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Record W4233608080 · doi:10.1002/ange.202111977

Desulfonative Suzuki–Miyaura Coupling of Sulfonyl Fluorides

2021· article· en· W4233608080 on OpenAlexafffund
Paul Chatelain, Cyprien Muller, Abhijit Sau, Daria Brykczyńska, Maryam Bahadori, Christopher N. Rowley, Joseph Moran

Bibliographic record

VenueAngewandte Chemie · 2021
Typearticle
Languageen
FieldChemistry
TopicSulfur-Based Synthesis Techniques
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of CanadaAgence Nationale de la Recherche
KeywordsElectrophileSulfonylChemistryTransmetalationReactivity (psychology)ArylCombinatorial chemistryCatalysisSuzuki reactionCoupling reactionMedicinal chemistryOrganic chemistryPalladium

Abstract

fetched live from OpenAlex

Abstract Sulfonyl fluorides have emerged as powerful “click” electrophiles to access sulfonylated derivatives. Yet, they are relatively inert towards C−C bond forming transformations, notably under transition‐metal catalysis. Here, we describe conditions under which aryl sulfonyl fluorides act as electrophiles for the Pd‐catalyzed Suzuki–Miyaura cross‐coupling. This desulfonative cross‐coupling occurs selectively in the absence of base and, unusually, even in the presence of strong acids. Divergent one‐step syntheses of two analogues of bioactive compounds showcase the expanded reactivity of sulfonyl fluorides to encompass both S−Nu and C−C bond formation. Mechanistic experiments and DFT calculations suggest oxidative addition occurs at the C−S bond followed by desulfonation to form a Pd‐F intermediate that facilitates transmetalation.

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 score0.002
Threshold uncertainty score0.007

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 science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.024
GPT teacher head0.260
Teacher spread0.237 · 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

Citations7
Published2021
Admission routes2
Has abstractyes

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