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Record W1988295182 · doi:10.1116/1.582250

Electrical characterization of metal–oxide–semiconductor capacitors with anodic and plasma-nitrided oxides

2000· article· en· W1988295182 on OpenAlexafffund
L. M. Landsberger, Rahim Ghayour, M. Sayedi, M. Kahrizi, D. Landheer, J. A. Bardwell, C. Jean, V. Logiudice

Bibliographic record

VenueJournal of Vacuum Science & Technology A Vacuum Surfaces and Films · 2000
Typearticle
Languageen
FieldEngineering
TopicSemiconductor materials and devices
Canadian institutionsInstitute for Microstructural SciencesMitel (Canada)Concordia University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceAnodizingAnodeOxideWaferNitridingAnnealing (glass)Electron cyclotron resonanceSiliconAnalytical Chemistry (journal)PlasmaOptoelectronicsComposite materialMetallurgyAluminiumLayer (electronics)ChemistryElectrode

Abstract

fetched live from OpenAlex

We have studied two novel techniques that should inherently be more uniform than current mainstream processes used to produce silicon dioxide or nitrided-oxide gate insulators. Anodic films were fabricated by anodizing Si wafers in HCl solutions, and thermal oxide films were nitrided in N2O plasmas produced with an electron-cyclotron resonance source. Using typical polysilicon-gate test structures, the electrical characteristics are obtained and compared to thermal oxides. Both techniques can produce thin films (<15 nm thick) with interface state densities and leakage currents initially comparable to their thermal oxide counterparts, if the films are subjected to rapid thermal annealing at temperatures of 950 °C. The annealed films are subjected to high-field (⩾8 MV/cm) Fowler–Nordheim stress and the buildup of trapped charge is monitored as a function of time. Anodic films are found to have moderately higher bulk and interface trap generation rates than the thermal control. Thinner anodic oxides, which were grown at slower rates, had better properties than thicker anodic oxides, suggesting that even slower growth rates could yield anodic oxides with improved electrical properties.

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 score0.011
Threshold uncertainty score0.627

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.006
GPT teacher head0.193
Teacher spread0.187 · 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
Published2000
Admission routes2
Has abstractyes

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