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Record W2025217064 · doi:10.2202/1542-6580.1330

Synthesis of SiO2 Nanoparticles in RF Plasma Reactors: Effect of Feed Rate and Quench Gas Injection

2006· article· en· W2025217064 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.

Bibliographic record

VenueInternational Journal of Chemical Reactor Engineering · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicCoagulation and Flocculation Studies
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsNanoparticleMaterials scienceScanning electron microscopeInductively coupled plasmaParticle sizeParticle-size distributionPlasmaAnalytical Chemistry (journal)Absorption (acoustics)Particle (ecology)Chemical engineeringNanotechnologyChemistryComposite materialChromatography

Abstract

fetched live from OpenAlex

Nanoparticles of SiO2 have been produced in an inductively coupled thermal plasma reactor. The resulting nanoparticles were characterized based on their morphology and size distribution. Scanning electron microscopy, nitrogen absorption (BET method), laser diffractometry and X-ray diffraction techniques were used to characterize and to measure the equivalent diameter (D(1,0), D(3,2) and D(4,3)) of the resulting nanopowders. The computational fluid dynamics (CFD) software FluentTM 6.1 with the Fine Particle Model (FPMTM) was used to simulate the whole synthesis process. The nanoparticles of SiO2 produced at the exit (filter) and on the reactor wall had primary particles diameter between 10-300 nm while the aggregates were of much larger size, between 1 and 4 micrometers. The simulation predictions were used to gain more insight into the experimental results.

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 score0.041
Threshold uncertainty score0.249

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 head0.004
GPT teacher head0.213
Teacher spread0.209 · 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