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Record W2563042313 · doi:10.1021/jacs.6b12329

Palladium-Catalyzed Suzuki–Miyaura Coupling of Aryl Esters

2016· article· en· W2563042313 on OpenAlexafffund
Taoufik Ben Halima, Wanying Zhang, Imane Yalaoui, Xin Hong, Yun‐Fang Yang, K. N. Houk, Stephen G. Newman

Bibliographic record

VenueJournal of the American Chemical Society · 2016
Typearticle
Languageen
FieldChemistry
TopicCatalytic Cross-Coupling Reactions
Canadian institutionsUniversity of Ottawa
FundersDivision of ChemistryNatural Sciences and Engineering Research Council of CanadaZhejiang UniversityGovernment of Jiangxi ProvinceCanada Research ChairsMinistère de l'Education Nationale, de l'Enseignement Superieur et de la RechercheOntario Ministry of Economic Development and InnovationUniversity of Ottawa
KeywordsChemistryElectrophileChemoselectivityArylPalladiumCatalysisCombinatorial chemistryCoupling reactionKetoneOrganic chemistryAlkyl

Abstract

fetched live from OpenAlex

The Suzuki-Miyaura coupling is among the most important C-C bond-forming reactions available due to its reliability, chemoselectivity, and diversity. Aryl halides and pseudohalides such as iodides, bromides, and triflates are traditionally used as the electrophilic coupling partner. The expansion of the reaction scope to nontraditional electrophiles is an ongoing challenge to enable an even greater number of useful products to be made from simple starting materials. Herein, we present how an NHC-based Pd catalyst can enable Suzuki-Miyaura coupling where the C(acyl)-O bond of aryl esters takes on the role of electrophile, allowing the synthesis of various ketone-containing products. This contrasts known reactions of similar esters that provide biaryls via nickel catalysis. The underlying cause of this mechanistic divergence is investigated by DFT calculations, and the robustness of esters compared to more electrophilic acylative coupling partners is analyzed.

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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.011
GPT teacher head0.260
Teacher spread0.249 · 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

Citations250
Published2016
Admission routes2
Has abstractyes

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Same venueJournal of the American Chemical SocietySame topicCatalytic Cross-Coupling ReactionsFrench-language works237,207