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Record W2032742368 · doi:10.1021/la048349d

Structure and Diffusion Characterization of SBA-15 Materials

2005· article· en· W2032742368 on OpenAlexafffund
Hoang Vinh‐Thang, Qinglin Huang, Mladen Eić, Trong‐On Do, Serge Kaliaguine

Bibliographic record

VenueLangmuir · 2005
Typearticle
Languageen
FieldMaterials Science
TopicMesoporous Materials and Catalysis
Canadian institutionsUniversité LavalUniversity of New Brunswick
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMesoporous materialMicroporous materialHeptaneDiffusionMaterials scienceChemical engineeringDiffusion processChemistryAnalytical Chemistry (journal)ChromatographyThermodynamicsOrganic chemistryComposite materialCatalysis

Abstract

fetched live from OpenAlex

In situ formation of the micro- and mesoporous structures of SBA-15 materials was investigated. It was found that the structure is significantly different from that for cylindrical or hexagonal pores, which suggests that the SBA-15 is more complex than an array of hexagonally ordered channels. Nitrogen adsorption isotherms at 77 K provided evidence that large (primary) mesopores are accompanied by a certain amount of significantly smaller pores with a broad distribution in the micropore/small-mesopore range within the mesoporous walls of main channels. It was found that the microporosity can be controlled by the time of heating as well as the synthesis temperature. The diffusion properties of n-heptane as a probe molecule in four selected SBA-15 samples with different micropore volumes were studied by the standard zero length column technique and related to their structural characteristics. The results have shown that the diffusion process involving n-heptane at a low concentration level takes place inside the walls of main mesoporous channels and depends on the relative content of micropores. In the samples that have a relatively high content of micropores, n-heptane diffusivities are relatively low, their activation energies are high, and the process is similar to diffusion in typical microporous adsorbents, like zeolites. As the micropore content is decreased, diffusion becomes more and more controlled by secondary mesopores of the intrawall pore structure, rendering diffusion faster and activation energies lower.

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 categoriesInsufficient 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 score0.031
Threshold uncertainty score0.998

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)0.0030.000

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 head0.005
GPT teacher head0.201
Teacher spread0.196 · 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

Citations111
Published2005
Admission routes2
Has abstractyes

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