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Record W2531123024 · doi:10.1021/om500765u

Phenylene- and Biphenylene-Bridged Bis-Imidazolylidenes of Palladium. Influence of the Presence of Pyrene Tags on the Catalytic Activity of the Complexes

2014· article· en· W2531123024 on OpenAlexfundno aff
Sheila Ruiz‐Botella, Eduardo Peris

Bibliographic record

VenueOrganometallics · 2014
Typearticle
Languageen
FieldChemistry
TopicN-Heterocyclic Carbenes in Organic and Inorganic Chemistry
Canadian institutionsnot available
FundersMinisterio de Economía y CompetitividadWilfrid Laurier University
KeywordsChemistryBiphenyleneArylPyreneCatalysisMedicinal chemistryPalladiumCarbeneHalidePhenyleneStereochemistryOrganic chemistryPolymer

Abstract

fetched live from OpenAlex

A series of dimetallic complexes with N-heterocyclic carbene ligands with formally identical stereoelectronic properties have been obtained and fully characterized. The dimetallic complexes were bridged by bis-imidazolylidenes, with different spacers (phenylene and biphenylene). The N substituents were methyl or methylpyrene groups. The related monometallic complexes were also obtained. The catalytic properties of the complexes were tested in the acylation of aryl halides with hydrocinnamaldehyde and in the Suzuki–Miyaura coupling between aryl halides and arylboronic acids. In general, the dimetallic complexes display better activities than the monometallic analogues. The results also indicate that those complexes with pyrene groups at the N substituents display better catalytic activities than those with N -methyl groups. These observations are interpreted as a consequence of the π stacking interaction between the substrates and the pyrene groups in the pyrene-containing catalysts, which may provide some beneficial catalytic properties. The addition of a catalytic amount of pyrene to the Suzuki–Miyaura coupling reactions results in a partial inhibition of the activities of the complexes with the pyrene substituents, while the activity of the complexes with the N -methyl groups is not affected.

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)0.001
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 score0.022
Threshold uncertainty score0.693

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.010
GPT teacher head0.210
Teacher spread0.200 · 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

Citations34
Published2014
Admission routes1
Has abstractyes

Explore more

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