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Record W2051341421 · doi:10.1049/mnl.2010.0233

Ultra-thin porous silicon membranes fabricated using dry etching

2011· article· en· W2051341421 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMicro & Nano Letters · 2011
Typearticle
Languageen
FieldMaterials Science
TopicSilicon Nanostructures and Photoluminescence
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsMaterials scienceMembraneWaferPorous siliconSiliconXenon difluorideEtching (microfabrication)PorosityScanning electron microscopeDry etchingThin filmFabricationNanotechnologyComposite materialOptoelectronicsChemistryLayer (electronics)

Abstract

fetched live from OpenAlex

The fabrication of free-standing ultra-thin porous silicon membrane structures using xenon difluoride (XeF2)-based isotropic dry etching of thin silicon wafers is reported. Using this technique, the authors demonstrate 1, 5 and 10 µm-thick porous silicon membranes that are stable and self-supporting and of relatively large surface area. By strategically choosing the etching parameters and conditions, membrane thickness and pore size can be tuned to produce porous silicon membranes with attractive features that could allow structural optimisation for different applications including biological sample filtering, sensing and drug delivery. The pore size, porosity and thickness of the various developed ultra-thin free-standing porous silicon membranes were characterised with scanning electron microscopy and optical transmittance measurements.

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.

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 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 score0.005
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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)0.0010.000

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 head0.023
GPT teacher head0.226
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