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Record W6966397767 · doi:10.48336/0ngv-2b59

Extractive desulfurization of fuel oils using ionic liquids

2022· article· en· W6966397767 on OpenAlexaff

Bibliographic record

VenueMemorial University Research Repository (Memorial University) · 2022
Typearticle
Languageen
FieldEngineering
TopicCatalysis and Hydrodesulfurization Studies
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsFlue-gas desulfurizationDibenzothiopheneIonic liquidBenzothiopheneSulfurThiopheneDecompositionSulfatePyridinium

Abstract

fetched live from OpenAlex

The sulphur content of transportation fuels must be reduced in high-sulphur crude oil by desulfurization. Traditionally, desulfurization methods have required harsh reaction conditions and are not very effective at removing refractory sulfur compounds such as benzothiophene (BT), dibenzothiophene (DBT) and 4,6-dimethyldibenzothiophene (4,6-DMDBT). Alternative methods, such as ionic liquid (IL)-mediated desulfurization, are both effective and environmentally friendly. Isolants ideal for desulfurization are required to be recyclable, insoluble in oil, selective for compounds containing sulphur, and eco-friendly. These properties are offered by ILs based on pyridinium. Therefore, the primary objectives of this thesis were to: (1) investigate the properties of N-butyl-pyridinium tetrafluoroborate ([BPy][BF₄]) and N-carboxymethyl pyridinium hydrogen sulfate ([CH₂COOHPy][HSO₄]); (2) understand the effects of reaction parameters (temperature, volume ratio, oxidant dosage, quantities of sulphur compound extracted, etc.) on desulfurization efficiency; (3) clarify the interactions between ILs and sulphur compounds; and (4) investigate the recycling and regeneration of ILs. Experimental results showed that the desulfurization efficiency of [BPy][BF₄] increased with temperature and oxidant dosage and declined with IL to fuel volume ratio. It was observed that at 30゚C, 1:1 ration of IL to model fuel [BPy][BF₄] could remove up to 79% of DBT in 80 min in the presence of oxidant H₂O₂. [CH₂COOHPy] [HSO₄] was found to be more effective in desulfurization, capable of removing up to 99.9% of DBT in the presence of oxidant H₂O₂ within 40 min at 25゚C, 1:1 ratio of IL to model fuel. The recycled [CH₂COOHPy][HSO₄] marginally lost effectiveness after 8 recycles. It was also found that the effectiveness of both ILs was lower in real diesel compared to model fuels. Computational density functional theory-based structural analysis revealed that there were two types of possible π-π interactions between [BPy] [BF₄] and DBT/DBTO₂, resulting in the formation of complexes with different geometries. [CH₂COOHPy][HSO₄] also exhibits similar potential π−π interactions with DBT/DBTO₂. Moreover, both ILs undergo the same oxidative mechanism of desulfurization, as they involve π-π interactions and hydrogen bonds.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
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 score0.424
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.033
GPT teacher head0.253
Teacher spread0.219 · 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.

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

Citations2
Published2022
Admission routes1
Has abstractyes

Explore more

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