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Record W1984198339 · doi:10.1021/ef700588y

Measurement of the Liquid−Deposit Interface Temperature during Solids Deposition from Wax−Solvent Mixtures under Static Cooling Conditions

2008· article· en· W1984198339 on OpenAlexafffund
Hamid Bidmus, Anil K. Mehrotra

Bibliographic record

VenueEnergy & Fuels · 2008
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsUniversity of Calgary
FundersWorkforce Development for Teachers and ScientistsNatural Sciences and Engineering Research Council of Canada
KeywordsWaxCoolantSolventParaffin waxHeat transferChemistryMaterials scienceDeposition (geology)DiffusionChemical engineeringAnalytical Chemistry (journal)ThermodynamicsChromatographyComposite materialOrganic chemistry

Abstract

fetched live from OpenAlex

The liquid−deposit interface temperature for solids deposition was measured under static cooling (i.e., without any induced shear stress) from prepared mixtures of a petroleum wax (C 20 −C 40 ) and a multicomponent paraffinic solvent (C 9 −C 16 ) at different coolant temperatures. Two designs for the cooling of wax−solvent mixtures were developed for monitoring the temperature at fixed radial locations in a cylindrical vessel. The wax−solvent mixture was cooled from a temperature higher than its wax appearance temperature (WAT), and the movement of the liquid−deposit interface was obtained from the rate of change of temperature at different radial locations. The deposit-layer thickness increased more rapidly with a larger heat-transfer area and a lower coolant temperature. The interface temperature was observed to be equal to the WAT of the wax−solvent mixture, and it decreased slightly when the liquid-region temperature became less than the WAT of the original mixture (causing the precipitation of wax crystals). The results of this study support the constant-interface-temperature assumption made in the heat-transfer approach for modeling solids deposition from waxy mixtures, but not the increasing-interface-temperature assumption in the molecular-diffusion approach.

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 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 score0.005
Threshold uncertainty score0.609

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 head0.012
GPT teacher head0.226
Teacher spread0.215 · 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 teacher head, 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

Citations33
Published2008
Admission routes2
Has abstractyes

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