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Record W2791000843 · doi:10.1021/acsomega.7b01877

Revised Mechanism for a Ruthenium-Catalyzed Coupling of Aldehyde and Terminal Alkyne

2018· article· en· W2791000843 on OpenAlexafffund
Anna Tomberg, Soumen Kundu, Feng Zhou, Chao‐Jun Li, Nicolas Moitessier

Bibliographic record

VenueACS Omega · 2018
Typearticle
Languageen
FieldChemistry
TopicCatalytic C–H Functionalization Methods
Canadian institutionsMcGill UniversityCentre in Green Chemistry and Catalysis
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCanada Foundation for Innovation
KeywordsRutheniumAlkyneAldehydeCatalysisChemistryAldol reactionCycloadditionCatalytic cycleDecarbonylationCombinatorial chemistryReaction mechanismCoupling reactionOrganic chemistry

Abstract

fetched live from OpenAlex

Ruthenium catalysts have been found to be of great use for many kinds of reactions. Understanding the details of the catalytic cycle allows to not only rationalize experimental results but also to improve upon reactions. Herein, we present a detailed computational study of a ruthenium-catalyzed coupling between a terminal alkyne and an aldehyde. The reaction under examination facilitates novel access to olefins with the concurrent loss of a single carbon as carbon monoxide. The reaction was first developed in 2009, but the tentative mechanism initially proposed was proven to be contradictory to some experimental data obtained since then. Using a combination of computational investigations and isotope-labeling experiments, several potential mechanisms have been studied. In contrast to the [2+2] cycloaddition mechanism suggested for similar catalysts, we propose a new consensus pathway that proceeds through the formation of a ruthenium-vinylidene complex that undergoes an aldol-type reaction with the aldehyde to yield the product olefins. Computational insights into the influence of different reagents used to optimize reaction conditions and the intricacies of decarbonylation of a Ru-CO complex affecting catalyst turnover are highlighted.

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 score0.030
Threshold uncertainty score0.547

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0000.000

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 head0.028
GPT teacher head0.302
Teacher spread0.274 · 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

Citations9
Published2018
Admission routes2
Has abstractyes

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