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Record W2317430215 · doi:10.1002/cjce.22477

Role of binary solvent and ionic liquid in bitumen recovery from oil sands

2016· article· en· W2317430215 on OpenAlexvenueno aff
Hong Sui, Zhang Jianqiang, Yipu Yuan, Lin He, Yun Bai, Xingang Li

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2016
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsHeptaneOil sandsEthyl acetateAsphaltSolventExtraction (chemistry)DissolutionChemistryIonic liquidButyl acetateFractionationChemical engineeringOrganic chemistryChromatographyMaterials scienceComposite material

Abstract

fetched live from OpenAlex

A binary solvent of ethyl acetate and n ‐heptane was made and applied together with ionic liquids (ILs, 1‐ethyl‐3‐methyl imidazolium tetrafluoroborate ([Emim]BF 4 )) to extract bitumen from oil sands at ambient conditions. Results of bottle tests show that the bitumen recovery is highly dependent on the volume ratio of ethyl acetate to n ‐heptane. The maximum recovery was obtained at the ethyl acetate‐to‐ n ‐heptane ratio of 3:6. With external addition of ILs, an additional improvement of ∼10 % of bitumen recovery was observed (from 83 to 93 % at the ethyl acetate‐to‐ n ‐heptane ratio of 3:6). Based on the intensive investigation of key operational parameters (i.e. ILs‐to‐solvent ratio, agitation time, and conditioning time), a set of recommended extraction conditions were proposed to maximize the bitumen recovery. Further fractionation of the extracted bitumen together with FTIR and SEM detection on the residual solids indicated that ILs addition could increase the dissolution of bitumen fractions into solvents, while reducing the entrapment of fine particles in the solvents. The improvement of bitumen recovery by ILs addition was attributed to the enhancement of the liberation of bitumen components from mineral solids surfaces during oil sands solvent extraction. However, the asphaltenes were observed to be rejected during processing due to their accumulation at the oil‐ILs interface as a film.

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 score0.006
Threshold uncertainty score0.315

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 head0.004
GPT teacher head0.168
Teacher spread0.164 · 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

Citations22
Published2016
Admission routes1
Has abstractyes

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