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Record W1852598946 · doi:10.1139/cjc-2013-0135

Distribution of Al and adsorption of NH<sub>3</sub> and pyridine in ZSM-12: a computational study

2013· article· en· W1852598946 on OpenAlexvenueno aff
Gang Feng, Ying-Ying Lian, Deqin Yang, Jianwen Liu, Dejin Kong

Bibliographic record

VenueCanadian Journal of Chemistry · 2013
Typearticle
Languageen
FieldChemistry
TopicZeolite Catalysis and Synthesis
Canadian institutionsnot available
Fundersnot available
KeywordsChemistryPyridineAdsorptionLewis acids and basesZSM-5Brønsted–Lowry acid–base theoryInorganic chemistryDensity functional theoryZeolitePhysical chemistryCatalysisMolecular sieveMedicinal chemistryComputational chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

The distribution of Al and the adsorption of NH3 and pyridine in both Na-form and H-form ZSM-12 were investigated using dispersion-corrected density functional theory. It was found that the energy differences for Al atoms in the different T sites of ZSM-12 (both H form and Na form) were less than 0.3 eV, which indicates that the Al atoms could distribute in all kinds of T sites in ZSM-12. In addition, the small energy difference indicates that both H and Na atoms could stay in either the small cage or the main channel of ZSM-12. The adsorption of NH3 and pyridine on NaZSM-12 is weak, while the adsorption of NH3 and pyridine on HZSM-12 is strong, as they could form NH4+ and NC5H6+ species in the presence of protons. Both NH3 and pyridine could adsorb on the Lewis Al3+ sites in HZSM-12, while the adsorption of NH3 and pyridine on the Lewis acid sites are less stable than on the Brønsted acid sites of ZSM-12.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.008
GPT teacher head0.195
Teacher spread0.188 · 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

Citations19
Published2013
Admission routes1
Has abstractyes

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