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Record W4409706802 · doi:10.3390/catal15050409

Evaluation of Vanadium Oxide Nanocatalysts over Graphene for Propylene Production Through Oxidative Propane Dehydrogenations

2025· article· en· W4409706802 on OpenAlexaff
Robabeh Mousavi, Armin Fazlinezhad, Abdollah Fallah Shojaeı, Alimorad Rashidi, Moslem Fattahi

Bibliographic record

VenueCatalysts · 2025
Typearticle
Languageen
FieldChemical Engineering
TopicCatalysis and Oxidation Reactions
Canadian institutionsUniversity of Alberta
FundersUniversity of Guilan
KeywordsPropaneNanomaterial-based catalystChemistryVanadiumPropeneOrganic chemistryCatalysis

Abstract

fetched live from OpenAlex

This study reports an efficient and low-cost hydrothermal method for synthesizing vanadium oxide/graphene nanocatalysts. Field-emission scanning electron microscopy (FESEM) revealed the formation of nanostructured catalysts with consistent and directional shapes, as confirmed by X-ray diffraction (XRD). Fourier transform infrared (FTIR) spectroscopy indicated the presence of V2O5 and graphene, highlighting their bonds and structures. Thermogravimetric analysis (TGA) identified three stages of weight loss in the nanocatalysts, corresponding to water molecule evaporation, decomposition of residual organics, and the formation of yellow vanadium pentoxide particles due to the oxidation of vanadium V4+. Gas chromatography analysis from 450 °C to 600 °C showed that ethylene selectivity increased with temperature, while propylene selectivity showed the opposite trend. The effectiveness of these nanocatalysts was assessed in the oxidative dehydrogenation of propane using temperature programmed reduction. The approach of graphene-based vanadium oxide nanostructures will open up a new insight into the fabrication of high-performance catalysts.

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)0.001
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 score0.033
Threshold uncertainty score0.843

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.029
GPT teacher head0.309
Teacher spread0.280 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

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