MétaCan
Menu
Back to cohort
Record W4308284242 · doi:10.1002/cjce.24758

Kinetic modelling of 1, 3, 5‐triisopropylbenzene catalytic cracking using a <scp>CREC</scp> Riser Simulator emulating <scp>FCC</scp> operation: The <scp>C/O</scp> ratio effect

2022· article· en· W4308284242 on OpenAlexafffundvenue
Cesar Medina‐Pedraza, Abdualkaber Alkhlel, Hugo de Lasa

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2022
Typearticle
Languageen
FieldEngineering
TopicCatalysis and Hydrodesulfurization Studies
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsKineticsFluid catalytic crackingCatalysisCokeKinetic energyCrackingChemistryBenzeneChemical engineeringMaterials scienceThermodynamicsSimulationOrganic chemistryEngineeringPhysics

Abstract

fetched live from OpenAlex

Abstract The present study establishes the suitability of a kinetic model for the catalytic cracking of 1, 3, 5‐triisopropylbenze (TIPB) using the data obtained in the Chemical Reactor Engineering Centre (CREC) Riser Simulator. The postulated kinetic model accounts for both the TIPB and the various major products formed experimentally, such as: 1, 3‐diisopropylbenzene, isopropylbenzene, benzene, propylene, and coke. It is proven that the proposed kinetics is suitable to describe the chemical concentration changes in a CREC Riser Simulator at various reaction times, partial pressures, temperatures, and C/O (catalyst/feedstock) ratios. It is demonstrated that the proposed kinetics simulates well the experimental data from the CREC Riser Simulator, including an experimentally observed C/O optimum ratio. It is anticipated that this type of kinetic model, accounting for intrinsic kinetics, coke deactivation, and diffusional phenomena, could have significant value in establishing the influence of catalyst solid fluxes, at set hydrocarbon feed fluxes, in both industrial riser and downer fluid catalytic cracking (FCC) units.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.016
GPT teacher head0.204
Teacher spread0.188 · 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 designSimulation or modeling
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

Citations1
Published2022
Admission routes3
Has abstractyes

Explore more

Same venueThe Canadian Journal of Chemical EngineeringSame topicCatalysis and Hydrodesulfurization StudiesFrench-language works237,207