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Record W2936950441 · doi:10.1021/acs.joc.9b00068

Development of Palladium-Catalyzed Decarboxylative Allylation of Electron-Deficient Sulfones and Identification of Unusual Side Products

2019· article· en· W2936950441 on OpenAlexafffund
Monica A. Gill, Jeffrey M. Manthorpe

Bibliographic record

VenueThe Journal of Organic Chemistry · 2019
Typearticle
Languageen
FieldChemistry
TopicCatalytic C–H Functionalization Methods
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for InnovationCarleton University
KeywordsChemistryProtonationCatalysisPalladiumSubstrate (aquarium)TetrahydrofuranCombinatorial chemistryTrifluoromethylOrganic chemistryAlkylSolventIon

Abstract

fetched live from OpenAlex

The use of sulfones as electron-withdrawing groups in substrates for palladium-catalyzed decarboxylative allylation was explored. A previously published trifluoromethanesulfonyl-based substrate was highly reactive and selective under mild conditions, but the substrate scope was not readily expanded. Instead, 3,5-bis(trifluoromethyl)phenyl sulfones were employed, thereby simultaneously retaining most of the electron deficiency and providing facile synthetic access. Optimization of the catalytic conditions to maximize the product distribution to a synthetically useful level of the allylation product over the protonation side product proved extremely challenging, with inconsistent and irreproducible results afforded with Pd2(dba)3 as the palladium source. A variety of substrates were subjected to the optimized catalytic conditions of PdCp(1-cinnamyl) and Xantphos in tetrahydrofuran at 50 °C for 30 min. These conditions were applicable to all substrates with the exception of the α,α-dimethyl allyl ester, which required more forcing conditions and afforded four products: the allylation and protonation products, as expected, along with a cyclopropylation product and an unprecedented pseudodimeric product. The mechanism for the formation of these unusual side products is considered.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.003
Threshold uncertainty score0.448

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.000
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 spread0.240 · 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

Citations4
Published2019
Admission routes2
Has abstractyes

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