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Record W2508129102 · doi:10.1002/cjce.22636

Oxidative desulphurization of model fuel by in situ produced hydrogen peroxide on palladium/active carbon

2016· article· en· W2508129102 on OpenAlexvenueno aff
Qing Wang, Shengqiang Wang, Hongbing Yu

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2016
Typearticle
Languageen
FieldEngineering
TopicCatalysis and Hydrodesulfurization Studies
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsHydrogen peroxideChemistryAdsorptionSulfurCarbon fibersPalladiumDehydrogenationPeroxideAnhydrousCatalysisHydrogenInorganic chemistryOrganic chemistryMaterials science

Abstract

fetched live from OpenAlex

Abstract Thiophenic compounds are considered one of the major obstacles in deep desulphurization of transportation gasoil. In this paper, a single‐stage reactor, in which the induction of hydrogen peroxide, oxidation of thiophenes, and adsorption of sulphones from model fuel was demonstrated in one single step at mild temperatures. In our proposed mechanism, the removal of thiophenes from model fuel undergoes three stages: 2‐propanol dehydrogenation and in situ generation of hydrogen peroxide, oxidative desulphurization, and the adsorption of sulphones on active carbon. Palladium/active carbon (Pd/C) was not only used to catalyze the production of hydrogen peroxide, but also guarantees efficiency in the adsorption of sulphones from the oil phase and aqueous phase owing to its large specific surface area and pore volume. Thus, the goal to get ultra‐low sulphur fuel was well achieved under optimal conditions after almost all the sulphones had entered into the pores of active carbon and stayed in the adsorbent. Accumulation of sulphur in active carbon inhibits further desulphurization operation. Washing with excessive anhydrous ethanol, the efficiency of Pd/C was almost fully recovered.

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 score0.170
Threshold uncertainty score0.371

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 head0.009
GPT teacher head0.185
Teacher spread0.176 · 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

Citations4
Published2016
Admission routes1
Has abstractyes

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