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Record W2036306818 · doi:10.1021/ef801005m

Effect of Hydrogen Purity on Hydroprocessing of Heavy Gas Oil Derived from Oil-Sands Bitumen

2009· article· en· W2036306818 on OpenAlexaff
Majak Mapiour, Ajay K. Dalai, John Adjaye

Bibliographic record

VenueEnergy & Fuels · 2009
Typearticle
Languageen
FieldEngineering
TopicCatalysis and Hydrodesulfurization Studies
Canadian institutionsSyncrude (Canada)University of Saskatchewan
Fundersnot available
KeywordsHydrodenitrogenationChemistrySpace velocityCatalysisMethaneHydrogenOil sandsHydrodesulfurizationDeoxygenationDiesel fuelTetralinHydrocarbonAsphaltOrganic chemistryMaterials scienceSelectivityComposite material

Abstract

fetched live from OpenAlex

The effect of hydrogen purity on hydroprocessing of heavy gas oil (HGO) was studied in a trickle bed reactor over a commercial Ni−Mo/γ-alumina catalyst. Methane was used as a diluent for the hydrogen stream, and its effect on the catalyst performance was compared to that of helium, which is inert toward the catalyst. Furthermore, a deactivation study was conducted over a period of 66 days, during which the catalyst was subjected to H 2 purity ranging from 95 to 75% (with the rest methane); no significant deterioration in the hydroprocessing activities of the catalyst was observed. Therefore, it was concluded that methane was inert toward a commercial Ni−Mo/γ-alumina catalyst. However, its presence resulted in hydrogen partial pressure reduction, which in turn led to a decrease in hydrodesulphurization (HDS), hydrodenitrogenation (HDN), hydrodearomatization (HDA) conversions. This reduction can be offset by increasing the total pressure of the system. HDS, HDN, HDA, and mild hydrocracking (MHC) conversions were studied. Also determined were cetane index, density, aniline point, diesel index, and fractional distribution of the products. The temperature and liquid hourly space velocity (LHSV) were set constant at 380 °C and 1 h −1, respectively. Pressure and gas/oil ratio ranges were 7.2−10.1 MPa and 400−1270 mL/mL, respectively. The hydrogen purity was varied in the range of 0−100 vol % (with the rest methane or helium).

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 score0.124
Threshold uncertainty score0.755

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.006
GPT teacher head0.214
Teacher spread0.209 · 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

Citations27
Published2009
Admission routes1
Has abstractyes

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