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Record W2890298838 · doi:10.1021/acs.iecr.8b02427

Catalytic Cracking of Hydrocarbons in a CREC Riser Simulator Using a Y-Zeolite-Based Catalyst: Assessing the Catalyst/Oil Ratio Effect

2018· article· en· W2890298838 on OpenAlexafffund
Abdualkaber Alkhlel, Hugo de Lasa

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2018
Typearticle
Languageen
FieldChemistry
TopicZeolite Catalysis and Synthesis
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCokeCatalysisCrackingZeoliteFluid catalytic crackingYield (engineering)Chemical engineeringRaw materialMaterials scienceAdsorptionChemistryMetallurgyOrganic chemistryEngineering

Abstract

fetched live from OpenAlex

The present study investigates the effects of the changes of the catalyst to feedstock ratio (C/O) on FCC cracking using a Y-zeolite-based catalyst. Experiments are developed in a CREC Riser Simulator. This bench-scale mini-fluidized batch unit mimics the operating conditions of large-scale FCC units as follows: It uses temperatures ranging from 510 to 550 °C and reaction times from 3 7 s. For every experiment, 0.2 g of 1,3,5-TIPB is contacted with a 0.12–1g catalyst amount. This is done to achieve a C/O ratio in the range of 0.6–5. Experiments show the effects of increasing the C/O ratio on 1,3,5-TIPB conversion, coke formation, and product selectivity. On this basis, a mechanism involving single catalyst sites for cracking and two sites for coke formation is considered. Coke formation is postulated as an additive process involving coke precursor species, which are either adsorbed on sites in the same particle or adsorbed in close sites in different particles. The proposed mechanism helps explain the results obtained, introducing a rationale for the selection of optimum C/O ratios to yield the highest possible 1,3,5-TIPB conversions with controlled amounts of coke formation. It is anticipated that the findings of this study will have a significant influence on the selection of an optimum C/O ratio for the design and operation of the most advanced FCC risers and downers.

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)0.003
metaresearch head score (Gemma)0.005
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.163
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
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 head0.075
GPT teacher head0.355
Teacher spread0.279 · 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

Citations29
Published2018
Admission routes2
Has abstractyes

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