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Record W2087448018 · doi:10.1021/ef800825n

Biodegradable Polymer for Demulsification of Water-in-Bitumen Emulsions

2008· article· en· W2087448018 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

VenueEnergy & Fuels · 2008
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAsphaltPolymerEmulsionSolventChemistryFlocculationChemical engineeringAsphalteneSettlingChromatographyMaterials scienceOrganic chemistryComposite materialEnvironmental engineeringEnvironmental science

Abstract

fetched live from OpenAlex

Removal of residual water from a solvent-diluted bitumen is a challenging task because the water drops, in the emulsified form of a few micrometers, are extremely stable. A nontoxic and biodegradable polymer, ethylcellulose, was used to break up emulsified water from naphtha-diluted bitumen. It was found that the ethylcellulose polymer at 130 ppm dosage removed up to 90% of the emulsified water in the diluted bitumen by gravity settling after 1 h at 80 °C. The tests, extended to bitumen froth containing about 10% solids by weight, showed a 90% removal of the water in the diluted bitumen froth. The addition of ethylcellulose also assisted the removal of fine solids with the water. However, for bitumen froths containing 30% or more solids, the efficiency of water removal by ethylcellulose addition was found to be less effective. Micrographic images revealed that ethylcellulose broke up the water-in-bitumen emulsions by flocculation and coalescence.

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 score0.033
Threshold uncertainty score0.336

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 head0.018
GPT teacher head0.234
Teacher spread0.217 · 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