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Record W2021175875 · doi:10.2118/06-11-06

Raney Nickel for the Desulphurization of FCC Gasoline

2006· article· en· W2021175875 on OpenAlexaffabout
J.A. Hendsbee, Ronald W. Thring, David G. Dick

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2006
Typearticle
Languageen
FieldEngineering
TopicCatalysis and Hydrodesulfurization Studies
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsGasolineSulfurNickelRaney nickelSulfideFlue-gas desulfurizationChemistryHydrodesulfurizationNickel sulfideMetallurgyInorganic chemistryCatalysisMaterials scienceOrganic chemistry

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 sulphur compounds from the fluid catalytically cracked stream of gasoline (FCC gasoline). As of January 1, 2005, Canada developed new regulations for the amount of total sulphur in fuel, thereby limiting the total sulphur to 30 ppmw. This paper reports on our work using Raney nickel for the removal of sulphur-containing compounds from FCC gasoline. Raney nickel is activated with an alkaline solution, then reacted with the FCC gasoline to form a nickel sulfide precipitate. Simply by varying the reaction time, a maximum reduction of 80% sulphur concentration can be seen at 60 min. Similarly, by varying the temperature, a maximum reduction of 99% sulphur concentration was obtained at a reaction temperature of 50 °C. Finally, sequential reaction experiments indicated a maximum reduction in sulphur concentration of 97% in the treated FCC gasoline using two consecutive additions of Raney nickel. These reactions are being performed on a laboratory scale but indicate that Raney nickel is very effective at removing sulphur from FCC gasoline. Introduction The removal of sulphur from fossil fuels has become a major concern. Currently, the most common way of removing sulphur from fossil fuels is by hydrotreating. However, it is an expensive process. As of January 1, 2005, Canada legislated that the sulphur content in gasoline be lowered to 30 ppmw from 150 ppmw with the hopes of further lowering the sulphur levels in future years. The purpose of this project was to develop an alternative method for removing sulphur from gasoline, specifically, fluid catalytically cracked gasoline (FCC gasoline) Raney nickel is one of the most common metal catalysts and was discovered by Murray Raney in 1927. In general, Raney nickel is comprised of sponge-like particles and it is this porous structure that makes Raney nickel a high capacity catalyst or rapid reactant for the removal of sulphur(1). Raney nickel is prepared by reacting an alkaline solution with a nickel-aluminum alloy(1). The activation is typically carried out by the addition of a sodium hydroxide solution. This leaching process causes the nickel-aluminum (Ni-Al) alloy to be more porous, have a higher surface area, and become activated(2). The activation process oxidizes the aluminum and generates hydrogen gas, which activates the nickel portion of the catalyst(3). Equation (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 in steam-reforming reactions(4). In particular, Raney nickel has been used in industry for the hydrogenation of organic compounds(2) and the determination of trace amounts of sulphur in organic Mixtures(5). There were several methods developed to determine trace amounts of sulphur in petroleum distillates(6). These methods were previously used in the laboratory analysis of sulphur levels in fuels.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.741
Threshold uncertainty score0.975

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.005
GPT teacher head0.184
Teacher spread0.179 · 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 designNot applicable
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
Published2006
Admission routes2
Has abstractyes

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