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Record W2012442722 · doi:10.1049/mnl.2009.0107

Dry etch fabrication of porous silicon using xenon difluoride

2010· article· en· W2012442722 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 · 2010
Typearticle
Languageen
FieldMaterials Science
TopicSilicon Nanostructures and Photoluminescence
Canadian institutionsMcGill University
FundersFonds Québécois de la Recherche sur la Nature et les TechnologiesMcGill University
KeywordsPorous siliconMaterials scienceSiliconFabricationXenon difluorideEtching (microfabrication)Dry etchingPorosityMicroelectronicsLayer (electronics)OptoelectronicsPhotoresistNanotechnologyComposite materialChemistry

Abstract

fetched live from OpenAlex

The authors report the fabrication of porous silicon material using a xenon difluoride (XeF2) dry etching technique. Using a XeF2 fabrication process, porous silicon can be formed selectively on silicon by employing a standard hard-baked photoresist layer as a masking layer. The authors demonstrate porous silicon with different pore sizes and configurations rendering this material as an attractive candidate for a wide spectrum of potential applications. The pore size, porosity and thickness of the various developed porous silicon samples were characterised with electron microscopy and optical reflectance measurements. This XeF2 etching technique offers flexible and straightforward fabrication of porous silicon and could allow simple monolithic integration of porous silicon devices with microelectronic circuitry, following the current trend of integrated microsystems.

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 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 score0.003
Threshold uncertainty score0.646

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 science0.0000.000
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 head0.009
GPT teacher head0.231
Teacher spread0.222 · 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