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Record W1991205242 · doi:10.1021/ie0506825

Catalytic Desulfurization of Gasoline via Dehydrosulfidation

2006· article· en· W1991205242 on OpenAlexaffabout
Hugo de Lasa, R. Hernandez Enriquez, Gabriela Marta Tonetto

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2006
Typearticle
Languageen
FieldEngineering
TopicCatalysis and Hydrodesulfurization Studies
Canadian institutionsWestern University
FundersConsejo Nacional de Ciencia y TecnologíaConsejo Nacional de Investigaciones Científicas y Técnicas
KeywordsCatalysisFlue-gas desulfurizationGasolineChemistryOctane ratingSulfurMethanolHydrogen sulfideOctaneDesorptionInorganic chemistryAmmoniaChemical engineeringOrganic chemistryAdsorption

Abstract

fetched live from OpenAlex

This study presents a potentially attractive route for the desulfurization of gasoline via catalytic dehydrosulfidation, removal of hydrogen sulfide from sulfur-containing molecules . The proposed study involves thermodynamic calculations and experimentation in a fluidized riser simulator at the Chemical Reaction Engineering Centre (CREC) at the University of Western Ontario. A ZSM-5 catalyst was used because of its demonstrated performance for the dehydration of methanol, a parent reaction with an expected similar reaction network. The catalyst was characterized using several techniques, including (a) BET (surface area), (b) ammonia temperature-programmed desorption (concentration of acid sites), and (c) SEM-EDX (sodium content) at various stages of catalyst preparation. The catalytic dehydrodesulfidation reaction was studied using a model compound (ethyl mercaptan, EM) in n -octane ( n -C 8 ) to represent sulfur-contaminated gasoline. The experimental data obtained were successfully fitted using a kinetic model representing the rate of disappearance of the sulfur-containing species.

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 score0.180
Threshold uncertainty score0.804

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 studies0.0000.000
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 head0.042
GPT teacher head0.274
Teacher spread0.233 · 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

Citations23
Published2006
Admission routes2
Has abstractyes

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