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Record W2057185012 · doi:10.1116/1.3628593

Silicon nitride nanotemplate fabrication using inductively coupled plasma etching process

2011· article· en· W2057185012 on OpenAlexaff
Asma Ayari-Kanoun, Abdelatif Jaouad, Abdelkader Souifi, Dominique Drouin, Jacques Beauvais

Bibliographic record

VenueJournal of Vacuum Science & Technology B Nanotechnology and Microelectronics Materials Processing Measurement and Phenomena · 2011
Typearticle
Languageen
FieldEngineering
TopicSemiconductor materials and devices
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsEtching (microfabrication)Materials scienceInductively coupled plasmaSilicon nitrideSiliconNitridePlasma etchingFabricationDry etchingReactive-ion etchingOptoelectronicsNanotechnologyPlasmaLayer (electronics)

Abstract

fetched live from OpenAlex

In this work, we have investigated the fabrication of ordered silicon nitride nanohole arrays as part of an overall process aimed at producing organized silicon nanocrystals. The authors have demonstrated that it is possible to use inductively coupled plasma etching systems in order to etch nanometric layers, despite the fact that these systems are designed for deep and fast etching. A stable process is developed for shallow etching of silicon nitride nanoholes. The influence of different plasma etching parameters on silicon nitride nanohole properties is analyzed. 30 nm deep nanoholes of approximately 30 nm diameter, near vertical sidewalls and a good control of the selectivity are achieved. The overall process provides a simple and reproducible approach based on shallow inductively coupled plasma etching to obtain high quality nanosized silicon nitride templates. A suitable process for organized arrays of 10 nm diameter silicon nanocrystals realized by electrochemical etching is shown.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.008
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0010.000
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 head0.032
GPT teacher head0.237
Teacher spread0.205 · 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.

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

Citations13
Published2011
Admission routes1
Has abstractyes

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