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Record W1835049006 · doi:10.5539/apr.v7n5p1

Fabrication of Gas Sensor Device for H2 and NO2 from Porous Silicon

2015· article· en· W1835049006 on OpenAlexvenueno aff
Waleed Bdaiwi

Bibliographic record

VenueApplied Physics Research · 2015
Typearticle
Languageen
FieldMaterials Science
TopicSilicon Nanostructures and Photoluminescence
Canadian institutionsnot available
Fundersnot available
KeywordsMaterials sciencePorous siliconHydrofluoric acidSiliconEtching (microfabrication)WaferPhotoluminescenceHillockOptoelectronicsLayer (electronics)Nanocrystalline siliconSurface finishSurface roughnessAnalytical Chemistry (journal)NanotechnologyCrystalline siliconComposite material

Abstract

fetched live from OpenAlex

A nanocrystalline porous silicon (PS) layer was prepared by electrochemical etching method of p–type silicon wafer in hydrofluoric acid (HF). The properties of porous silicon structure under various etching times (10–50 min), HF concentrations, and current density were studied. The study included photoluminescence (PL), morphology, x–ray, and gas sensor. The results (PL) spectra (peak wavelength) can be shifted from (505 to 625) nm. PL analysis indicated that the energy band gap can be tuned from (1.984–2.455) eV with respect to etched time. Atomic Force Microscopy (AFM) analysis showed that the PS layer had a sponge–like structure. Surface roughness and the pyramid–like hillocks on the entire surface play an important role in variation visible luminescence. The AFM images shows that the average diameter of the PS layer pore and thickness the Silicon decreased when etching time increase and the average diameter particleboard ranged from (80.8–35.4) nm. PS X–ray topography studies that the skeleton maintained its silicon crystalline structure after anodization. PS Sensors were fabricated and tested successfully on H2 and No2 gas.

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 score0.004

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)0.0010.000

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 head0.101
GPT teacher head0.357
Teacher spread0.256 · 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

Citations8
Published2015
Admission routes1
Has abstractyes

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