 defect level at EC- 0.66 eV, that seems to be omnipresent, four other electron traps labeled IL1 to IL4 with ionization energies between 0.87 and 1.31 eV could be detected. The dependence of the deep level concentrations on the incorporated N concentration ranging from few 1014 to some 1015 cm-3 and the C/Si ratio (1.2¸3) was examined. The concentration of both Z1,2 and IL1 increases with increa-sing N doping. For medium C/Si ratios this dependence is linear for Z1,2 and quadratic for IL1. High C/Si ratios enhance the formation of Z1,2 while they suppress that of IL1. These results suggest a complex of interstitial C and N on carbon site (Ci-NC) for Z1,2 and a nitrogen pair (NC-Ni) for IL1. However, other possibilities like Si vacancy related defects cannot be ruled out at present.

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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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 head0.012
GPT teacher head0.208
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

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

Citations15
Published2003
Admission routes1
Has abstractyes

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