Ligands for Iron‐based Homogeneous Catalysts for the Asymmetric Hydrogenation of Ketones and Imines
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".