A copper diimine‐based honeycomb‐like porous network as an efficient reduction catalyst
Bibliographic record
Abstract
Nitrophenols are among the widely used industrial chemicals worldwide; however, their hazardous effects on environment are a major concern nowadays. Therefore, the conversion of environmentally detrimental p‐nitrophenol (PNP) to industrially valuable p‐aminophenol (PAP), a prototype reaction, is an important organic transformation reaction. However, the traditional conversion of PNP to PAP is an expensive and environmentally unfriendly process. Here, we report a honeycomb‐like porous network with zeolite‐like channels formed by the self‐organization of copper, 1,10‐phenanthroline, 4,4′‐bipyridine, and water. This porous network effectively catalyzed the transformation of hazardous PNP to pharmaceutically valued PAP. In the presence of complex, PNP to PAP conversion occurred in a few minutes, which is otherwise a very sluggish process. To assess the kinetics, the catalytic conversion of PNP to PAP was studied at five different temperatures. The linearity of lnCt/Co versus temperature plot indicated pseudo‐first‐order kinetics. The copper complex with zeolite like channels may find applications as a reduction catalyst both on laboratory and industrial scales and in green chemistry for the remediation of pollutants.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".