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Record W2055785576 · doi:10.2202/1542-6580.1338

Catalytic Cracking of Plastic Pyrolysis Waxes with Vacuum Gasoil: Effect of HZSM-5 Zeolite in the FCC Catalyst

2006· article· en· W2055785576 on OpenAlexaff
Iker Torre, José M. Arandes, Pedro Castaño, Miren J. Azkoiti, Javier Bilbao, Hugo Ignacio de Lasa

Bibliographic record

VenueInternational Journal of Chemical Reactor Engineering · 2006
Typearticle
Languageen
FieldMaterials Science
TopicPolymer crystallization and properties
Canadian institutionsWestern University
Fundersnot available
KeywordsWaxZeoliteCrackingFluid catalytic crackingCatalysisGasolinePyrolysisVacuum distillationChemical engineeringMaterials scienceRaw materialYield (engineering)NaphthaleneDistillationFraction (chemistry)Organic chemistryPolypropyleneWaste managementChemistryComposite material

Abstract

fetched live from OpenAlex

Catalytic cracking of waste plastics is an interesting option for selectively recovering raw materials or for obtaining fuels. In this paper, a new recycling strategy is proposed, which consists of upgrading the waxes obtained by flash pyrolysis of polyolefins in a FCC (Fluidized Catalytic Cracking) unit. The waxes have been obtained by flash pyrolysis of polypropylene at 500 ºC and they have been dissolved (20 wt% wax) in the vacuum gasoil (VGO) of a FCC unit. The runs have been carried out in a CREC-UWO Riser Simulator Reactor (atmospheric pressure; 500-550 ºC; C/O = 5.5; contact times, 3-12 s). A commercial catalyst and a hybrid one (containing HZSM-5 zeolite) have been used. The cracking of the mixture leads to higher yield of gasoline than in the cracking of VGO with a higher content of olefins. The results of the effect of the operating conditions (temperature and contact time) are qualitatively similar to those corresponding to standard feed. Consequently, no difficulties inherent to the presence of waxes in the feed are expected in the treatment of mixtures at industrial conditions. The presence of HZSM-5 zeolite in the catalyst causes a significant increase in the amount of LPG (especially C3-C4 olefins), at the expense of a decrease in the gasoline fraction, whose RON is 1-2 points higher than that corresponding to the commercial catalyst. The gasoline obtained also has a higher content of olefins (especially C5-C7) and benzene at the expense of a decrease in the amount of C6-C10 i-paraffins.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.270

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 head0.004
GPT teacher head0.206
Teacher spread0.202 · 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 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

Citations18
Published2006
Admission routes1
Has abstractyes

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