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Record W4379780573 · doi:10.1021/acscatal.3c01713

Chemoenzymatic Dynamic Kinetic Resolution of Secondary Alcohols and Amines Employing Copper-Based Photocatalysis

2023· article· en· W4379780573 on OpenAlexafffund
Clémentine Minozzi, Nicolas Dowe, Noémie Beaucage, Shawn K. Collins

Bibliographic record

VenueACS Catalysis · 2023
Typearticle
Languageen
FieldChemistry
TopicRadical Photochemical Reactions
Canadian institutionsUniversité de MontréalCentre in Green Chemistry and Catalysis
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of Canada
KeywordsKinetic resolutionCandida antarcticaRacemizationPhotocatalysisChemistryCatalysisCopperYield (engineering)LipaseRadicalOrganic chemistryCombinatorial chemistryEnantioselective synthesisEnzymeMaterials science

Abstract

fetched live from OpenAlex

A tandem photo- and biocatalytic dynamic kinetic resolution of secondary alcohols and amines was achieved employing a commercially available lipase, Candida antarctica lipase B (CALB), and a heteroleptic copper complex. The process is an example of using copper-based photocatalysis to promote hydrogen atom transfer (HAT) processes employing thiyl radicals. Screening of 48 complexes and 5 disulfides identified Cu(dtbbpy)(DPEPhos)BF 4 and (Ph 3 SiS) 2 as an optimal catalyst system to promote the HAT process. The catalytic system represents a general system for radical-mediated racemization applicable to both aliphatic and aromatic alcohols and amines (18 examples, 60 → 97% yield, 76 → 99% ee).

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 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 score0.025
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.014
GPT teacher head0.263
Teacher spread0.249 · 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

Citations24
Published2023
Admission routes2
Has abstractyes

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