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Record W1972519703 · doi:10.1039/c2ob07176b

SBA-15-functionalized palladium complex partially confined with ionic liquid: an efficient and reusable catalyst system for aqueous-phase Suzuki reaction

2012· article· en· W1972519703 on OpenAlexfundno aff
Babak Karimi, Asghar Zamani

Bibliographic record

VenueOrganic & Biomolecular Chemistry · 2012
Typearticle
Languageen
FieldChemistry
TopicCatalytic Cross-Coupling Reactions
Canadian institutionsnot available
FundersInstitute for Advanced Studies in Basic SciencesIran National Science FoundationMcGill University
KeywordsChemistryCatalysisHexafluorophosphateIonic liquidArylPalladiumHalideAqueous solutionSorptionHeterogeneous catalysisHomogeneous catalysisAqueous two-phase systemSuzuki reactionAryl halideOrganic chemistryInorganic chemistryAlkylAdsorption

Abstract

fetched live from OpenAlex

A novel SBA-15 functionalized palladium complex partially confined with 1-butyl-3-methylimidazolium hexafluorophosphate ionic liquid (Material 4) was found to be a very efficient and reusable catalyst in the Suzuki-Miyaura coupling reaction of aryl halides including aryl chlorides and heteroaryl halides with different aryl boronic acids under aqueous conditions without any organic co-solvents. Our studies showed that 4 is a more efficient catalyst in comparison with the catalyst not containing IL or catalyst with a higher ratio of IL. The materials were characterized by N(2)-sorption analysis, TGA and transmission electron microscopy before and after catalysis. While our studies showed that the catalyst can be successfully recycled and reused in at least 4 reaction runs, in contrast, several poisoning experiments and kinetic studies provide the notion that homogeneous (dissolved) species are responsible for the observed catalysis.

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)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.014
GPT teacher head0.264
Teacher spread0.249 · 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

Citations53
Published2012
Admission routes1
Has abstractyes

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