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Record W2085645099 · doi:10.1002/cjce.5450820423

Breaking Water‐in‐Bitumen Emulsions using Polyoxyalkylated DETA Demulsifier

2004· article· en· W2085645099 on OpenAlexaffvenue
Yuming Xu, Jiangying Wu, T. Da̧broś, Hassan Hamza, Sanyi Wang, Marianne Bidal, Johann Venter, Tom Tran

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2004
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsSyncrude (Canada)Devon Energy (Canada)
Fundersnot available
KeywordsDemulsifierDehydrationSettlingAsphaltSettling timeChromatographyChemistryMaterials scienceChemical engineeringPulp and paper industryEmulsionEnvironmental scienceComposite materialEnvironmental engineeringOrganic chemistryEngineering

Abstract

fetched live from OpenAlex

Abstract Adding demulsifier is currently the most widely used method for breaking water‐in‐oil emulsions. Experimental demulsifiers based on DETA with various PO and EO contents were synthesized and their RSN values were determined. The dehydration efficiency of these demulsifiers was measured in diluted bitumen using both gravitational settling and centrifugation tests. The results indicate that some of the DETA products could perform potentially at least as well or better than the demulsifier currently used in a commercial plant. RSN values are correlated very well with EO and PO numbers. Optimal dehydration efficiency is in the RSN range of 18 to 22, which corresponds to a PO‐to‐EO ratio in the range of 1 to 1.8.

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 score0.094
Threshold uncertainty score0.486

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 integrity0.0000.001
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 head0.009
GPT teacher head0.204
Teacher spread0.195 · 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

Citations47
Published2004
Admission routes2
Has abstractyes

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