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Record W1968093290 · doi:10.1115/1.2400270

Effect of Atomization Method on the Morphology of Spray-Generated Particles

2006· article· en· W1968093290 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

VenueJournal of Engineering Materials and Technology · 2006
Typearticle
Languageen
FieldEngineering
TopicElectrohydrodynamics and Fluid Dynamics
Canadian institutionsUniversity of TorontoUniversity of New Brunswick
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSplashNozzleMistMagnesiumNebulizerMaterials scienceMorphology (biology)Particle sizeParticle (ecology)Saturation (graph theory)Analytical Chemistry (journal)Chemical engineeringChemistryMetallurgyChromatographyThermodynamicsMeteorology

Abstract

fetched live from OpenAlex

Effect of various atomization methods and solute concentration on the morphology of spray dried magnesium sulphate particles is investigated. Four types of atomizers are characterized and tested including (i) a vibrating mesh nebulizer, (ii) a splash plate nozzle, (iii) an air mist atomizer, and (iv) a pressure atomizer. Several types of particle morphologies are identified in this research. Spray characteristics, such as droplet number density, droplet size, and velocity, and accompanying atomizing air have major influence on the drying and morphology of the particles. High initial solute concentrations result in the formation of thick-walled particles, and this prevents the particles to burst. It is found to be difficult to obtain fully filled magnesium sulphate particles, even for saturated solutions at room temperature because the solution equilibrium saturation changes substantially with temperature.

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 score0.029
Threshold uncertainty score0.266

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 head0.002
GPT teacher head0.188
Teacher spread0.186 · 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