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Record W4387957392 · doi:10.1021/acs.iecr.3c02543

SAPO-34 Catalyst: Synthesis Optimization by Template Alteration and In Situ Coke Evolution Analysis in Methanol Conversion to Light Olefins

2023· article· en· W4387957392 on OpenAlexafffund
Mohammad Ghavipour, Ralph Al Hussami, Kirill Levin, Ranjan Roy, Jan Kopyscinski

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2023
Typearticle
Languageen
FieldChemistry
TopicZeolite Catalysis and Synthesis
Canadian institutionsMcGill University
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of Canada
KeywordsDiethylamineCatalysisMorpholineChemistryCokeMesoporous materialMethanolThermogravimetric analysisChemical engineeringZeoliteMicroporous materialMolecular sieveOrganic chemistry

Abstract

fetched live from OpenAlex

The template’s role in the physicochemical properties of SAPO-34 was investigated using the four most popular templates (tetraethylammonium hydroxide (TEAOH), morpholine (MOR), triethylamine (TEA), and diethylamine (DEA)) in both single- and mixed-template methods to reduce the consumption of costly TEAOH. Catalyst activity in methanol conversion to light olefins was examined at 425 °C and WHSV of 1 g MeOH g Cat –1 h –1 . The TEA-based sample proved to be a good substitute for TEAOH in single template SAPO, and both TEAOH/DEA and TEAOH/TEA-based samples were successfully produced with the sole existence of the SAPO-34 phase and exhibited acceptable performance. Possessing a high external surface area (macro and mesopores) was recognized to be the dominant parameter affecting the catalyst’s lifetime while having the optimum acidity and the small particle size played minor roles. In-situ measurement of coke formation over SAPO-34 was also conducted in a thermogravimetric reactor and led to the proposal of the coke formation mechanism, which was confirmed by 13 C NMR spectroscopy and gas chromatography–mass spectrometry techniques.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.023
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.044
GPT teacher head0.297
Teacher spread0.252 · 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

Citations9
Published2023
Admission routes2
Has abstractyes

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