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Record W2561737163 · doi:10.1155/2016/3752484

Effect of Particle Size on the HDS Activity of Molybdenum Sulfide

2016· article· en· W2561737163 on OpenAlexafffund
Carola Contreras, Fernanda Isquierdo, Pedro Pereira‐Almao, Carlos E. Scott

Bibliographic record

VenueJournal of Nanotechnology · 2016
Typearticle
Languageen
FieldEngineering
TopicCatalysis and Hydrodesulfurization Studies
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaAlberta InnovatesChina National Offshore Oil CorporationUniversity of Calgary
KeywordsMaterials scienceHydrodesulfurizationMolybdenumParticle sizeSulfideChemical engineeringCatalysisParticle (ecology)PolyvinylpyrrolidoneRaw materialNanoparticleX-ray photoelectron spectroscopyRefineryVacuum distillationMetallurgyNanotechnologyOrganic chemistrySulfurDistillationPolymer chemistryChemistry

Abstract

fetched live from OpenAlex

More than half of the total world oil reserves are heavy oil, extra heavy oil, and bitumen; however their catalytic conversion to more valuable products is challenging. The use of submicronic particles or nanoparticles of catalysts suspended in the feedstock may be a viable alternative to the conversion of heavy oils at refinery level or downhole (in situ upgrading). In the present work, molybdenum sulfide (MoS 2 ) particles with varying diameters (10000–10 nm) were prepared using polyvinylpyrrolidone as capping agent. The prepared particles were characterized by DLS, TEM, XRD, and XPS and tested in the hydrodesulfurization (HDS) of a vacuum gas oil (VGO). A correlation between particle size and activity is presented. It was found that particles with diameters around 13 nm show double the HDS activity compared with the material with micrometric particle sizes (diameter ≈ 10,000 nm).

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)0.001
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 score0.018
Threshold uncertainty score0.141

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.006
GPT teacher head0.222
Teacher spread0.216 · 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

Citations11
Published2016
Admission routes2
Has abstractyes

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