Informing our understanding of the copper–cuprizone reaction with computational chemistry
Bibliographic record
Abstract
The reaction of copper with bis(cyclohexanone)oxaldihydrazone (cuprizone) is a challenging coordination chemistry problem that has confounded attempts at elucidation for the past 70 years. The product of the reaction, a blue copper complex, wherein the cuprizone ligand is hydrolyzed, has been the primary focus during its history. We have recently characterized an additional green multi-copper product which contains unhydrolyzed cuprizone, which only added to the mystery. Using density functional structure models and thermodynamic calculations we address several of the long-standing questions surrounding the copper-cuprizone reaction, as well as identify the likely reaction pathway that gives rise to the blue and green products. Cu(II)-induced asymmetric hydrolysis of the cuprizone ligand is essential for formation of the blue product, followed by a series of Cu(II)-induced deprotonation and coordination events, with complex formation terminating with hydrolyzed cuprizone tautomerization and intramolecular electron transfer, generating a pseudo-macrocyclic Cu(III) species. Alternatively, in the presence of excess Cu(II), or in non-aqueous solvents, a green multi-Cu(II) complex forms comprised of alternating Cu(II)-cuprizone units. Structure calculations are supported by experimental data and represent the most rigorous approach to-date toward understanding the complex solution chemistry of copper with cuprizone.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".