Enhanced reduction of nitrobenzene derivatives using reusable Ni nanoparticles supported on multi-layered poly(1,2-phenylenediamine)-coated layered double hydroxides
Bibliographic record
Abstract
Recently, nanomaterials with layered double hydroxide (LDH) cores have been the subject of intense research regarding their promising applications in organic synthesis. In this study, nitrobenzene reduction is investigated by designing and synthesizing a novel LDH-based heterogeneous catalyst containing a nickel-1,2-phenylenediamine complex. The Cu–Zn–Al LDH was functionalized with copolymer bearing a glycidyl methacrylate (GMA) linkage that makes it suitable for grafting with 1,2-phenylenediamine. Overall, the synthesized LDH@MPS-GMA-PDA-Ni was found to be a highly efficient heterogeneous nanocatalyst that can catalyze nitroarene reduction with high yields under mild conditions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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 teacher head, 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".