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Record W2151639755 · doi:10.1002/cjce.22247

Catalytic Pyrolysis of Low Rank Canadian Boundary Dam Coal over ZSM‐5 and LTL Zeolites

2015· article· en· W2151639755 on OpenAlexafffundvenueabout
Kavan Motazedi, Davood Karami, Nader Mahinpey

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2015
Typearticle
Languageen
FieldEngineering
TopicThermochemical Biomass Conversion Processes
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaShandong Academy of SciencesUniversity of Calgary
KeywordsPyrolysisZeoliteCatalysisCoalChemistryChemical engineeringDecompositionHydrogenZSM-5Hydrogen productionMethanePhenolCrackingHydrothermal circulationInorganic chemistryMaterials scienceOrganic chemistry

Abstract

fetched live from OpenAlex

The catalytic pyrolysis of low‐rank coal (boundary dam lignite coal) for production of valuable chemical compounds, such as aromatics, over zeolites has been investigated with promising results. In this study, primarily zeolites ZSM‐5 (zeolite socony mobil‐5) and LTL (Linde type L) were successfully synthesized by a direct hydrothermal method without using any templates, known as structure directing agents (SDAs). Various analysis methods were employed to characterize the parent and modified zeolites before catalyzing the pyrolysis of coal. The H‐form of zeolite LTL showed the best performance for phenol, methane, and hydrogen formations in slow pyrolysis of coal at a temperature range of 400–600 °C and heating rate of 5° C/min. The effect of zeolite LTL potassium content on changing the coal decomposition path is suggested to enhance the production of these compounds along with cracking activity of the acid sites of the zeolites.

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 score0.024
Threshold uncertainty score0.989

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 head0.006
GPT teacher head0.173
Teacher spread0.167 · 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

Citations9
Published2015
Admission routes4
Has abstractyes

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