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Record W3016680398 · doi:10.3390/catal10040418

Propane Oxidative Dehydrogenation on Vanadium-Based Catalysts under Oxygen-Free Atmospheres

2020· article· en· W3016680398 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCatalysts · 2020
Typearticle
Languageen
FieldChemical Engineering
TopicCatalysis and Oxidation Reactions
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDehydrogenationCatalysisVanadiumPropaneOxygenInorganic chemistryChemistryStoichiometryMaterials scienceOrganic chemistry

Abstract

fetched live from OpenAlex

Catalytic propane oxidative dehydrogenation (PODH) in the absence of gas phase oxygen is a promising approach for propylene manufacturing. PODH can overcome the issues of over-oxidation, which lower propylene selectivity. PODH has a reduced environmental footprint when compared with conventional oxidative dehydrogenation, which uses molecular oxygen and/or carbon dioxide. This review discusses both the stoichiometry and the thermodynamics of PODH under both oxygen-rich and oxygen-free atmospheres. This article provides a critical review of the promising PODH approach, while also considering vanadium-based catalysts, with lattice oxygen being the only oxygen source. Furthermore, this critical review focuses on the advances that were made in the 2010–2018 period, while considering vanadium-based catalysts, their reaction mechanisms and performances and their postulated kinetics. The resulting kinetic parameters at selected PODH conditions are also addressed.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.060
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.022
GPT teacher head0.233
Teacher spread0.211 · 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