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Record W3183254341 · doi:10.1021/jacs.1c05498

Direct, Catalytic α-Alkylation of <i>N</i>-Heterocycles by Hydroaminoalkylation: Substrate Effects for Regiodivergent Product Formation

2021· article· en· W3183254341 on OpenAlexafffund
Rebecca C. DiPucchio, Karst Eelco Lenzen, Pargol Daneshmand, Maria B. Ezhova, Laurel L. Schafer

Bibliographic record

VenueJournal of the American Chemical Society · 2021
Typearticle
Languageen
FieldChemistry
TopicCatalytic C–H Functionalization Methods
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsUniversity of Bern
KeywordsChemistryAlkylationCatalysisRegioselectivityAlkeneAmine gas treatingSubstrate (aquarium)Combinatorial chemistryOrganic chemistryReactivity (psychology)

Abstract

fetched live from OpenAlex

Saturated N-heterocycles are prevalent in pharmaceutical and agrochemical industries, yet remain challenging to catalytically alkylate. Most strategies for C–H activation of these challenging substrates use protected amines or high loadings of precious metal catalysts. We report an early transition-metal system for the broad, robust, and direct alkylation of unprotected amine heterocycles with simple alkenes. Short reaction times are achieved using an in situ generated tantalum catalyst that avoids the use of bases, excess substrate, or additives. In most cases, this catalyst system is selective for the branched reaction product, including examples of products that are generated with excellent diastereoselectivity. Alkene electronic properties can be exploited for substrate-modified regioselectivity to access the alternative linear amine alkylation product with a group 5 catalyst. This method allows for the facile isolation of unprotected N-heterocyclic products, as useful substrates for further reactivity.

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)0.001
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 score0.014
Threshold uncertainty score0.482

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
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 head0.015
GPT teacher head0.261
Teacher spread0.246 · 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

Citations44
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueJournal of the American Chemical SocietySame topicCatalytic C–H Functionalization MethodsFrench-language works237,207