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Record W3185211613 · doi:10.1016/j.fmre.2021.06.018

Photoinduced transition-metal and external photosensitizer free phosphonation of unactivated C(sp2)–F bond via SET process under mild conditions

2021· article· en· W3185211613 on OpenAlexafffund
Qian Dou, Yatao Lang, Huiying Zeng, Chao‐Jun Li

Bibliographic record

VenueFundamental Research · 2021
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicFluorine in Organic Chemistry
Canadian institutionsCentre in Green Chemistry and CatalysisMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for InnovationNational Natural Science Foundation of ChinaE.B. Eddy Endowment FundCanada Research ChairsFonds Québécois de la Recherche sur la Nature et les TechnologiesInternational Joint Research Center for Green Catalysis and Synthesis
KeywordsChemistryPhotosensitizerArylNucleophilePhotochemistryBond cleavageTransition metalCatalysisHeteroatomDissociation (chemistry)MetalCombinatorial chemistryOrganic chemistryRing (chemistry)Alkyl

Abstract

fetched live from OpenAlex

Transition-metal catalyzed cross-couplings of aryl halides (ArI, ArBr and ArCl) with a broad range of nucleophiles have been developed as powerful methods for carbon–carbon and carbon–heteroatom bonds formation. However, due to the high bond dissociation energy of unactivated C(sp2)–F, cross-couplings of mono-fluoroarenes are the most challenging, especially without using transition-metal catalysts. Herein, a photo-induced transition-metal and external photosensitizer free defluorophosphonation of monofluoroarenes via unactivated C(sp2)–F bond cleavage is reported. Different mono-fluoroarenes have been successfully cross-coupled with dialkyl phosphites in moderate to excellent yields under mild conditions. Mechanistic studies have revealed the possible involvement of a photo-induced SET process and aryl free radical intermediates.

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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.184
GPT teacher head0.503
Teacher spread0.319 · 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

Citations20
Published2021
Admission routes2
Has abstractyes

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Same venueFundamental ResearchSame topicFluorine in Organic ChemistryFrench-language works237,207