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Record W2512303752 · doi:10.1002/9781118839621.ch8

Ligands for Iron‐based Homogeneous Catalysts for the Asymmetric Hydrogenation of Ketones and Imines

2016· other· en· W2512303752 on OpenAlexaff
Demyan E. Prokopchuk, Samantha A. M. Smith, Robert H. Morris

Bibliographic record

Venuenot available
Typeother
Languageen
FieldChemistry
TopicAsymmetric Hydrogenation and Catalysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCatalysisChemistryReactivity (psychology)BifunctionalLigand (biochemistry)CobaltRhodiumCombinatorial chemistryMetalPalladiumHomogeneous catalysisPlatinumSolventSubstrate (aquarium)Organic chemistry

Abstract

fetched live from OpenAlex

A current endeavor in research is the replacement of expensive and rare platinum group metal homogeneous catalysts with those of earth abundant metals such as iron, cobalt, nickel and zinc. In order for these cheaper metals to achieve comparable activity with conventional industrial catalysts, they must be activated by suitable ligands. These often offer a site of reactivity for substrate activation in addition to tuning the electronic properties of the metal and controlling the stereochemistry around the metal. Catalysis that is thought to exploit this extra point of reactivity at the ligand is termed metal–ligand bifunctional catalysis or metal–ligand cooperative catalysis. This chapter describes the design elements for ligands required to activate iron(II) so that the resulting complexes can serve for the first time as effective catalysts for the asymmetric reduction of ketones and imines, either by asymmetric transfer hydrogenation (ATH) from isopropanol solvent or asymmetric direct hydrogenation (ADH) using hydrogen gas.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.540
Threshold uncertainty score0.736

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.011
GPT teacher head0.257
Teacher spread0.247 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations9
Published2016
Admission routes1
Has abstractyes

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