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Record W2321953558 · doi:10.1021/ef501341h

Viscosity Changes during Mild Oxidation of Oilsands-Derived Bitumen: Solvent Effects and Selectivity

2014· article· en· W2321953558 on OpenAlexaff
José L. García Zapata, Arno de Klerk

Bibliographic record

VenueEnergy & Fuels · 2014
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsAsphaltSelectivityViscositySolventChemistryChemical engineeringOrganic chemistryThermodynamicsMaterials scienceComposite materialCatalysisPhysics

Abstract

fetched live from OpenAlex

The low-temperature oxidation of oilsands bitumen was investigated to determine how viscosity was affected by oxidation and whether oxidative hardening could be suppressed by solvent dilution. This work was performed to support the development of an oxidative desulfurization process, but it could also find application in processes for bitumen recovery by in situ low-temperature oxidation. The experimental investigation was conducted at 140–200 °C and near atmospheric pressure with oilsands-derived bitumen, air, and mesitylene as the solvent. Solvent dilution decreased the bitumen viscosity through diluent action, but it did not suppress oxidative hardening of the bitumen. In fact, with the presence of a solvent, the bitumen viscosity increased more than by oxidation of bitumen on its own. This could be explained in terms of easier hydrogen abstraction from bitumen relative to the solvent, which increased the probability of addition reactions. The increase in viscosity with oxidation extent was also investigated, and apparently conflicting reports in the literature were reconciled. At a constant temperature, different periods of near constant viscosity increase with the increase in the oxygen consumption were identified. It was also found that, during the first free radical chain-propagation-dominated oxidation period, the extent of viscosity increase was different at different oxidation temperatures for the same level of O 2 consumption. Oxidative hardening is not just related to oxidation extent, but it is also affected by changes in oxidation selectivity because of the conditions at which the oxidation was performed.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.207
Teacher spread0.202 · 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 source (direct Gemma or distilled Codex), 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

Citations10
Published2014
Admission routes1
Has abstractyes

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