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Record W2034809663 · doi:10.1002/cjce.22188

Effect of CO<sub>2</sub> on catalytic hydrotreatment of gas‐oil

2015· article· en· W2034809663 on OpenAlexvenueno aff
Stella Bezergianni, Vasiliki Dagonikou

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2015
Typearticle
Languageen
FieldEngineering
TopicCatalysis and Hydrodesulfurization Studies
Canadian institutionsnot available
Fundersnot available
KeywordsFlue-gas desulfurizationCatalysisChemistryHydrodesulfurizationHydrogenMethaneFraction (chemistry)PetroleumRaw materialChemical engineeringWaste managementOrganic chemistry

Abstract

fetched live from OpenAlex

The aim of this study is to investigate the effect of CO 2 on catalytic hydrotreatement of gas‐oil to evaluate the potential of catalytic co‐ hydroprocessing of petroleum fractions with liquid biomass. A total of six experiments were conducted under low (330 °C), mild (345 °C) and severe (360 °C) operating conditions employing straight run gas‐oil as the petroleum fraction feedstock. During three of these experiments CO 2 was artificially added to the reaction system to assess its impact on the associated catalytic reactions over a commercial CoMo/Al 2 O 3 catalyst. The dedicated experiments revealed a suspending role of CO 2 on hydro‐ desulfurization (HDS), hydro‐denitrogenation (HDN), and saturation reactions, which is attributed to the subsequent hydrogen partial pressure reduction of the reacting system caused by the competitive water gas‐shift and methane reforming reactions.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.600
Threshold uncertainty score0.401

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 head0.008
GPT teacher head0.194
Teacher spread0.187 · 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

Citations22
Published2015
Admission routes1
Has abstractyes

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