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Record W2313900386 · doi:10.1021/ef300854r

Depolarized Light Scattering for Study of Heavy Oil and Mesophase Formation Mechanisms

2012· article· en· W2313900386 on OpenAlexaff
S. Reza Bagheri, Murray R. Gray, William C. McCaffrey

Bibliographic record

VenueEnergy & Fuels · 2012
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMesophaseNucleationScatteringSmall-angle X-ray scatteringMaterials scienceChemical engineeringChemical physicsCrackingAsphalteneLight scatteringDynamic light scatteringMicelleNanoscopic scaleTexture (cosmology)Phase (matter)ChemistryComposite materialNanotechnologyOrganic chemistryNanoparticleOpticsAqueous solution

Abstract

fetched live from OpenAlex

Mesophase formation in heavy oil fractions during thermal cracking was studied by a depolarized light scattering technique using a high temperature/high pressure stirred hot-stage reactor. The advantage of this technique relies on its ability to track the ordering of components at the molecular and nanoscale prior to the onset of observable mesophase. A mechanism for mesophase formation in pitches has been suggested based on the evaluation of the previous models for mesophase formation with the scattering results. The results suggest that mesophase formation does not follow a typical phase separation or nucleation process but instead is a result of the homogeneous self-assembly of planar aromatic molecules into clusters and finally spherical submicrometer domains that coalesce to form the final texture of micrometer-scale mesophase spheres. The scattering behavior of asphaltenes suggests that this material is more aggregated than the maltenes, at temperatures up to 350 °C. This new technique can be used in conjunction with traditional hot-stage microscopy to study the mechanisms of mesophase formation and predict the onset of mesophase formation during the cracking of heavy oil.

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 score0.029
Threshold uncertainty score0.387

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 head0.013
GPT teacher head0.243
Teacher spread0.231 · 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

Citations24
Published2012
Admission routes1
Has abstractyes

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