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Record W4384666155 · doi:10.1021/acscatal.3c02318

Selective Cobalt(II)–SNS Dithiolate Complex-Catalyzed Bifunctional Hydroboration of Aldehydes: Kinetics and Mechanistic Studies

2023· article· en· W4384666155 on OpenAlexafffund
Saeed Ataie, Samantha L. Dudra, Erin R. Johnson, R. Tom Baker

Bibliographic record

VenueACS Catalysis · 2023
Typearticle
Languageen
FieldChemistry
TopicSulfur-Based Synthesis Techniques
Canadian institutionsDalhousie UniversityUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsChemistryHydroborationBifunctionalCatalysisMedicinal chemistryAldehydeOrganic chemistry

Abstract

fetched live from OpenAlex

Anionic ligands containing a nonbonded lone pair ( i.e., amido, thiolate) are well-known to cooperate with a metal center in bifunctional catalytic reactions. An NHC Co II (κ 3 -SNS) imine–dithiolate complex ( Co-3 ) effects the selective hydroboration of aldehydes (vs ketones) in 4–30 min at a 1 mol % loading in benzene (NHC = 2,5-dimethyl-3,4-dichloroimidazol-2-ylidene). Although the catalyst was unchanged in stoichiometric reactions with the aldehyde or borane, VTNA kinetic studies showed first-order rate dependence on the concentrations of Co-3, aldehyde, and pinacolborane as well as significant product inhibition. DFT studies confirmed a bifunctional transition state with B–H activation at the 5-membered ring thiolate donor being slightly favored over the 6-membered ring. Stable van der Waals complexes of Co-3 with both benzaldehyde and its hydroboration product were also identified, and catalyst reuse studies further confirmed product inhibition, especially with aromatic aldehydes. Reactivation of the unchanged catalyst was easily accomplished by product removal using hexane.

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 score0.002
Threshold uncertainty score0.004

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 head0.044
GPT teacher head0.297
Teacher spread0.253 · 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

Citations8
Published2023
Admission routes2
Has abstractyes

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