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Record W4245711785 · doi:10.1002/ange.201908336

Suzuki–Miyaura Coupling of (Hetero)Aryl Sulfones: Complementary Reactivity Enables Iterative Polyaryl Synthesis

2019· article· en· W4245711785 on OpenAlexafffund
Paul Chatelain, Abhijit Sau, Christopher N. Rowley, Joseph Moran

Bibliographic record

VenueAngewandte Chemie · 2019
Typearticle
Languageen
FieldChemistry
TopicCatalytic Cross-Coupling Reactions
Canadian institutionsMemorial University of Newfoundland
FundersEuropean Research CouncilNatural Sciences and Engineering Research Council of Canada
KeywordsElectrophileReactivity (psychology)ArylChemistrySulfoneCombinatorial chemistryAryl halideSuzuki reactionCoupling reactionOrganic chemistryCatalysisAlkyl

Abstract

fetched live from OpenAlex

Abstract Ideal organic syntheses involve the rapid construction of C−C bonds, with minimal use of functional group interconversions. The Suzuki–Miyaura cross‐coupling (SMC) is a powerful way to form biaryl linkages, but the relatively similar reactivity of electrophilic partners makes iterative syntheses involving more than two sequential coupling events difficult to achieve without additional manipulations. Here we introduce (hetero)aryl sulfones as electrophilic coupling partners for the SMC reaction, which display an intermediate reactivity between those of typical aryl (pseudo)halides and nitroarenes. The new complementary reactivity allows for rapid sequential cross‐coupling of arenes bearing chloride, sulfone and nitro leaving groups, affording non‐symmetric ter‐ and quateraryls in only 2 or 3 steps, respectively. The SMC reactivity of (hetero)aryl sulfones is demonstrated in over 30 examples. Mechanistic experiments and DFT calculations are consistent with oxidative addition into the sulfone C−S bond as the turnover‐limiting step. The further development of electrophilic cross‐coupling partners with complementary reactivity may open new possibilities for divergent iterative synthesis starting from small pools of polyfunctionalized arenes.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.023
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0030.000

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 head0.019
GPT teacher head0.261
Teacher spread0.242 · 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.

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

Citations19
Published2019
Admission routes2
Has abstractyes

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