MétaCan
Menu
Back to cohort
Record W2555904089 · doi:10.1139/cjc-2016-0305

Synthesis of zeolite/carbon nanotube composite for gas separation

2016· article· en· W2555904089 on OpenAlexvenueno aff
Majideh Babaei, Mansoor Anbia, Maryam Kazemipour

Bibliographic record

VenueCanadian Journal of Chemistry · 2016
Typearticle
Languageen
FieldMaterials Science
TopicCovalent Organic Framework Applications
Canadian institutionsnot available
FundersIran University of Science and TechnologyIran National Science FoundationIslamic Azad UniversityNational Science Foundation
KeywordsZeoliteComposite numberAdsorptionChemistryMicroporous materialFourier transform infrared spectroscopyScanning electron microscopeChemical engineeringSelectivityBET theoryCarbon nanotubeMaterials scienceComposite materialOrganic chemistryCatalysis

Abstract

fetched live from OpenAlex

A hybrid composite of NaY zeolite and amine modified multi-walled carbon nanotube (MWCNT) has been synthesized by hydrothermal method. The obtained NaY/CNT composite (NC composite) was characterized by X-ray diffraction (XRD), Fourier transform infrared (FTIR), scanning electron microscopy (SEM), and BET analysis. CO2, CH4 and N2 adsorption at two different temperatures and P < 5 bar on the composite was investigated by the volumetric method. The selectivity of the NC composite for CO2/CH4 and CO2/N2 has been studied and compared with pure NaY zeolite. Crystal structures of NC composite were similar to those of pure NaY zeolite, but the surface area and pore volume of the NC composite are enhanced. Incorporation of MWCNTs into NaY zeolite increases nucleation sites for the formation of NaY zeolite crystals, resulting in the smaller size of NaY zeolite crystals. Gas adsorption capacity and selectivity of NC composite increased because of enhancement of micropore volume. The results confirm that NC composite is a promising material for the separation and purification of gases.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.009
GPT teacher head0.236
Teacher spread0.227 · 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 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

Citations15
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of ChemistrySame topicCovalent Organic Framework ApplicationsFrench-language works237,207