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Record W2145181833 · doi:10.1002/ceat.200500237

Experimental Investigation of Ethanol Enrichment Behavior in Batch and Continuous Feed Ultrasonic Atomization Systems

2006· article· en· W2145181833 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

VenueChemical Engineering & Technology · 2006
Typearticle
Languageen
FieldEngineering
TopicElectrohydrodynamics and Fluid Dynamics
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsUltrasonic sensorAlcoholMistChemistryMaterials scienceEthanolChemical engineeringChromatographyAnalytical Chemistry (journal)Organic chemistryAcoustics

Abstract

fetched live from OpenAlex

Abstract The fragmentation of a liquid layer to form a fine droplet mist by high frequency ultrasonic atomization of liquids has been applied to a range of industrial applications such as fine chemical manufacturing, pharmaceutical production, and food processing. A recent development is the separation of alcohol from miscible alcohol‐water mixtures using ultrasonic atomization. In this work, the effect of high frequency ultrasonic atomization at 1.6 MHz on the enrichment of ethanol from ethanol‐water feed mixtures has been studied. Experiments for evaluating this enrichment process were conducted in batch and continuous feed processing systems. The continuous enrichment process generated product concentrations that were higher than the equivalent vapor‐liquid equilibrium curve at feed concentrations greater than 40 mol.‐% in a single stage. The role of the ultrasonic jet formed at the surface of the feed solution combined with the ethanol separation characteristics has been discussed.

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 score0.417
Threshold uncertainty score0.724

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 head0.173
Teacher spread0.171 · 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