MétaCan
Menu
Back to cohort
Record W2017564984 · doi:10.1021/ie034197q

Adsorption, Diffusion, and Reaction Phenomena on FCC Catalysts in the CREC Riser Simulator

2004· article· en· W2017564984 on OpenAlexaff
J. A. Atias, Hugo de Lasa

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2004
Typearticle
Languageen
FieldChemistry
TopicZeolite Catalysis and Synthesis
Canadian institutionsWestern University
Fundersnot available
KeywordsCatalysisAdsorptionProduct distributionDiffusionKinetic energyCrystalliteChemistryChemical engineeringSelectivityFluid catalytic crackingCrackingThermodynamicsMaterials sciencePhysical chemistryCrystallographyOrganic chemistryPhysics

Abstract

fetched live from OpenAlex

Two typical FCC catalysts with similar acidities and structural properties and different crystallite sizes, CAT-SC (0.4 μm) and CAT-LC (0.9 μm), are studied in a novel CREC riser simulator using 1,3,5-triisopropylbenzene. Catalytic and thermal runs allow for the development of a heterogeneous kinetic model and the assessment of intrinsic kinetic constants and adsorption and diffusional parameters. Analysis of 1,3,5-triisopropylbenzene conversions and product distribution helps establish the influence of intracrystallite diffusion as the controlling step at lower reaction temperatures (350−450 °C). Moreover, product distribution and selectivity differences between the CAT-SC and CAT-LC catalysts provide evidence of cracking reactions affected by hindered diffusion of the reactant and products.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.065
GPT teacher head0.302
Teacher spread0.237 · 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 source (direct Gemma or distilled Codex), 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

Citations17
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueIndustrial & Engineering Chemistry ResearchSame topicZeolite Catalysis and SynthesisFrench-language works237,207