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Record W3141756641 · doi:10.1021/acscatal.1c00014

Ureate Titanium Catalysts for Hydroaminoalkylation: Using Ligand Design to Increase Reactivity and Utility

2021· article· en· W3141756641 on OpenAlexafffund
Manfred Manßen, Danfeng Deng, Cameron H. M. Zheng, Rebecca C. DiPucchio, Dafa Chen, Laurel L. Schafer

Bibliographic record

VenueACS Catalysis · 2021
Typearticle
Languageen
FieldChemistry
TopicOrganoboron and organosilicon chemistry
Canadian institutionsUniversity of British Columbia
FundersChina Scholarship CouncilNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsAlexander von Humboldt-Stiftung
KeywordsCatalysisReactivity (psychology)ChemistryAlkeneAmine gas treatingOrganic chemistryRegioselectivityTitaniumAlkylArylCombinatorial chemistry

Abstract

fetched live from OpenAlex

Hydroaminoalkylation describes the atom-economical catalytic synthesis of amines by forming new Csp3–Csp3 bonds using readily available amine and alkene feedstocks. Herein, we describe an earth-abundant and cost-efficient titanium catalyst generated in situ using commercially available Ti(NMe2)4 and a simple to synthesize urea proligand. This system demonstrates high TOFs for hydroaminoalkylation with unactivated substrates and features easy to use commercially available titanium amido precursors. Additionally, a high catalytic activity, scope of reactivity, and regioselectivity are all demonstrated in the transformation of unactivated terminal olefins with various alkyl and aryl secondary amines. Finally, syntheses of useful amine-containing monomers suitable for the generation of amine-containing materials, as well as amine-containing building blocks for medicinal chemistry, are disclosed. These preparative methods avoid the necessity of glovebox techniques and are modified to be useful to all synthetic chemists.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.005
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.031
GPT teacher head0.265
Teacher spread0.234 · 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.

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

Citations25
Published2021
Admission routes2
Has abstractyes

Explore more

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