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Record W4385830070 · doi:10.1021/jacs.3c06533

Copper and Silver Catalysis in the (3 + 2) Cycloaddition of Neutral Three-Atom Components with Terminal Alkynes

2023· article· en· W4385830070 on OpenAlexafffund
Dominic Campeau, Alice Pommainville, Mila Gorodnichy, Fabien Gagosz

Bibliographic record

VenueJournal of the American Chemical Society · 2023
Typearticle
Languageen
FieldChemistry
TopicClick Chemistry and Applications
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Ottawa
KeywordsChemistryCycloadditionAcetylideCatalysisAlkyneCombinatorial chemistryAzideIntramolecular forceCopperComputational chemistryStereochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

The introduction of the copper-catalyzed azide-alkyne coupling (CuAAC) to 1,3-dipolar cycloadditions was pivotal to their popularization in synthetic chemistry and to their application to multiple other domains of science. The reaction rate enhancement observed when coinage metal acetylide intermediates are involved in the cyclization process greatly expanded the structural and conditional range in which (3 + 2) cycloadditions may take place with terminal alkynes. Herein, we report that comparable rate enhancements, in nature and level, are induced by copper and silver catalysts in the intramolecular (3 + 2) cycloaddition of terminal alkynes with "neutral" three-atom components (TACs), specifically alkynyl sulfides. Through careful observations amidst reaction optimization, experimental, and DFT mechanistic studies, a pathway involving a proton-coupled cyclometallation key step is proposed. The sets of catalytic conditions that have been developed allow us to overcome several scope limitations previously presented by the thermally promoted (3 + 2) cycloaddition of "neutral" TACs, thus expanding their synthetic and applicative potential.

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 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 score0.021
Threshold uncertainty score0.227

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 studies0.0000.001
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 head0.013
GPT teacher head0.253
Teacher spread0.239 · 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

Citations12
Published2023
Admission routes2
Has abstractyes

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