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Record W4298877923 · doi:10.14716/ijtech.v6i4.1417

The adsorption Properties of Surface-Modified Mesoporous Silica Materials with ß-Cylodextrin

2015· article· en· W4298877923 on OpenAlexaff
Lee D. Wilson, Sarker T. Mahmud

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2015
Typearticle
Languageen
FieldMaterials Science
TopicMesoporous Materials and Catalysis
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsAdsorptionMesoporous materialMaterials scienceMesoporous silicaChemical engineeringSurface modificationChemistryOrganic chemistryCatalysis

Abstract

fetched live from OpenAlex

The adsorption properties of surface-modified mesoporous silica materials containing ?-cyclodextrin (CD ICS) were studied using two types of gas phase adsorbates (N2 and CH3Cl), along with a dye molecule (p-nitrophenol; PNP) in an aqueous solution. The CD ICS materials possess an ordered silica mesostructure framework that depends on the type of surfactant template and the level of loading of ?-CD. Incremental variations in the uptake of gas phase adsorbates and PNP from an aqueous solution were observed, according to the composition of CD ICS materials. For materials with similar CD loading, the surface area (SA) and pore volume doubled, as the surfactant from dodecylamine to hexadecylamine was varied. The SA of the CD ICS materials decreased by ca. 1.5-fold as the CD loading varied from 2% to 6%. The sorption capacity (Qe; mmol/g) of PNP increased from 61% to 84% as the CD loading increased from 2% to 6% and as the alkyl chain length of the surfactant template varied from C12 to C16. The adsorption properties of CD ICS materials with CH3Cl in the gas phase and for PNP in aqueous solution adopt a multi-layer adsorption profile, as described by the BET isotherm model.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Insufficient payload (model declined to judge)
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 score0.009
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0030.001
Research integrity0.0000.000
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 head0.250
GPT teacher head0.474
Teacher spread0.224 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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