Boron nitride-palladium nanostructured catalyst: efficient reduction of nitrobenzene derivatives in water
Bibliographic record
Abstract
Abstract Boron nitride (BN) supported palladium (Pd) nanostructured catalyst, as an alternative support for heterogeneous reduction of nitrobenzene derivatives, was prepared by a mild reduction of a Pd precursor in water. The structural characteristics and distribution of the synthesized Pd nanoparticles (NPs) on BN support were investigated by transmission electron microscopy, scanning transmission electron microscopy, energy-dispersive x-ray spectroscopy and x-ray photoelectron spectroscopy methods. The potential and efficiency of the BN supported Pd NPs as an active and stable nanostructured catalyst were verified in the reduction of nitroaromatics. Excellent yields of the corresponding aryl amines in water were obtained and due discussion were included about the catalytic activity of the synthesized catalyst. It was also indicated that the nanostructured catalyst can be recycled at least for six consecutive cycles in the reduction of nitrobenzene, without losing significant activity.
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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) | 0.001 | 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 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".