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Record W2092909457 · doi:10.1021/la034067m

Effect of Pentanol on Morphologies and Pore Structure of Mesoporous Silica

2003· article· en· W2092909457 on OpenAlexaff
Shuhua Han, Wanguo Hou, Xin Yan, Zhengmin Li, Peng Zhang, Dongqing Li

Bibliographic record

VenueLangmuir · 2003
Typearticle
Languageen
FieldMaterials Science
TopicMesoporous Materials and Catalysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMesoporous materialMesoporous silicaAdsorptionDesorptionBromideMesoporous organosilicaScanning electron microscopeChemical engineeringMolar ratioMicelleMolarMaterials scienceChemistryInorganic chemistryOrganic chemistryComposite materialAqueous solutionCatalysis

Abstract

fetched live from OpenAlex

Using wormlike micelles of cetyltrimethylammonium bromide (CTAB) and nitric acid as templates, fibrous mesoporous silica was synthesized and the effects of pentanol on the morphologies and ordered pore structure of mesoporous silica were studied. The resulting mesoporous silica was characterized by small-angle X-ray diffraction, nitrogen adsorption−desorption measurements, and scanning electron microscopy. Results showed that the amount of mesoporous silica with fibrous shapes decreased with the decrease of the molar ratio of CTAB to pentanol and that mesoporous silica with a spherical appearance only was obtained at a molar ratio of 1:3 (CTAB to pentanol). The pore structure of mesoporous silica was more ordered when the molar ratio of CTAB to pentanol was between 1:1 and 1:2, and distances between centers of two adjacent pores increased with the decrease of the molar ratio of CTAB to pentanol. There existed a type IV adsorption isotherm and an H1 hysteresis loop in N 2 adsorption−desorption curves; total pore volume and most probable pore size with Barrett−Joyner−Halenda diameter increased with the decrease of the molar ratio of CTAB to pentanol. The result was in agreement with that of small-angle X-ray diffraction.

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 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 score0.750

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)0.0010.000

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 head0.004
GPT teacher head0.228
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.

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

Citations21
Published2003
Admission routes1
Has abstractyes

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