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Record W3168869418 · doi:10.1002/chem.202101324

Iron‐Catalyzed Halogen Exchange of Trifluoromethyl Arenes**

2021· article· en· W3168869418 on OpenAlexafffund
Andreas Dorian, Emily Landgreen, Hayley Petras, James J. Shepherd, Florence Williams

Bibliographic record

VenueChemistry - A European Journal · 2021
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicFluorine in Organic Chemistry
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaAmerican Chemical Society Petroleum Research Fund
KeywordsHalogenCatalysisChemistryReagentHalideTrifluoromethylCombinatorial chemistryMedicinal chemistryOrganic chemistryAlkyl

Abstract

fetched live from OpenAlex

Abstract The facile production of ArCF 2 X and ArCX 3 from ArCF 3 using catalytic iron(III)halides is reported, which constitutes the first iron‐catalyzed halogen exchange for non‐aromatic C−F bonds. Theoretical calculations suggest direct activation of C−F bonds by iron coordination. ArCX 3 and ArCF 2 X products of the reaction are synthetically valuable due to their diversification potential. In particular, chloro‐ and bromodifluoromethyl arenes (ArCF 2 Cl, ArCF 2 Br respectively) provide access to a myriad of difluoromethyl arene derivatives (ArCF 2 R). To optimize for mono‐halogen exchange, a statistical method called Design of Experiments was used. Optimized parameters were successfully applied to electron rich and electron deficient aromatic substrates, and to the late stage diversification of flufenoxuron, a commercial insecticide. These methods are highly practical, being run at convenient temperatures and using inexpensive common reagents.

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 score0.004

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 integrity0.0000.000
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 head0.089
GPT teacher head0.374
Teacher spread0.286 · 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

Citations23
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueChemistry - A European JournalSame topicFluorine in Organic ChemistryFrench-language works237,207