Catalytic and co-ordination chemistry of enolate oxazoline K2-N,O-ligands to group 9 & 11 transition metals
Bibliographic record
Abstract
The co-ordination chemistry and resulting catalytic potential of Group 9 and 11 transition metal centered complexes with the 2-acylmethyl-2-oxazoline skeleton are detailed. Each of the synthesized ligand species were treated with either a Copper (II) or Cobalt (II) salt to promote co-ordination, in all cases deprotonation of the ligand occurred. These complexes have, thereafter, been examined by infrared spectroscopy (IR), UV-Visible spectroscopy (UV-Vis), mass spectrometry (MS), cyclic voltammetry (CV), combustion analysis (EA) and x-ray diffraction and probed for their potential redox properties. In the case of Cu(II) chelated complexes, no desirable redox behaviour was observed. Although, with respect to Co(II) complexes, one complex displayed favourable redox potential. The redox active species have been shown to effectively catalyze the polymerization of methyl methacrylate with tosyl chloride as an initiator, through an ATRP-like mechanism. Work within also reflects preliminary co-ordination to Iridium and Rhodium metal centers. Successfully synthesized Iridium complexes have been tested with respect to their oxidative properties. Positive results have been observed in their ability to perform oxidative addition with both HSnPh3 and MeI. Both small molecule species have been effectively added to an Ir(I) complex, formally changing its oxidation state to Ir(III).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".