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Record W4407752952 · doi:10.1002/anie.202423275

Manganese‐Ketenimine Intermediates as Active Catalysts in the Michael Addition of Unactivated Nitriles to α,β‐Unsaturated Ketones

2025· article· en· W4407752952 on OpenAlexfundno aff
Kartick Dey, Akhanda Gorai, Katarzyna Młodzikowska‐Pieńko, Natalia Fridman, Idan Avigdori, Renana Gershoni‐Poranne, Graham de Ruiter

Bibliographic record

VenueAngewandte Chemie International Edition · 2025
Typearticle
Languageen
FieldChemistry
TopicAsymmetric Hydrogenation and Catalysis
Canadian institutionsnot available
FundersAzrieli FoundationIsrael Science Foundation
KeywordsPropionitrileChemistryAcetonitrileNitrileCatalysisManganeseTrifluoromethylPropargylOrganic chemistryElectrophileMichael reactionKetenimineSteric effectsReactivity (psychology)Medicinal chemistryCombinatorial chemistryAlkyl

Abstract

fetched live from OpenAlex

Abstract The Michael addition of unactivated nitriles to α,β‐unsaturated ketones is a challenging yet desirable strategy for installing alkyl cyano‐groups (R‐CN) in organic molecules. However, despite formidable efforts, using acetonitrile as a Michael donor in these reactions has remained a significant challenge. Herein, we report a highly active manganese(I) complex [(PC NHC P)Mn(CO) 2 H] ( 1 ), which chemoselectively catalyzes the 1,4‐addition of unactivated nitriles (incl. acetonitrile) to α,β‐unsaturated ketones. The developed methodology operates under mild conditions, does not require any additives or bases, features low catalyst loadings (1 mol %), fast reaction times (2–8 hours), and is compatible with a wide variety of functional groups, including halides, trifluoromethyl, alkenyl, alkynyl, and (hetero)aryl groups. Extensive mechanistic studies revealed that after base‐free activation of the nitrile, either the N‐bound manganese‐ketenimine (propionitrile or benzyl cyanide) or the C‐bound manganese‐cyanoalkyl (acetonitrile) complex is formed. The difference in stability of these two species explains why more sterically hindered and presumably less activated nitriles ( i.e ., propionitrile, and butyronitrile) show higher reactivity than their corresponding more activated congeners ( i.e ., acetonitrile). Finally, the practicality of our approach was demonstrated through a gram‐scale reaction and subsequent derivatizations of the obtained product into important organic motifs such as ene‐lactams and tetrahydropyridines.

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 score0.044
Threshold uncertainty score0.786

Codex and Gemma teacher scores by category

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

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 head0.007
GPT teacher head0.265
Teacher spread0.258 · 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

Citations3
Published2025
Admission routes1
Has abstractyes

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