MétaCan
Menu
Back to cohort
Record W2052896820 · doi:10.1002/aic.11825

Kinetic modeling of catalytic conversion of methylcyclohexane over USY zeolites: Adsorption and reaction phenomena

2009· article· en· W2052896820 on OpenAlexaff
Mustafa Al‐Sabawi, Hugo de Lasa

Bibliographic record

VenueAIChE Journal · 2009
Typearticle
Languageen
FieldEngineering
TopicCatalysis and Hydrodesulfurization Studies
Canadian institutionsWestern University
Fundersnot available
KeywordsMethylcyclohexaneCatalysisChemistryZeoliteAdsorptionIsomerizationFluid catalytic crackingChemical engineeringThermodynamicsMass transferKinetic energyHydrogenPhysical chemistryOrganic chemistryChromatography

Abstract

fetched live from OpenAlex

Abstract Catalytic conversion of cycloparaffins is a complex process involving competing reaction steps. To understand this process, FCC experiments using methylcyclohexane (MCH) on USY zeolite catalysts were carried out in the mini‐fluidized CREC riser simulator. Runs were developed under relevant FCC process conditions in terms of partial pressures of MCH, temperatures (450–550°C), contact times (3–7 s), catalyst‐oil mass ratios (5), and using fluidized catalysts. MCH overall conversions ranged between 4 to 16 wt %, with slightly higher conversions obtained using the larger zeolite crystallites. Moreover, it was found that MCH undergoes ring opening, protolytic cracking, isomerization, hydrogen transfer and transalkylation. A heterogeneous kinetic model for MCH conversion including thermal effects, adsorption and intrinsic catalytic reaction phenomena was established. Adsorption and kinetic parameters were determined, including the heat of adsorption (−40 kJ/mol), as well as thermal and primary catalytic intrinsic activation energies, which were in the range of 43–69 kJ/mol, and 50–74 kJ/mol, respectively. © 2009 American Institute of Chemical Engineers AIChE J, 2009

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.817
Threshold uncertainty score0.305

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.012
GPT teacher head0.224
Teacher spread0.212 · 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 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

Citations34
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueAIChE JournalSame topicCatalysis and Hydrodesulfurization StudiesFrench-language works237,207