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Record W2030331487 · doi:10.1021/ic0300868

Preparation, Characterization, and Condensation of Copper Tellurolate Clusters in the Pores of Periodic Mesoporous Silica MCM-41

2003· article· en· W2030331487 on OpenAlexaff
Collin M. Kowalchuk, Günter Schmid, Wolfgang Meyer‐Zaika, Yining Huang, John F. Corrigan

Bibliographic record

VenueInorganic Chemistry · 2003
Typearticle
Languageen
FieldMaterials Science
TopicPolyoxometalates: Synthesis and Applications
Canadian institutionsWestern University
Fundersnot available
KeywordsChemistryThermogravimetric analysisCopperMesoporous materialPowder diffractionChalcogenCondensationSpectroscopyDiffuse reflectance infrared fourier transformInfrared spectroscopyChemical engineeringCrystallographyOrganic chemistryCatalysisPhotocatalysis

Abstract

fetched live from OpenAlex

The copper-tellurolate cluster [(Cu(6)(TePh)(6)(PPh(2)Et)(5)] has been loaded into the pores of MCM-41 by solid-state impregnation techniques. It was found that the best loading conditions are 110 degrees C and 10(-)(3) Torr static vacuum. The resulting material was analyzed by powder X-ray diffraction (PXRD), nitrogen adsorption isotherms, thermogravimetric analysis (TGA), (31)P CP MAS NMR spectroscopy, and TEM. It was observed that loading is accompanied by loss of the phosphine shell, with retention of the copper-tellurium core. Condensation of the impregnated material may proceed thermally or photochemically. Thermal condensation results in the formation of Cu(2)Te nanoparticles as demonstrated by PXRD, and TEM data suggests that the process has taken place inside the pores of MCM-41. Photochemical condensation yields larger metal-chalcogen clusters in the pores as suggested by the result of UV-vis diffuse reflectance spectroscopy and TEM measurements.

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 score0.002

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 head0.008
GPT teacher head0.231
Teacher spread0.223 · 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

Citations20
Published2003
Admission routes1
Has abstractyes

Explore more

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