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Record W2049313489 · doi:10.2118/2005-045-ea

An Alternative Method for the Removal of Sulphur From FCC Gasoline

2005· article· en· W2049313489 on OpenAlexaffabout
J.A. Hendsbee, Ronald W. Thring, David G. Dick, C. Sieben

Bibliographic record

VenueCanadian International Petroleum Conference · 2005
Typearticle
Languageen
FieldEngineering
TopicCatalysis and Hydrodesulfurization Studies
Canadian institutionsHusky Energy (Canada)University of Northern British Columbia
Fundersnot available
KeywordsGasolineSulfurComputer scienceEnvironmental scienceProcess engineeringWaste managementMetallurgyMaterials scienceEngineering

Abstract

fetched live from OpenAlex

Abstract This study is being performed as part of a graduate thesis project at the University of Northern British Columbia. We are attempting to develop an alternative method for removing sulfur compounds from the fluid catalytically cracked stream of gasoline (FCC gasoline). Canada recently developed new regulations for the amount of total sulfur in fuel, as of January 1st, 2005, thereby limiting the total sulfur to 30 ppmw. This paper reports on our work to date using a Raney-nickel type catalyst for the removal of sulfur-containing compounds from FCC gasoline. We will report on the successful results we have achieved to date including experiments where temperature and reaction time were varied. Raney-type nickel is activated with an alkaline solution, then reacted with the FCC gasoline to form a nickel sulfide precipitate. Our most promising results indicate a 60% drop in total sulfur concentration in the treated FCC gasoline. This reaction occurs at ambient temperatures and pressures and is currently being performed on a laboratory scale. The samples are analyzed using UV Fluorescence Spectroscopy in order to determine total sulfur content. Introduction The removal of sulfur from fossil fuels has become a major concern. Currently, the most common way of removing sulfur from fossil fuels is hydrotreating. However, it is expensive. As of January 1st 2005, Canada legislated that the sulfur content in gasoline be lowered to 30 ppmw from 150 ppmw with the hopes of further lowering the sulfur levels in future years. The purpose of this project was to develop an alternative method for removing sulfur from gasoline specifically, the fluid catalytically cracked gasoline (FCC gasoline). Raney-type nickel is prepared by reacting an alkaline solution with a nickel-aluminum alloy1. The alkaline solution reaction is typically carried out by the addition of a sodium hydroxide solution. This leaching process causes the nickelaluminum alloy to be more porous, have a higher surface area, and become activated2. The activation process oxidizes the aluminum and generates hydrogen gas, which activates the nickel portion of the catalyst3. (Equation 1) (Available in full paper) Some of the hydrogen remains adsorbed on the nickel making it a low temperature hydrogenation catalyst. Therefore, nickel catalysts have been used widely in hydrogenation, hydrotreating, and steam-reforming reactions4. In particular, Raney-type nickel has been used in industry for the hydrogenation of organic compounds2 and the determination of trace amounts of sulfur in organic mixtures5. There were several methods developed to determine trace amounts of sulfur in petroleum distillates6. These methods were previously used in laboratory analysis of sulfur levels in fuels. However, there has been more recent work done with Raneytype nickel for use in fuel cells and for developing hydrogen from biomass7. The Raney-type nickel has never been attempted for desulfurization of FCC gasoline. Beigi et al6 determined that at lower temperatures and with newly prepared catalyst the desulfurization occurs as follows. (Equation 1) (Available in full paper) In order to determine the effectiveness of Raney-type nickel on desulfurization of FCC gasoline, Raney-type nickel was first prepared and used in preliminary experiments.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.628
Threshold uncertainty score0.989

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 head0.023
GPT teacher head0.276
Teacher spread0.253 · 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 designSimulation or modeling
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

Citations0
Published2005
Admission routes2
Has abstractyes

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