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Ionic Liquid-Enhanced Solvent Extraction for Oil Recovery from Oily Sludge

2019· article· en· W2921512620 on OpenAlexafffund
Yuan Tian, W. B. McGill, Todd W. Whitcombe, Jianbing Li

Bibliographic record

VenueEnergy & Fuels · 2019
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of Northern British Columbia
FundersFisheries and Oceans CanadaNatural Sciences and Engineering Research Council of CanadaUniversity of Northern British Columbia
KeywordsSolventExtraction (chemistry)ChemistryChromatographyIonic liquidSewage sludgeFraction (chemistry)CyclohexaneSewage treatmentOrganic chemistryWaste management

Abstract

fetched live from OpenAlex

An ionic liquid (IL), 1-ethyl-3-methyl-imidazolium tetrafluoroborate ([Emim][BF4]), was investigated for its effectiveness on enhancing oil recovery from hazardous crude oil tank bottom sludge using a solvent. A range of solvent (cyclohexane)/sludge ratio (2–8 mL/g), shaking speed (100–400 rpm), extraction duration (10–120 min), and IL/sludge ratio (0.25–1.0 mL/g) were examined. The addition of IL (i.e., 1 mL/g of IL/sludge ratio) increased total petroleum hydrocarbon (TPH) recovery by 9.4% (from 84.4 ± 2.4 to 93.8 ± 2.3% at the solvent/sludge ratio of 8 mL/g). An orthogonal experimental design was subsequently applied to optimize extraction conditions. The use of IL (i.e., 0.1 mL/g of IL/sludge ratio) with the solvent yielded higher TPH recovery (above 95%) at shorter extraction duration (10 min), lower solvent/sludge ratio (4:5 mL/g), and lower energy consumption (100 rpm). The recovered oil had similar calorific value but a higher F3 fraction compared with crude oil. The results suggested that the IL-enhanced solvent extraction with lower solvent consumption is an effective approach for oily sludge treatment.

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 categoriesMeta-epidemiology (narrow)
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 score0.139
Threshold uncertainty score1.000

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 head0.008
GPT teacher head0.227
Teacher spread0.219 · 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.

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

Citations63
Published2019
Admission routes2
Has abstractyes

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