The use of a chiral borate counteranion as a <sup>1</sup>H NMR shift reagent for cationic copper(I) complexes
Bibliographic record
Abstract
The chiral borate counteranion bis[(R)-1,1′-bi-2-naphtholato]borate (1) has been found to be a competent chiral 1H NMR shift reagent for cationic copper(I) complexes. This has been demonstrated by the addition of the Cu(NCMe)4+ salt of 1 to two classes of common chiral ligands in asymmetric catalysis: 2,2′-bis(di-p-tolylphosphino)-1,1′-binaphthyl (tol-BINAP) (2) and 2,2′-isopropylidenebis(4-phenyl-2-oxazoline) (3). In the case of ligand 2, the addition of 1 equiv. of either (R,R)-2 or (S,S)-2 to Cu(NCMe)4+1 results in well-resolved 1H NMR resonances for the two enantiomers. Examination of standard solutions of non-enantiopure 2 shows that the copper complex can be an effective NMR shift reagent of a wide range of enantiomeric compositions. Cu(NCMe)4+1 also generates distinct 1H NMR resonances for the two separate enantiomers of 2,2′-isopropylidenebis(4-phenyl-2-oxazoline) (3). However, attempts to employ this copper salt as a chiral NMR shift reagent for rac-3 led to the discovery of a new and unexpected equilibrium: [(R,R)-3]Cu+ + [(S,S)-3]Cu+ [Formula: see text] [(R,R)-3][(S,S)-3]Cu+ + Cu+. Key words: chiral counteranion, copper, chiral NMR shift reagent, ion pairing.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".