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Record W2978732337 · doi:10.1021/acs.organomet.9b00524

Iron-SNS and -CNS Complexes: Selective C<sub>aryl</sub>–S Bond Cleavage and Amine-Borane Dehydrogenation Catalysis

2019· article· en· W2978732337 on OpenAlexafffund
Matthew R. Elsby, Karine Ghostine, Uttam Kumar Das, Bulat Gabidullin, R. Tom Baker

Bibliographic record

VenueOrganometallics · 2019
Typearticle
Languageen
FieldChemistry
TopicAsymmetric Hydrogenation and Catalysis
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsChemistryImineMedicinal chemistryThioetherBond cleavageArylCatalysisProtonationDehydrogenationLigand (biochemistry)Amine gas treatingReactivity (psychology)Cationic polymerizationBoraneDenticityStereochemistryPolymer chemistryOrganic chemistryAlkyl

Abstract

fetched live from OpenAlex

The synthesis, structure, and reactivity of an electron-rich FeII thioether-imine-thiolate complex, [Fe(SMeNS)(PMe3)3](OTf) (1-SNS), prepared by reaction of Fe(OTf)2(PMe3)4 with the SMeNHS ligand in THF, are reported (OTf = CF3SO3). Substitution reactions of 1 with mono- and bidentate donor ligands afforded [Fe(SMeNS)L(PMe3)2](OTf) (2,3-SNS; L = P(OMe)3, CNxylyl) and [Fe(SMeNS)(dmpe)(PMe3)](OTf) [4-SNS; dmpe = 1,2-bis(dimethylphosphino)ethane]. Heating 1-SNS in THF at 60 °C gave a new trivalent aryl-imine-thiolate complex, [Fe(CNS)(PMe3)3](OTf) (1-CNS) via Caryl–S bond cleavage. Reduction of 1-CNS with cobaltocene yielded divalent [Fe(CNS)(PMe3)3] (2-CNS) which, upon dmpe addition, yields [Fe(CNS)(PMe3)(dmpe)] (3-CNS). Treatment of the previously reported cationic Fe amine-amido complex [Fe(SMeNHSMe)(SMeNSMe)]+ with PMe3 gave FeII aryl-imine-thioether complex [Fe(CNSMe)(PMe3)3]+ (4-CNS′) via selective activation of both Caryl–S and benzylic C–H bonds. Assessment of complexes 3-CNS, 4-SNS, and 4-CNS′ as precatalysts for amine-borane dehydrogenation catalysis in THF at 60 °C shows that 3-CNS forms a selective and robust bifunctional catalyst system.

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 score0.023
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
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.005
GPT teacher head0.200
Teacher spread0.195 · 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

Citations22
Published2019
Admission routes2
Has abstractyes

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