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A damascene platform for controlled ultra-thin nanowire fabrication

2013· article· en· W1969006357 on OpenAlexafffund
Marc Guilmain, Thibault Labbaye, F Dellenbach, C. Nauenheim, Dominique Drouin, Serge Ecoffey

Bibliographic record

VenueNanotechnology · 2013
Typearticle
Languageen
FieldEngineering
TopicAdvanced Surface Polishing Techniques
Canadian institutionsInstitut interdisciplinaire d'innovation technologiqueUniversité de Sherbrooke
FundersNatural Sciences and Engineering Research Council of CanadaAgence Nationale de la Recherche
KeywordsMaterials scienceChemical-mechanical planarizationFabricationCopper interconnectTitaniumNanowireNanometreNanostructureNanotechnologyNanolithographyOptoelectronicsComposite materialMetallurgyDielectricLayer (electronics)

Abstract

fetched live from OpenAlex

This paper presents a damascene process for the fabrication of titanium micro/nanostructures and nanowires with adjustable thickness down to 2 nm. Their depth is precisely controlled by chemical-mechanical planarization together with in-process electrical characterization. The latter, in combination with a model of the titanium resistivity versus thickness, allows control of the metal line depth in the nanometer range. In summary, we have developed a planarization end point detection method for metal nanostructures. In addition, the model adopted covers geometrical influences like oxidation and ageing. The fabricated titanium nanowire test structures have a thickness ranging from 2 to 25 nm and a width ranging between 15 and 230 nm.

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 score0.005

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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.235
Teacher spread0.224 · 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

Citations16
Published2013
Admission routes2
Has abstractyes

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