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Record W2755150496 · doi:10.1021/acs.inorgchem.7b01654

Enhanced Catalytic Activity of Iridium(III) Complexes by Facile Modification of C,N-Bidentate Chelating Pyridylideneamide Ligands

2017· article· en· W2755150496 on OpenAlexfundno aff
Miquel Navarro, Christene A. Smith, Martin Albrecht

Bibliographic record

VenueInorganic Chemistry · 2017
Typearticle
Languageen
FieldChemistry
TopicAsymmetric Hydrogenation and Catalysis
Canadian institutionsnot available
FundersFP7 Ideas: European Research CouncilNatural Sciences and Engineering Research Council of CanadaQueen's UniversitySchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
KeywordsChemistryIridiumDenticityPhenylacetyleneCatalysisTransfer hydrogenationChelationHydrosilylationLigand (biochemistry)Medicinal chemistryBase (topology)ArylAlcoholPolymer chemistryOrganic chemistryMetalRutheniumAlkyl

Abstract

fetched live from OpenAlex

A set of aryl-substituted pyridylideneamide (PYA) ligands with variable donor properties owing to a pronounced zwitterionic and a neutral diene-type resonance structure were used as electronically flexible ligands at a pentamethylcyclopentadienyl (Cp*) iridium center. The straightforward synthesis of this type of ligand allows for an easy incorporation of donor substituents such as methoxy groups in different positions of the phenyl ring of the C,N-bidentate chelating PYA. These modifications considerably enhance the catalytic activity of the coordinated iridium center toward the catalytic aerobic transfer hydrogenation of carbonyls and imines as well as the hydrosilylation of phenylacetylene. Moreover, these PYA iridium complexes catalyze the base-free transfer hydrogenation of aldehydes, and to a lesser extent also of ketones. Under standard transfer hydrogenation conditions including base, aldehydes are rapidly oxidized to carboxylic acids rather than reduced to the corresponding alcohol, as is observed under base-free conditions.

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 categoriesMeta-epidemiology (narrow)
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 score0.011
Threshold uncertainty score1.000

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 science0.0010.000
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 head0.016
GPT teacher head0.267
Teacher spread0.250 · 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

Citations48
Published2017
Admission routes1
Has abstractyes

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