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Record W4401328085 · doi:10.3390/catal14080505

A Kinetic Model for Catalytic N-Butane Oxidative Dehydrogenation under Oxygen-Free Reaction Conditions in a Fluidized CREC Riser Simulator

2024· article· en· W4401328085 on OpenAlexafffund
Abdulhamid Bin Sulayman, Hugo de Lasa

Bibliographic record

VenueCatalysts · 2024
Typearticle
Languageen
FieldChemical Engineering
TopicCatalysis and Oxidation Reactions
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of CanadaMinistry of Higher Education and Scientific Research
KeywordsDehydrogenationCatalysisButaneKinetic energyChemistryDesorptionOlefin fiberResidence time (fluid dynamics)SelectivityFluidized bedThermodynamicsMaterials scienceChemical engineeringPhysical chemistryOrganic chemistryAdsorptionPhysics

Abstract

fetched live from OpenAlex

This study considers the development of a kinetic model for the n-butane oxidative dehydrogenation (ODH) to C4-olefins using a VOx/MgO−γAl2O3 catalyst. The prepared catalyst contained 5 wt% V on an MgO modified γAl2O3 support. The developed catalyst exhibited both weak and medium acid sites, as revealed by NH3-temperature-programmed desorption. TPR/TPO analyses also indicated that 73% of the loaded VOx was reducible. Kinetic experiments were conducted in a fluidized CREC Riser Simulator at temperatures ranging from 475–550 °C and residence times of 5–20 s. An optimal C4-olefin selectivity of 86% was achieved at 500 °C and 10 s, with this selectivity then decreasing at higher temperatures and longer residence times. The kinetic model developed involved a Langmuir–Hinshelwood-type of kinetics that incorporated cracking, oxydehydrogenation, and complete oxidation reactions. Model parameters were determined by fitting experimental data with kinetic parameters established with narrow 95% confidence intervals and low cross-correlation.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.768
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)0.0000.000

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 head0.021
GPT teacher head0.282
Teacher spread0.261 · 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

Citations3
Published2024
Admission routes2
Has abstractyes

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