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Record W2773479731 · doi:10.4236/jpee.2017.512011

Desulphurization of Transportation Fuels by Per-Formic Acid Oxidant Using MoOx Loaded on ZSM-5 Catalyst

2017· article· en· W2773479731 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Power and Energy Engineering · 2017
Typearticle
Languageen
FieldEngineering
TopicCatalysis and Hydrodesulfurization Studies
Canadian institutionsnot available
FundersUniversity of Alberta
KeywordsPerformic acidNaphthaFlue-gas desulfurizationFormic acidChemistryThiopheneCatalysisDibenzothiopheneNuclear chemistryZSM-5SulfurFuel oilZeoliteOrganic chemistryWaste management

Abstract

fetched live from OpenAlex

Desulphurization of model and real oil samples was investigated using performic acid as oxidant assisted by air as co-oxidant. The catalysts used were Mo-oxide supported on ZSM-5 zeolite, which was synthesized in the laboratory and characterized by FT-IR, XRD, SEM and SSA analysis. In case of model oil, the optimum condition determined for complete oxidation of all the model compounds including thiophene, DBT and 4,6-DMDBT were; 60?C, 60 min, ambient pressure and air flow rate of 100 mL/min. The oxidation reactivity decreased from 4,6-DMDBT to DBT and thiophene, which was found to follow pseudo first order kinetics. The real oil sample used in the study included untreated naphtha (NP), light gas oil (LGO), heavy gas oil (HGO) and Athabasca bitumen (Bit.). In case of NP and LGO the sulfur removal of above 78% was attained whereas in case of HGO and Bit. samples about 60% of desulfurization was achieved.

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.

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 score0.217
Threshold uncertainty score0.530

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 head0.007
GPT teacher head0.204
Teacher spread0.197 · 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