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Record W2083304160 · doi:10.1116/1.1647589

Arrays of holes fabricated by electron-beam lithography combined with image reversal process using nickel pulse reversal plating

2004· article· en· W2083304160 on OpenAlexaff
Y. Awad, Éric Lavallée, Kien Mun Lau, Jacques Beauvais, Dominique Drouin, Mélanie Cloutier, David Turcotte, Yang Pan, Prasad Kelkar

Bibliographic record

VenueJournal of Vacuum Science & Technology A Vacuum Surfaces and Films · 2004
Typearticle
Languageen
FieldMaterials Science
TopicOptical Coatings and Gratings
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsMaterials scienceLithographyPlating (geology)Electron-beam lithographyEtching (microfabrication)NickelOptoelectronicsPhotolithographySilicon nitrideResistReactive-ion etchingSiliconNitrideCathode rayOpticsNanotechnologyElectronMetallurgy

Abstract

fetched live from OpenAlex

A critical issue in fabricating arrays of holes is to achieve high-aspect-ratio structures. Formation of ordered arrays of nanoholes in silicon nitride was investigated by the use of ultrathin hard etch mask formed by nickel pulse reversal plating to invert the tonality of a dry e-beam resist patterned by e-beam lithography. Ni plating was carried out using a commercial plating solution based on nickel sulfamate salt without organic additives. Reactive ion etching using SF6/CH4 was found to be very effective for pattern transfer to silicon nitride. Holes array of 100 nm diam, 270 nm period, and 400 nm depth was fabricated on a 5×5 mm2 area.

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: Methods · Consensus signal: none
Teacher disagreement score0.002
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.006
GPT teacher head0.246
Teacher spread0.240 · 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
GenreMethods

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

Citations7
Published2004
Admission routes1
Has abstractyes

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