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Solvent Selection for Asphalt Particles Production of Canadian Oil Sands Bitumen

2012· article· en· W2392836546 on OpenAlexaboutno aff
Fan Meng, Zhiming Xu, Suoqi Zhao, Sun Xue-wen

Bibliographic record

VenueActa Petrolei Sinica(Petroleum Processing Section) · 2012
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsCyclopentanePentaneAsphalteneAsphaltOil sandsSolventSoftening pointChemistryNaphthaOrganic chemistryChemical engineeringMaterials scienceComposite materialPolymer chemistry

Abstract

fetched live from OpenAlex

Asphaltenes from Canadian oil sands bitumen were obtained by solvent precipitation with two mixed solvent systems,n-pentane+n-hexane mixed solvent and n-pentane+cyclopentane mixed solvent.Several analytical means were conducted to study the variation of asphaltene properties with the solvent changing,such as saturate,aromatic,resin and asphaltene compositions,elemental composition,average molecular structures and aromatic sheets stacking structures.The experiment results indicated that the yield of asphaltene could be remarkable reduced with the increase of n-hexane or cyclopentane proportion in the mixed solvent and the softening point of asphaltene increased correspondingly.When the n-pentane+cyclopentane mixed solvent was used with a small amount of cyclopentane in n-pentane,the softening point of asphaltene could meet the demand for asphalt spray granulation and the n-pentane+cyclopentane mixed solvent was suitable to be the solvent system in the asphalt particles production from Canadian oil sands bitumen.The n-pentane+cyclopentane mixed solvent containing about 10% cyclopentane could decrease the yield of deoiled asphalt by 4 percent and promote the softening point of asphalt by 10-12℃.Hence,nice asphalt particles could be produced,and the n-pentane+cyclopentane mixed solvent with 10% cyclopentane would be the right candidate solvent system for Canadian oil sands bitumen processing.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.506
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.021
GPT teacher head0.258
Teacher spread0.237 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

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