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Record W2095391440 · doi:10.1139/p07-053

Ètude des interfaces SiO<sub>2</sub>/TiO<sub>2</sub> et TiO<sub>2</sub>/SiO<sub>2</sub> dans la structure SiO<sub>2</sub>/TiO<sub>2</sub>/SiO<sub>2</sub>/c-Si préparée par pulvérisation cathodique radio fréquence

2007· article· en· W2095391440 on OpenAlexvenueno aff
K. Hafidi, M. Azizan, Y. Ijdiyaou, E.L. Ameziane

Bibliographic record

VenueCanadian Journal of Physics · 2007
Typearticle
Languageen
FieldEngineering
TopicSemiconductor materials and devices
Canadian institutionsnot available
Fundersnot available
KeywordsX-ray photoelectron spectroscopyReflectometryTitaniumSiliconSputteringSubstrate (aquarium)Analytical Chemistry (journal)Materials sciencePhysicsThin filmNanotechnologyChemistryOptoelectronicsNuclear magnetic resonance

Abstract

fetched live from OpenAlex

The atomic structure of the TiO2/SiO2 and SiO2/TiO2 interfaces has been investigated in SiO2/TiO2/SiO2 multilayers deposited by radio frequency reactive sputtering without breaking the vacuum on the crystalline substrate cooled by water. The characterizations of these interfaces have been performed using three complementary techniques sensitive to surface and interface state: X-ray photoelectron spectroscopy (XPS), grazing incidence X-ray diffraction (GIXD), and specular X-ray reflectometry (GIXR). The concentration profiles and Si2p and O1s core level chemical displacements show that TiO2/SiO2 and SiO2/TiO2 interfaces are very diffuse. The reflectometry measurements confirm this character and indicate that the silicon, titanium, and oxygen atomic concentrations vary gradually at the interfaces. The grazing incidence X-ray spectra indicates that the interfacial layers are not well crystallized and are formed by SiO2-TiO2, TiO, Ti2O3, Ti3O5, Ti5Si3, Ti5Si4, TiSi, and TiSi2 components.

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 score0.003
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.214
Teacher spread0.203 · 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

Citations0
Published2007
Admission routes1
Has abstractyes

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