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Record W1997994076 · doi:10.1080/10916460601054297

Dependence of Molecular Kinetics of Asphaltene Cracking on Chemical Composition

2007· article· en· W1997994076 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenuePetroleum Science and Technology · 2007
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsAsphalteneCrackingAlkylReactivity (psychology)KineticsChemistryHydrocarbonHydrogenChemical engineeringOrganic chemistryThermodynamicsPhysics

Abstract

fetched live from OpenAlex

Abstract Asphaltenes from Iranian Light, Khafji and Maya were cracked in batch reactors at 350, 370, 390, 410, and 430°C under hydrogen to produce liquid products for kinetic analysis. The cracking kinetics of the asphaltenes and their intermediates were analyzed on a total molar basis, to avoid the assumptions inherent in lumped kinetics. The overall reactivity of the three asphaltenes was similar for reaction times from 1 to 37 min. The behavior of Khafji was distinct in its initial high reactivity of sulfur species, while the high yield of hydrocarbon gases from Iranian Light was likely due to the poly-alkyl side chains of the aromatic rings. The apparent first order activation energies were in between 170 and 255 KJ/mol. The activation energies were in the sequence Iranian Light > Maya > Khafji. Keywords: asphaltenechemical structurecrackingkinetic modelselectivity ACKNOWLEDGMENTS The authors acknowledge the financial support of Idemitsu Kosan, the New Energy and Industrial Technology Development Organization (NEDO) of Japan through international collaborative research and development project. Many helpful conversations with Ryuzo Tanaka, Shinya Sato, and Toshi Takanohashi are gratefully acknowledged. Current address for Samina Rahmani: National Centre for Upgrading Technology, Devon, Alberta. Notes a CitationTanaka et al. (2003). b CitationZhang et al. (2005). a Errors are standard error of the slope from Figure 5 b Data from CitationZhao et al. (2001).

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.

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 score0.022
Threshold uncertainty score0.396

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.006
GPT teacher head0.250
Teacher spread0.243 · 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