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Record W2334049094 · doi:10.1021/ef501128p

Visbreaking Oilsands-Derived Bitumen in the Temperature Range of 340–400 °C

2014· article· en· W2334049094 on OpenAlexafffundabout
Lin Wang, Ashley Zachariah, Shaofeng Yang, Vinay Prasad, Arno de Klerk

Bibliographic record

VenueEnergy & Fuels · 2014
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsUniversity of Alberta
FundersNatural Resources CanadaHelmholtz-Alberta Initiative
KeywordsAsphaltCokeAtmospheric temperature rangeChemistryViscosityVolume (thermodynamics)Fraction (chemistry)Yield (engineering)ThermodynamicsWork (physics)Analytical Chemistry (journal)Materials scienceChromatographyOrganic chemistryComposite material

Abstract

fetched live from OpenAlex

The low-temperature visbreaking of Canadian oilsands-derived bitumen was investigated. The objective was to determine the extent to which the fluidity of the bitumen can be improved by less-severe thermal conversion than normally employed industrially, while, at the same time, maintaining a high liquid yield. Most of the experimental work was conducted in the temperature range of 340–400 °C, although some data were also obtained at lower temperatures. It was possible to limit gas and coke formation and obtain a 96–97 wt % liquid yield, while decreasing the bitumen viscosity from ∼100 Pa s to 1 Pa s (measured at 40 °C). More remarkable was that viscosities of ∼3 Pa s could be obtained by just heating the bitumen to either 360 or 380 °C and then cooling it. The most plausible explanation for the rapid decrease in viscosity during low-temperature visbreaking was that there was a decrease in the effective volume fraction of the colloidal fraction. The viscosity change over time at constant temperature was complex, with at least one local minimum and maximum being observed. This aspect of the behavior could not yet be fully explained. Overall, it was found that the bitumen was reactive and that its thermal conversion behavior over the temperature range studied was comparable to that of a young crude oil, not a residuum.

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 score0.058
Threshold uncertainty score0.408

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 head0.007
GPT teacher head0.217
Teacher spread0.210 · 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

Citations43
Published2014
Admission routes3
Has abstractyes

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